hammer matthew justin

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 UNIVERSITY OF CINCINNATI Date: August 13, 2007 I, Matt Hammer, hereby submit this work as part of the requirements for the degree of: Master of Science in: Occupational Safety and Ergonomics It is entitled: Ergonomic Comparison of Keyboard and Touch Screen Data Entry While Standing and Sitting This work and its defense approved by: Chair: Kermit G. Davis, PhD Amit Bhattacharya, PhD

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UNIVERSITY OF CINCINNATI

Date: August 13, 2007

I, Matt Hammer,hereby submit this work as part of the requirements for the degree of:

Master of Sciencein:

Occupational Safety and ErgonomicsIt is entitled:

Ergonomic Comparison of Keyboard and Touch

Screen Data Entry While Standing and Sitting

This work and its defense approved by:

Chair: Kermit G. Davis, PhD

Amit Bhattacharya, PhD

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Ergonomic Comparison of Keyboard and Touch Screen Data Entry

While Standing and Sitting 

A thesis submitted to the

Division of Research and Advanced Studies of the University of Cincinnati

In partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

in the College of Medicine, Department of Environmental Health,

Division of Environmental and Occupational Hygiene

2007

by

Matthew Justin Hammer

B.S., Western Kentucky University, 2005

Thesis Committee:

Kermit G. Davis, PhD, Chair

Amit Bhattacharya, PhD

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ABSTRACT

Data entry is a common practice in many facilities throughout the world. From an ergonomic

prospective, these jobs place employees at risk of musculoskeletal disorders due to prolonged

sitting, static postures, and highly repetitive motions. The study’s objective was to evaluate the

differences between data entry tasks performed in both sitting and standing positions with

different work heights using a keyboard and a touch screen input device. Twenty subjects

performed multiple food order entries where postural analysis, error rate, self-reported regional

body discomfort, and usability data were measured. The results indicate that the angled touch

screen produced less ergonomic stress and body discomfort as compared to traditional keyboard

and was the preferred input device. The proper position of the touch screen depended upon the

height of the work surface—angled touch screen for the sitting condition and angled or

horizontal touch screen for the standing at high work surface height.

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ACKNOWLEDGMENTS

I would like to thank my advisor, Dr. Kermit Davis, for his help and guidance as an extremely

helpful mentor through this research project and writing of this thesis. I would also like to give a

special thanks to Susan Kotowski, a student of the Low Back Biomechanics & Workplace Stress

Lab at the University of Cincinnati whom was a vital contributor to this project. In addition, I

would like to thank committee member Dr. Amit Bhattacharya for his help throughout the

project. I am also grateful for fellow students Qiang Zheng and Balaji Sharma for their assistance

in the data collection and analysis. I would also like to mention that the support of my family,

friends, and girlfriend throughout this project and my years at the University of Cincinnati will

not be forgotten. Last but not least, I would like to acknowledge the ERC for funding my

scholarship while I was a student and also the Department of Environmental Health for funding

this research. Without the help and support of all these individuals, this research would not have

been possible.

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TABLE OF CONTENTS

1.0 INTRODUCTION……………………………………………………………………....…1-4

2.0 MATERIALS AND METHODS………………………………………………………...5-27 

2.1 Subject Selection…………………………………………………………………………….5

2.2 Study Design…………………………………………………………………………………..9

2.3 Procedure………………………………………………………………………………….….13

2.4 Test Set-up………………………………………………………………………………...….13

2.5 Ergonomic Postural Load…………………………………………………………………...14

2.6Quantification of Body Discomfort

………………………………………………………..25

2.7 Quantification of Usability………………………………………………………………….25

2.8 Error Rate……………………………………………………………………………………...26

2.9 Statistical Analyses……………………………………………………………………...…...26

3.0 RESULTS………………………………………………………………………………..28-51 

3.1 

Statistical Analyses Results: Analysis of Variance ……………………………………

...28 

3.2 Joint Kinematics: Joint Angles, Angular Velocities, and Angular Accelerations…...29 

3.3 

Body Discomfort …………………………………………………………………………….45 

3.4 Error Rate…………………………………………………………………………….47 

3.5 Usability Index……………………………………………………………………….47 

3.6  Rating of Preference…………………………………………………………………51 

4.0 DISCUSSION……………………………………………………………………………52-61

4.1 Limitations …………………………………………………………………………..59

4.2 Future Work………………………………………………………………………….60

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5.0 CONCLUSIONS………………………………………………………………………..62-63

REFERENCES……………………………………………………………………………...64-65

APPENDICES………………………………………………………………………………66-68

Appendix 1.0 Current Symptom Survey (Body Discomfort)……………………………67

Appendix 2.0 User Satisfaction Survey / (IBM Usability Survey).……………….……..68

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LIST OF TABLES AND FIGURES

Table 1: Demographic & Anthropometric Data

Table 2: Description of Anthropometric & Workstation Measurements

Table 3: Description of Joint Angles & Distances

Table 4: Summary of the P-values for the ANOVA test for the Maximum Joint Angles

Table 5: Summary of the P-values for the ANOVA test for the Maximum Angular Velocities

Table 6: Summary of the P-values for the ANOVA test for the Maximum Accelerations

Table 7: Summary of the P-values for the ANOVA test for the Discomfort

Table 8: Summary of the P-values for the ANOVA test for the Error Rate, Usability Index, andPerceived Ranking

Table 9: Summary of Kinematics

Table 10: Summary of Results

Figure 1 a-l: Pictures of Conditions and Acronym Descriptions

Figure 2 a-c: Front, Back, and Side Views of Marker Placement

Figure 3 a-d: Peak Motus Views of Sitting / Standing Combinations with Touch Screen /

Keyboard

Figure 4: Maximum Angles: Height Dependent for Lower Extremities

Figure 5: Maximum Angles: Height Dependent for Upper Extremities / Neck

Figure 6: Maximum Angles: Data Entry Device Dependent for Right and Left Hip

Figure 7: Maximum Angles: Data Entry Device Dependent for Right and Left Elbows, RightShoulder, and Neck

Figure 8: Maximum Angles: Height / Data Entry Device Dependent for Right Wrist

Figure 9: Maximum Angles: Height / Data Entry Device Dependent for Neck

Figure 10: Maximum Angles: Height / Gender Dependent for Left Knee

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Figure 11: Maximum Angles: Height / Gender Dependent for Left and Right Hip

Figure 12: Maximum Angles: Height / Gender Dependent for Left and Right Elbow

Figure 13: Maximum Angular Velocities: Height Dependent for Left and Right Knee and Hip,Right Elbow

Figure 14: Maximum Angular Velocities: Data Entry Device Dependent (Numerous Body Parts)

Figure 15: Maximum Angular Velocities: Data Entry Device / Gender Dependent for Right Knee

Figure 16: Maximum Angular Velocities: Data Entry Device / Gender Dependent for Left Knee

Figure 17: Maximum Angular Velocities: Data Entry Device / Gender Dependent for Neck

Figure 18: Maximum Accelerations: Height Dependent for Right Knee and Right Hip

Figure 19: Maximum Accelerations: Data Entry Device Dependent for Right and Left Elbows

Figure 20: Maximum Accelerations: Data Entry Device Dependent for Right Hip, Left Shoulder,and Neck

Figure 21: Maximum Accelerations: Data Entry Device / Gender Dependent for Right Elbow

Figure 22: Maximum Accelerations: Height / Gender Dependent for Right Hip

Figure 23: Maximum Accelerations: Height / Gender Dependent for Left Shoulder

Figure 24: Body Discomfort Rating for Upper and Lower Back

Figure 25: Body Discomfort Rating for Hand, Elbow, Shoulder, and Neck

Figure 26: Body Discomfort Rating for Leg, Knee, and Hip

Figure 27: Error Rate: (as a function of work surface height and type of input device)

Figure 28: Error Rate: (as a function of work surface height and type of order)

Figure 29: Usability Index (as a function of work surface height and type of input device)

Figure 30: Rank of Preference (as a function of work surface height and type of input device)

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1.0 INTRODUCTION

Data entry is a common practice in many facilities today, ranging from the manufacturing

industry entering the number of parts produced to the healthcare industry recording patient’s

data, to the restaurant industry entering food orders. In recent years, calls centers have increased

in popularity as the service sector has increased its prominence in the United States economy. In

fact, according to the North American Call Center Report of 2004 by  McDaniel Executive

 Recruiters, there are currently 50,600 call centers in the U.S. These call centers employ

approximately 2.86 million agent positions. However, this market will likely see a reduction in

size in the years to come due to self-service technologies, offshore outsourcing, and the effects of

the federal do-not-call list. Regardless of where these call centers are located, though, their

presence is well known and will continue to grow over the years to come.  The nature of the work

in these call centers is short periods of data entry while listening to information provided over the

phone. Traditionally, call centers have been locations where calls are either placed or received in

high volume for various purposes, including sales, marketing, telemarketing, customer service, or

technical support (Alibaba website, 2007).

The traditional office data entry jobs have similar requirements with the employee sitting

at a computer and processing information for long periods of time. From an ergonomic

perspective, these types of jobs place employees at risk of musculoskeletal discomfort due to

prolonged sitting, static or near static postures, and highly repetitive motions (Brophy, 1996).

Low intensity exertions and static postures that are typically found during data entry office work

have been found to increase the rate of discomfort in the neck, shoulders, and upper extremities

(Jensen et al., 2002). Static postures have also been identified as a contributing factor for low

back disorders (NIOSH, 1997). With many potential ergonomic stressors and a large number of

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workers typing in data on a keyboard, there is a need to investigate alternative data entry modes.

One potential input device option would be a touch screen. Touch screens have the ability to be

custom-designed so that entry buttons can be directly linked to specific types of data, which

would be optimal in food services and other retail industries. However, little is known about the

proper position of these screens with respect to ergonomic postural load. There are several

identified advantages of touch screens over traditional keyboard entry including: 1) Touching a

visual display of choices requires little thinking and is a form of direct manipulation that is easy

to learn, 2) Touch screens are the fastest pointing device, 3) Touch screens have easier hand-eye

coordination than mice or keyboards, 4) No extra workspace is required as with other pointing

devices, and 5) Touch screens are durable in public-access and in high-volume usage

(Shneiderman, 1991).

While it appears obvious that the angle of the touch screen would be dependent on the

anthropometric dimensions of the specific individual performing the data entry, past studies

have indicated that there is no specific optimal viewing angle for touch screens. However, in a

study conducted by Schultz and associates (1998), a recommended range of 30° to 55° from the

horizontal is given based on the fact that 92% of the subjects adjusted the display to an angle

within this range. It is also interesting to note that nearly half (46%) adjusted the angle between

44°  and 49°. While this recommended range is helpful in giving a rough estimation, the

research relied on the perceptions of the individuals rather than quantitative ergonomic

measurement. Furthermore, the proper angle of the touch screen may depend on the position of

the individual (sitting vs. standing) and the relative height of the screen to the individual (desk

at standing or sitting height).

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Another key issue referred to above that is a major ergonomic risk factor for data entry

 jobs is the prolonged sitting and postures. There have also been several studies that have

evaluated the effects of exercise breaks and work-rest regimens to reduce the effects of

prolonged postures during data entry tasks. Results concluded that “micro” breaks after short

periods of work may be a “good” option (Balci, 2004). However, it is unclear the proper

duration of these micro-breaks. A study by Henning et al. found that the average length of

breaks for data entry operators was about 27.4 seconds, which was based on the perception of

when they felt they were ready to continue data entry after the break. However, to date, there is

no absolute guideline regarding the break time required for adequate rest or recovery to take

place (McLean, et al., 2001). In lieu of this limited data for adequate breaks, another alternative

may be to introduce variable postures through altering between standing and sitting positions.

However, the proper position of the data entry device may be dependent on whether the

individual is in a sitting or standing position. The standing posture may also be compromised

by the position of the table. In other words, the proper position of the touch screen may depend

on whether the desk is at waist height (traditional desk height) or elbow height (standing

position).

Thus, this study investigated the ergonomic postural load (postures, accelerations, and

velocities) during data entry utilizing two different input devices: 1) keyboard and 2) touch

screen, which were positioned in three different positions. Further, the impact of standing

versus sitting on the postures and velocities adopted during data entry was also investigated.

It was hypothesized that the touch screen conditions would produce significantly greater

results in both postural load quantification and usability compared to the keyboard conditions.

In particular, the touch screen positioned at a 60°  angle from the vertical would provide

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optimal results in terms of postural load. By providing a sit-stand table and allowing the

subject to adjust the height of the work surface, it was expected that the results would prove

the benefit of these tables in each of the usability, current symptom, and postural load

categories. In addition to postural load, other important factors were also considered in the

evaluation of keyboards and touch screens. First, body discomfort provided an immediate

pain response to the postural demands. Discomfort may lead to increased error rates and

employee turnover (Jackson, 2006). Second, error rate is another important variable when

deciding the best data entry device and the proper position of that device. Therefore, a

comprehensive evaluation was undertaken to identify differences between keyboard and

touch screen data entry that quantified body postures, worker comfort, and performance.

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2.0 MATERIALS AND METHODS

This cross-sectional study evaluated the differences in posture, discomfort, and error rates

between the keyboard and touch screen data entry. The impact of touch screen position was

evaluated by comparing three different positions: 1) vertical, 2) horizontal, and 3) 60o  angled

position. In addition, the impact of standing was evaluated under two conditions: 1) standing

with desk height at traditional height (73.66 cm) and 2) standing height with elevated desk height

(dependent on subjects’ selection). A sit-stand table with a pneumatic lift function was used to

adjust the desk surface up and down, depending on the anthropometric data and desired position

of the subject.

 2.1 Subject Selection:

Twenty subjects (10 male and 10 female) participated in the study. The subjects were recruited

using a flier that was posted in various places near the University of Cincinnati campus. In order

to be eligible to participate, subjects had to fall in the age range of 18-65 years old. All subjects

were required to sign a consent form approved by the University of Cincinnati Institutional

Review Board (Protocol # 06-09-27-01E). All the subjects were either students, staff members

employed at the university, or colleagues of other subjects with limited data entry experience.

For each subject, standard anthropometric measurements were used to quantify subject

dimensions using standard procedures (NASA 1024). A scale (Model # 7075 3903 V1584), a

GPM Anthropometer (SiberHegner & Co. Ltd), and a tape measure were used to collect various

measurements. Anthropometric and demographic data included: age, birth date, gender, body

weight, stature, shoulder height, elbow height, hip height, knee height, upper arm length, lower

arm length, torso length, upper leg length, and torso circumference. In addition to these

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variables, table and chair height were measured using the Peak Motus Motion Capture System.

Reflective markers were placed on the side of the work surface and the back of the chair cushion.

These markers then provided accurate height measurements by capturing the distance between

the floor and these points. Table 1 provides a summary of the anthropometric and demographic

data. Table 2 provides descriptions of each anthropometric and workstation measurement.

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Table 1: Demographic & Anthropometric Data

Mean S.D.

Male 25.1 4.1

Age (years) Female 31.2 12.5

Male 177.7 5.5

Height (cm)  Female 164.9 7.9

Male 190.4 32.5

Weight (lbs)  Female 154.6 35.5

Male 148.5 5.9

Shoulder Height (cm)  Female 137.1 7.1

Male 109.5 4.4

Elbow Height (cm)  Female 101.4 6.0

Male 102.5 4.3

Hip Height (cm)  Female 95.6 6.2

Male 54.7 3.8

Knee Height (cm)  Female 49.9 3.5

Male 35.6 1.6Upper Arm Length

(cm)  Female 33.8 1.5

Male 46.7 1.8Lower Arm Length

(cm)  Female 43.3 1.4

Male 48.2 1.9

Upper Leg Length (cm)  Female 46.5 3.2

Male 50.3 2.5

Torso Length(cm)

  Female 44.3 3.7Male 92.2 12.8Torso Circumference

(cm)  Female 83.2 17.6

Male 8

RIGHT HANDDOMINANT Female 9

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Table 2: Description of Anthropometric & Workstation Measurements

Table 2: Description of Anthropometric & Workstation Measurements

Type Description

Stature Height of the subject while in a standing position, with shoulders back and arms at sidesShoulder Height Vertical distance from the floor to the superior aspect of the acromion.

Elbow HeightVertical distance from the floor to the posterior tip of the olecranon when the arm isflexed to 90 degrees at the elbow and the shoulder is in normal position

Hip Height Vertical distance from the floor to the innominate bone (hip bone)

Knee HeightVertical distance from the foot-resting surface to the top of the knee cap, just above thepatella

Upper Arm Length

Vertical distance from the posterior tip of the olecranon to the superior aspect of theacromion when the arm is flexed to 90 degrees at the elbow and the shoulder is innormal position

Lower Arm Length

Horizontal distance from the posterior tip of the olecranon to the third metacarpal when

the arm is flexed to 90 degrees at the elbow and the fingers are extended

Torso Length Vertical distance from the L5 vertebrae to the bump just above the C2 spinous process

Torso CircumferenceCircumference of the individuals torso, measured at the abdomen section directly ontop of the navel

Upper Leg LengthVertical distance from top of the knee cap, just above the patella, to the innominatebone (hip)

Chair HeightMeasured as the height from the floor to the chair cushion, depending on the subject’spreference

Standing Surface HeightMeasured as the height of the working surface of the sit-stand table, depending on thesubject’s preference

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 2.2 Study Design:

The study was designed to evaluate twelve specific combinations of the keyboard or the touch

screen conditions. There were three independent variables: 1) input device (keyboard vs touch

screen), 2) position of touch screen (vertical, horizontal, and angled), and 3) working height

(sitting with desk at sitting height, standing with desk at sitting height, and standing with desk at

standing height). The sitting height desk height was 73.66 cm, a height commonly found in the

workplace and recommended in the literature (Brophy, 1996). The standing heights were user

selected, which were adjusted by a pneumatically adjustable sit-stand table. Standing heights

were measured and recorded for each subject for each task. In all, there were twelve conditions

completed by each subject. A counter balanced and randomized strategy was utilized to ensure

bias was minimized during testing. The three sit-stand conditions (sitting, standing with desk at

sitting height, and standing with desk at standing height) were counter-balanced with the input

device conditions (keyboard, vertical touch screen, horizontal touch screen, and angled touch

screen) being randomly completed within each sit-stand condition. A brief description and photo

of each condition can be found in Figure 1.

There were four specific dependent variables evaluated within this study: 1) postural load

and kinematics; 2) body discomfort; 3) usability data; and 4) error rate. Postural load was

quantified by using the Peak Motus Motion Capture System Version 8.1.4. The basic concept of

this system is using reflective markers to identify joint locations, which allow factors such as

 joint angles, velocities, accelerations, and distances to be captured. Body discomfort data was

captured using a Body Discomfort / Current Symptom questionnaire that was given to the

subjects at the completion of each condition. This questionnaire allowed the subject to express if

any discomfort was experienced while performing the data entry tasks. It is broken down into

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different body parts so the subject can be specific as to where the discomfort was. A second

questionnaire was administered throughout the duration of the study to capture usability data.

This questionnaire contained 18 questions that were targeted at determining how useful the

subject felt that the conditions were. Finally, the last dependent variable in this study was error

rate. This variable is important since the ultimate purpose was to compare keyboards and touch

screens. Error rate was captured by simply tracking the number of errors made during each trial

performed by the subject.

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Figure 1: a-l

a

SKH

Standing, Keyboard, High

Surface 

b

SKL

Standing, Keyboard, Low

Surface 

c

CKL

Chair, Keyboard, Low Surface

d

SAH

Standing, Angled Screen, High

Surface 

e

SAL

Standing, Angled Screen, Low

Surface 

f

CAL

Chair, Angled Screen, Low

Surface 

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g

SVH

Standing, Vertical Screen, High

Surface 

h

SVL

Standing, Vertical Screen, Low

Surface 

i

CVL

Chair, Vertical Screen, Low

Surface 

 j

SHH

Standing, Horizontal Screen,

High Surface 

k

SHL

Standing, Horizontal Screen,

Low Surface 

l

CHL

Chair, Horizontal Screen, Low

Surface 

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 2.3 Procedure:

After being enrolled into the study, each subject read and signed a consent form. Prior to

beginning the data collection, a full explanation of the study and specifics about the touch screen

and keyboard were given. When subjects were comfortable with the explanation, a short practice

session was completed utilizing both the keyboard and touch screen input devices. Under each

condition (both practice and actual), a list of orders was read, simulating the processing of a

phone order that required the subject to enter the information into the computer via keyboard or

touch screen. There was a predetermined script that was read out loud by a researcher (who was

sitting out of sight at the other end of the room). For this script, there were 18 different orders (6

easy, 6 moderate, 6 complex) created using various combinations of up to 41 different menu

items. The complexity of the orders was determined based on the number of items to be entered

(easy = 3 to 5 items, moderate = 6 to 10 items, and complex = 11 to 15 items). Specifically,

menu items were 18 different drinks, 4 different appetizers, 16 different main courses, and 3

different appetizers. The subject was required to enter six orders for each of the twelve

conditions, for a total data entry of 72 orders. To allow a comparison of postural movements

required to complete the order, the same six orders were given for each condition. Throughout

the data collection process among the twelve conditions, each order was randomized and

arranged in a new sequence to prevent the subject from memorizing what was to be entered. The

six orders entered consisted of: two easy, two moderate, and two complex.

 2.4 Test Set-up:

The complete test set-up included 6 motion-capturing cameras, the adjustable sit/stand

table, the chair (with no back or arms), the keyboard, and the VDT computer monitor or the

touch screen. The cameras were part of the Peak Motus Motion Analysis system, where

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reflective markers could be picked up to identify joint locations and calculate joint angles,

velocities, and distances. To aid in the identification of joint locations for postural analysis, each

subject was equipped with nineteen reflective markers placed on the anatomical joint locations

(left and right sides) at the base of the fifth metacarpal, the wrist, elbow, shoulder, hip, knee,

ankle, and temple, along with the base of the neck. One additional marker was placed on the

subjects’ left thigh to aid in the identification during the digitizing process. Figure 2: a-c

illustrates where these markers were placed on the subject. A video camera was also positioned

to capture each trial for every subject. These videos were later converted to Windows Media files

and reviewed to give length of trials, postures assumed, and errors made. The overall data

collection time for each subject lasted about 3.5 hours, depending on the speed of data entry and

the number of mistakes made. Each trial time ranged anywhere from 20 seconds to 80 seconds,

again depending on the complexity of the order and the speed of the entry.

 2.5 Ergonomic Postural Load Quantification:

The whole body postures and velocities were captured by the Peak Motus Motion

Measuring System. The system utilizes video capturing capabilities through the use of reflective

markers located at bony landmarks that designate specific joints of interest. The joint angles are

then calculated by the Motus software that locates the motion segments via reflective markers.

The Peak Motus System has standard data reduction algorithms for editing, filtering, and

calculating linear and angular displacements, velocities, and accelerations, which was utilized to

calculate joint angles and velocities.

In this particular study, three templates were created: sitting, standing, and calibration

templates. These templates were created to assign proper labels to the reflective markers that

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would be picked up by the cameras. Also, the templates were designed to identify and determine

certain path segments throughout the trial. The segments identified included standard joint

connections (ankle to knee, knee to hip, hip to shoulder, shoulder to elbow, elbow to wrist, and

wrist to 5th

 metacarpal) on both sides of the body. Also, specialized segments of interest included

monitor distance (forehead to monitor) and keyboard distance (left hip to keyboard). Sitting

templates were used for the four conditions on which the subject was required to sit, and the

remaining eight conditions were captured using the standing templates. Before data collection

began each day, the Peak Motus Motion Analysis System was calibrated to ensure that the

cameras were capturing the correct volume and that all markers would be seen. This calibration

was done by flipping through all six cameras and eliminating any unwanted reflections. The

volume was then assured by waving a reflective wand in the area to be captured and ensuring

that the standard deviation was below 0.002. Thus, the video capturing system provided accurate

estimations of the joint angles and velocities.

Using the results captured from the Peak Motus Motion Capture System, each trial was

then reviewed using digitizing software in which the reflective markers could be connected to

form segments and a stick figure which identified the subjects’ body. Figure 3 a-d shows what

the stick figure looks like after all markers have been identified and segments have been

connected. The trials were completely reviewed to ensure all markers were present during the

entire active trial. Once the trials were digitized and all segments were formed to create the stick

figure, the next step was to use the Peak Motus system to calculate joint angles, velocities, and

appropriate distances. The significant joint angles that were of interest included the angle of the

upper and lower arms, the wrists, trunk, and neck. Additional measures about the workstation-

subject interaction was also collected and included: 1) chair height, 2) standing surface height, 3)

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distance between the subjects’ forehead and the monitor, and 4) distance between the subject’s

hip and the keyboard. By knowing these distances, it was possible to review how the different

conditions required different workstation-person interactions. Table 3 provides a description of

how these joint angles and distances were measured.

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Figure 2:

a.) Front View 

L Left Ankle

Forehead

Right TempleLeft Temple

Right Shoulder

Left Shoulde

Right Elbow

Left Elbow

Left HipRight Hip

Left WristRight Wrist

Left Thigh

Left KneeRight Knee

Right Ankle

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b.) Back View

Right

5th

 Metacarpal

Right Knee

Right

Ankle

Neck

Right Shoulde

Left Shoulder

Right Elbo

Right Hip

Left Elbow

Left Hip

Left WristRight Wris

Left 5t

 

Metacarpal

Left Knee

Left Ankle

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c.) Side View

Forehead

Left Temple

Left Shoulder

Left Hip

Left Thigh

Left Ankle

Left Knee

Left Elbow

Left Wrist

Left 5th

 Metacarp

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Figure 3: 

a.) Sitting with a touch screen

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b.) Sitting with a keyboard

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c.) Standing with a touch screen

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d.) Standing with a keyboard

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Table 3: Description of Joint Angles and Distances

Table 3: Description of Joint Angles & Distances Measured Using Peak Motus

Right & LeftShoulder Measured as the angle between the hip and the elbow markers

Right & Left Elbow Measured as the angle between the shoulder and the wrist markers

Right and Left Wrist Measured as the angle between the elbow and the 5th metacarpal markers

Right and Left Hip Measured as the angle between the knee and the shoulder markers

Right and Left Knee Measured as the angle between the ankle and the hip markers

Neck Flexion Measured as the angle between the shoulder and the temple markers

Monitor Distance Measured as the distance between the forehead and the computer monitor markers

Keyboard DistanceMeasured as the distance between the left hip and the keyboard markers (to givedistance of subjects body from the data entry device)

Chair Height Measured as the vertical distance from the floor to the marker on the chair cushion

Table HeightMeasured as the vertical distance from the floor to the marker on the side of theworksurface

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 2.6 Quantification of Body Discomfort:

To assess the discomfort levels of subjects throughout the study, a Body Discomfort

Survey was utilized to provide subjective data and opinions of the subjects. By having the

subject complete this survey after each condition, discomfort levels could be quantified and

compared between conditions. The Body Discomfort Survey (Appendix 1) assessed the current

pain levels in nine different body regions including the neck, shoulder, elbow, hand / wrist, upper

back, low back, hip, knee, and lower leg / foot. Immediately after completing a specific

condition, subjects circled the appropriate pain level on a 0 to 10 Likert scale, with 0 being no

pain, and 10 being most severe pain imaginable. Usability data was also collected and considered

as secondary variables. This data represented an outcome variable of overall user satisfaction

with the condition being completed (considering all independent variables (input device, working

surface height, and position of touch screen)).

 2.7 Quantification of Usability:

As mentioned above, a questionnaire was also used to capture usability data. The

Usability Survey (Appendix 2), which was adapted from the IBM Usability Survey, asks

eighteen questions about the subjects’ opinion of the current workstation. The content of the

questions basically refers to the workstation, the data entry device, screen layout, and overall

ease of use. Responses for this survey range from 1-7, with 1 being “strongly disagree” and 7

being “strongly agree.” This survey served as an effective tool in representing the subjects’

overall satisfaction level with the condition.

Both the Body Discomfort Survey and the Usability Survey were administered after

every condition (total of 12 times). Once all 12 conditions were completed, the conditions were

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then reviewed with the subject and they were asked to rank them in order of overall preference.

Refer to the results section and Figure 8 to review more on the rank of preferences collected.

 2.8 Error Rate:

As mentioned above, it was also important to compare the touch screen and the keyboard

by the error rates throughout the study. By collecting the amount of errors made and during

which condition the errors occurred, it was possible to evaluate the results to look for trends of

errors. During each of the four keyboard conditions, error rates were captured by verifying that

the order in which the menu items were read was input in that exact order. This was done by

programming the Excel file being used to only show the menu items in a specific column if in

fact the subject had input the items in the correct manner. At the completion of each condition,

the researcher would view the screen to check for errors. On the other hand, during each of the

eight touch screen conditions, the researcher could determine if errors were made by assuring

that what the subject announced as the “total amount due” actually matched what the correct

amount was. If an error was to be made during any of these trials, the subject was required to

repeat the trial. If an error was made on the second try, that particular trial was skipped and then

repeated at the end of that condition. Also, to save time during the data collection, subjects were

instructed to admit their errors right away if they knew they had made a mistake.

 2.9 Statistical Analyses:

Microsoft Excel statistical formulas were used to calculate descriptive statistics such as

the mean and standard deviations of all the questionnaires, errors, rankings, and anthropometric

data. Paired t-tests were performed to determine if group characteristics differed by gender.

Analysis of Variance (ANOVA) was conducted using the Statistical Analysis Software (SAS)

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program to determine if the results for the symptom surveys, usability questionnaires, errors and

rankings differed by group. Post-hoc Tukey tests were conducted on significant results. For the

Motus motion analysis data (joint positions, velocities, and accelerations), a database was

compiled containing the maximum and average values and the standard deviations for each trial

along with the trial details (subject, gender, height of desk, data entry device, and task

complexity). Using SAS, the next step was to determine which groups were statistically different

from each other using a repeated measures split-plot ANOVA at a 95% confidence level. The

final step was to perform post-hoc Tukey’s tests to determine which specific variables differed

from each other.

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3.0 RESULTS

 3.1 Statistical Analyses Results: Analysis of Variance: 

 3.1.a. Joint Kinematics:

The results of the Analyses of Variance indicated several significant effects for the joint

angle, angular velocity, and angular accelerations for many of the body joints that were

monitored (See Tables 1 to 3). As expected, the work surface height had a significant impact on

the joint angles and angular velocities of the majority of the joints (except for left wrist for

posture and right and left shoulders, right and left wrists, and left elbow for velocity). The

angular accelerations were significantly impacted by the work surface height for right and left

knees. The type of input device also had significant impact on the joint angle for the right and

left hip, right and left shoulder, right and left elbow, right wrist, and neck as well as angular

velocity for the right knee, right hip, right and left shoulders, right and left elbow, and neck. The

type of input device also had some impact on the angular accelerations for the left knee, left hip,

right and left elbow, and neck. Gender was only found to be significant for the joint angle for

left knee and left hip. The complexity of the data entry task was found not to impact any of the

 joint kinematics.

There were several significant interactions for the joint kinematics. Many of the

significant interactions were found for the joint angles (Table 1). The type of input device by

work surface height interaction was significant for all joint angles except left wrist but was only

significant for right knee, right and left shoulder, and right elbow for angular velocity and right

hip for angular acceleration. The gender by type of input device interaction was also an effect

found to be significant for multiple joint angles (e.g. left knee, right and left hip, right and left

elbow, and right wrist) and some velocities and accelerations (e.g. right and left knee and neck

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for velocity, left hip for acceleration). The work surface height by gender interaction was also

found to be significant for several kinematic variables: right and left hip and right elbow for joint

angle, right knee, right and left shoulder for angular velocity, and left knee and right elbow for

angular acceleration. One variable (left shoulder joint angle) had a significant effect for the work

surface height by task interaction. Finally there were three significant three-way interactions, all

for the works surface height by type of input device by gender interaction. However, upon visual

inspection the interaction was not meaningful so those results will not be discussed.

 3.1.b. Body Discomfort, Error Rate, Usability Index, and Perceived Ranking of Preference:

The results of the ANOVA for discomfort in the different body regions are shown in

Table 4. The condition effect, which is the combination of type of input device and work surface

height, was found to be significant for discomfort in all body regions. There was only one

significant interaction for condition and gender, which was for lower back discomfort.

Table 5 shows the results of the ANOVA analyses for error rate, usability index, and

ranking. For all three of the dependent variables, the effect of condition was significant at

p<0.05. No interaction between gender and condition was found for the error rate, usability

index, or ranking.

 3.2. Joint Kinematics: Joint Angles, Angular Velocities, and Angular Accelerations:

 3.2.a. Joint Angles:

While there were several joints that had significant differences among the different

effects, caution must be stressed about the interpretation of the actual angles. One has to keep in

mind that a larger angle does not always mean there is more risk. There are several examples of

this where a joint may be bent around 90° (e.g. knee or elbow) and straight when close to 180° 

(e.g. knee when standing or elbow).

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Table 6: Summary of the P-values for the Analysis of Variance test for the maximum accelerations

and left knee, right and left hip, right and left shoulder, right and left elbow, right and left

Accelerations RKNEE LKNEE RHIP LHIP RSHLDR LSHLDR RELBOW LELB

Gender (GNDR) 0.07 0.37 0.90 0.28 0.89 0.55 0.12 0.6

Work Surface Height (HGHT) <.0001 <.0001 0.18 0.12 0.91 0.94 0.54 0.8

Type of Input Device (DEVICE) 0.36 0.01 0.17 0.01 0.48 0.49 0.01 0.00

Task Complexity (TASK) 0.44 0.12 0.26 0.78 0.40 0.41 0.15 0.1

HGHT*GNDR 0.60 0.05 0.46 0.95 0.40 0.57 0.05 0.4

DEVICE*GNDR 0.43 0.76 0.20 0.02 0.33 0.35 0.12 0.9

TASK*GNDR 0.27 0.18 0.15 0.80 0.60 0.39 0.16 0.7

HGHT*DEVICE 0.07 0.02 0.48 0.06 0.39 0.53 0.005 0.3

HGHT*TASK 0.07 0.53 0.28 0.68 0.61 0.61 0.92 0.7

DEVICE*TASK 0.59 0.06 0.13 0.91 0.51 0.61 0.81 0.1

HGHT*DEVICE*GNDR 0.09 0.35 0.13 0.53 0.55 0.51 0.08 0.6

HGHT*TASK*GNDR 0.96 0.41 0.38 0.45 0.70 0.64 0.32 0.7

DEVICE*TASK*GNDR 0.99 0.96 0.46 0.61 0.44 0.59 0.55 0.5

HGHT*DEVICE*TASK 0.10 0.19 0.12 0.99 0.75 0.70 0.10 0.4

HGHT*DEVICE*TASK*GNDR 0.49 0.37 0.19 0.81 0.84 0.77 0.78 0.9

Table 7: Summary of the P-values for the Analysis of Variance test for the discomfort: knee, hips,

neck, lower back, and upper back.

Accelerations Knees Hips Shoulders Elbows Wrists Neck

Gender (GNDR) 0.68 0.39 0.80 0.34 0.89 0.84

Condition (COND) <.0001 <.0001 <.0001 <.0001 0.03 <.0001

GNDR*COND 0.47 0.21 0.34 0.23 0.32 0.06

Table 8: Summary of the P-values for the Analysis of Variance test for the error rate, usability ind

Accelerations Error Rate UsabilityIndex Ranking

Gender (GNDR) 0.85 0.73 N/A

Condition (COND) 0.02 <.0001 <.0001

GNDR*COND 0.13 0.93 0.53

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It was not surprising that the knee and hip angles were different as a function of work

surface height where the standing conditions had more neutral postures (closer to 180o) as

compared to the sitting condition (closer to 90o) (See Figure 4). There were some small

differences in the knee and hip angles for the standing at low surface and standing at high surface

(about 5o for knee and 15o for hip). Other differences were found for the elbows, shoulders and

neck for the different work surface heights (Figure 5). The sitting condition had the most flexed

elbow positions (at about 100o) with the standing at the low height having the most extended

elbow position (about 145o). Both the sitting and standing at the low height table conditions had

greater shoulder flexion than the standing at the higher height table (about 10

o

). A similar trend

was found between the low height work surface (sitting or standing) and standing at the high

height for neck (about 10o less flexion).

In Figure 6, the vertical position of the touch screen input device had the most flexed hip

position (in both hips) by about 10o. Similar trends were found for the joint angles of right and

left elbow (about 7.5o), right shoulder (about 15

o), and neck (up to 20

o) (see Figure 7). For the

neck, the keyboard condition was found to require the most flexed posture (10o more than the

vertical touch screen).

There were a couple of interesting interactions between work surface height and type of

input device. In Figure 8, the horizontal touch screen and keyboard input devices were found to

have the most right wrist flexion when the work surface was low and standing. Standing at the

high surface utilizing these two types of input devices produced the least amount of right wrist

flexion (about 5o  less). There was little difference between the different work surface heights

when using the vertical or angled touch screens (less than 2o). The best neck postures were found

for the angled and horizontal touch screens, particularly for the standing high work surface (See

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Maximum Angles:

Height Dependent

0

50

100

150

200

250

Right Knee Left Knee Right Hip Left Hip

   D  e  g  r  e  e  s

Sitting Standing, High Surface Standing, Low Surface

 

Figure 4: Maximum angles of the right and left lower extremities (knee and hip) as a function of

work surface height. Alpha characters that are similar are not significantly different.

Maximum Angles:

Height Dependent

0

20

40

60

80

100

120

140

160

180

Right Elbow Left Elbow Right

Shoulder

 Left Shoulder Neck

   D  e  g  r  e  e  s

Sitting Standing, High Surface Standing, Low Surface

 Figure 5: Maximum angles of the right and left upper extremities (elbow and shoulder) and neck

as a function of work surface height. Alpha characters that are similar are notsignificantly different.

B

A

A

A B

C

A

B

C

A B

C

BA

A

A

B

C

BAA

A

B

C

B

A A

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Maximum Angles:

Data Entry Device Dependent

80

100

120

140

160

180

200

Right Hip Left Hip

   D  e  g  r  e  e  s

Angled Horizontal Vertical Keyboard

 Figure 6: Maximum angles of the right and left hip as a function of type of data entry device.

Alpha characters that are similar are not significantly different.

Maximum Angles:

Data Entry Device Dependent

0

20

40

60

80

100

120

140

160

180

Right Elbow Left Elbow Right Shoulder Neck

   D  e  g  r  e  e  s

Angled Horizontal Vertical Keyboard

 Figure 7: Maximum angles of the right and left elbow, right shoulder, and neck as a function of

type of data entry device. Alpha characters that are similar are not significantly

different.

BA A A B AAA

A

AB

BCC

A

BB B

BA A

A

AB

CC

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Maximum Angles:

Height / Data Entry Device

RIGHT WRIST

0

2

4

6

8

10

12

14

16

ANGLED HORIZONTAL KEYBOARD VERTICAL

Data Entry Device

   D  e  g  r  e  e  s

StandHigh Sit StandLow

 Figure 8: Maximum angles of the right wrist as a function of work surface height and type of data

entry device.

Maximum Angles:

Height / Data Entry Device

NECK

105

115

125

135

145

155

165

ANGLED HORIZONTAL KEYBOARD VERTICAL

Data Entry Device

   D  e  g  r  e  e  s

StandHigh Sit StandLow

 Figure 9: Maximum angles of the neck as a function of work surface height and type of data entry

device.

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Figure 9). The keyboard and vertical touch screen had significantly more neck flexion,

particularly when standing at the low work surface height. In all, the neck flexion was impacted

by both the type of input device and the height of the work surface.

Although there was a small difference between males and females for left knee flexion,

the difference only occurred in the sitting position with the low work surface (See Figure 10). As

expected from the main effect of surface height for left knee angle, the standing condition had

straighter legs. A similar trend was found for left and right hip angle (see Figure 11) where any

difference between males and females occurred for the sitting condition, although this was

minimal.

A more complex interaction between gender and work surface height (Figure 12) was

found for right and left elbow angle. There was a general trend of more extended elbow angles

for the standing positions as compared to the sitting condition. Males used a straighter arm (large

elbow angle) as compared to females when in the sitting in low work surface and standing in the

high surface. Under the standing high surface, females utilized the extended elbow angle. Under

the standing low surface height, the females actually had elbow angles that were straighter

(opposite of the other surface height conditions).

 3.2.b. Angular Velocities:

In Figure 13, the lower extremity angular velocities were impacted by the surface height

conditions. In general, the sitting at low surface height had lower angular velocities for knee and

hip motion. No differences were found between the two standing height conditions. Standing at

the high work surface was found to have the lowest elbow angular velocity (about 5 to 8o /s

slower). No differences were found between sitting and standing at the low work surface height.

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Height / Gender

ELBOW

80

90

100

110

120

130

140

150

160

Standing High Surface Sitting Standing Low Surface

   D  e  g  r  e  e  s

LELBOW - Male LELBOW - Female RELBOW - Male RELBOW - Female

 Figure 12: Maximum angles of the right and left elbow as a function of work surface height and

gender 

Maximum Angular Velocities:

Height Dependent

0

20

40

60

80

100

120

Right Knee Left Knee Right Hip Left Hip Right Elbow

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

Sitting Standing, High Surface Standing, Low Surface

 Figure 13: Maximum angular velocities of the right and left lower extremities (knee and hip) and

right elbow as a function of work surface height. Alpha characters that are similar are

not significantly different.

B

A

A

B

A

A

A

B

AB

B

A

A BA

A

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In Figure 14, the type of input device impacted the angular velocities of several joints:

right knee, right hip, right and left elbow, right and left shoulder, and neck. In general, the

keyboard and vertical touch screen had the greatest velocities for all these joints while the angled

and horizontal touch screen had the lowest velocities (around 10 to 25o /s between the highest and

lowest). The differences between the input devices were influenced by gender (Figure 15).

Differences between the input devices were more pronounced for females where the keyboard

and vertical touch pad devices produced significantly more velocity in the right knee. A similar

effect was found for the left knee where the main difference for the vertical touch screen was due

to the females who had more angular velocity than the males (almost 25

 o

 /s). Another difference

between males and females was noted for the horizontal touch screen condition where females

had more angular velocity on the left knee (about 12o /s). Neck velocities were also found to be

different between the males and females where females had the higher velocities when using the

horizontal touch screen and keyboard input devices but lower velocities when using the angled

touch screen (see Figure 17). Basically, the interaction indicated that males and females moved

their necks differently while utilizing the different input devices.

 3.2.c. Angular Accelerations:

The maximum angular accelerations for the right knee and right hip had a similar trend as

the velocity trends for the different work surface heights (Figure 18). Basically, the sitting

accelerations were lower than both of the standing conditions. The right and left elbow

accelerations were also found to be lowest for the horizontal touch screen input device (about 40

o /s

2), refer to Figure 19. The angled touch screen condition was also found to significantly reduce

the left accelerations as compared to the keyboard and vertical touch screen. Several other joints

also showed increase accelerations for the keyboard input device conditions as compared to the

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Maximum Angular Velocities:

Data Entry Device Dependent

0

20

40

60

80

100

120

140

160

RKNEE RHIP RELBOW LELBOW RSHLDR LSHLDR NECK

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

An led Horizontal Vertical Ke board

 

Figure 14: Maximum angular velocities of the right knee, right hip, right and left upper extremities

(elbow and shoulder) and neck as a function of type of data entry device. Alpha

characters that are similar are not significantly different.

Maximum Angular Velocities: Gender / Data Entry DeviceRight Knee

10

20

30

40

50

60

Angle Horizontal Keyboard Vertical

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

Female Male

 Figure 15: Maximum angular velocities of the right knee as a function of type of data entry device

and gender.

A

AB

BB

A

AB

AB

B

A

B

BB

AAB

AB

B A

B

B

B

A

A

BB

AA

B

AB

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Maximum Angular Velocities: Gender / Data Entry Device

Left Knee

10

20

30

40

50

60

Angle Horizontal Keyboard Vertical

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

Female Male

 

Figure 16: Maximum angular velocities of the left knee as a function of type of data entry deviceand gender.

Maximum Angular Velocities: Gender / Data Entry Device

Neck

30

40

50

60

70

80

90

Angle Horizontal Keyboard Vertical

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

Female Male

 Figure 17: Maximum angular velocities of the neck as a function of type of data entry device and

gender.

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Maximum Acceleration:

Height Dependent

0

100

200

300

400

500

600

700

Right Knee Right Hip

   D  e  g  r  e  e  s   /   S  e  c  o  n   d   2

Sitting Standing, High Surface Standing, Low Surface

 Figure 18: Maximum angular accelerations of the right knee and right hip as a function of work

surface height. Alpha characters that are similar are not significantly different.

Maximum Acceleration:

Data Entry Device Dependent

0

100

200

300

400

500

600

700

800

Right Elbow Left Elbow

   D  e  g  r  e  e  s   /   S  e  c  o  n   d   2

Angled Horizontal Vertical Keyboard

 Figure 19: Maximum angular accelerations of the right and left elbow as a function of type of data

entry device. Alpha characters that are similar are not significantly different.

B

A

A

B

A A

AABAB B A

AB

BC

C

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touch screens, specifically the right hip and the neck (Figure 20). The left shoulder acceleration

was lowest for the angled touch screen and highest for vertical touch screen.

The effect of the type of input device on elbow acceleration was driven by females

(Figure 21). The differences between the devices were a direct result of the female responses

since the males right elbow accelerations was virtually unchanged across the different input

devices. The impact of gender was also seen for right hip and right shoulder for the different

work surface heights (Figures 22 and 23). Females produced more right hip accelerations during

the standing low surface than males, although the general trends remained across the work

surface height conditions. A more interesting trend between the genders occurred for the right

shoulder accelerations where females had greater accelerations than the males during the low

height conditions (both sitting and standing).

Maximum Acceleration:

Data Entry Device Dependent

0

100

200

300

400

500

600

700

Right Hip Left Shoulder Neck

   D

  e  g  r  e  e  s   /   S  e  c  o  n   d

   2

Angled Horizontal Vertical Keyboard

 Figure 20: Maximum angular accelerations of the right and left elbow as a function of type of data

entry device. Alpha characters that are similar are not significantly different.

A

BBB

A

ABABB

A

AB

BB

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Gender / Data Entry Device

RIGHT ELBOW

300

350

400

450

500

550

ANGLED HORIZONTAL KEYBOARD VERTICAL

   D  e  g  r  e  e  s   /   S  e  c  o  n   d    2

RELBOW - FemaleRELBOW - Male

 Figure 21: Maximum angular accelerations of the right elbow as a function of type of data entry

device and gender.

Height / Gender

RIGHT HIP

100

150

200

250

300

350

Standing High Surface Sitting Standing Low Surface

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

   2

RHIP - Male RHIP - Female

 

Figure 22: Maximum angular accelerations of the right hip as a function of work surface height

and gender.

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Height / Gender

LEFT SHOULDER

100

120

140

160

180

200

220

240

260280

300

Standing High Surface Sitting Standing Low Surface

   D  e  g  r  e  e  s   /   S  e  c  o  n   d

   2

LSHLDR - Male LSHLDR - Female

 Figure 23: Maximum angular accelerations of the left shoulder as a function of work surface height

and gender.

 3.3. Body Discomfort:

Figure 24 shows the discomfort in the upper and lower back for the different work station

height and type of input device. Standing at the low work surface device while entering data with

the vertical touch screen had the most discomfort, especially in the upper and lower back.

Several other conditions were found to have the lowest low back and upper back discomfort

including most of the sitting conditions and the standing at the high work surface height (with the

exception of the vertical touch screen). Similar discomfort responses were seen for the hand,

elbow, neck, and shoulder (Figure 25). For most of these body regions, the standing at low work

height and using the vertical touch screen produced the greatest discomfort. The angled touch

screen produced the lowest discomfort, slightly below the horizontal touch screen and keyboard

conditions when sitting or standing at the high work surface height. The horizontal touch screen

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0

1

2

3

4

5

CKL CAL CHL CVL SKL SAL SHL SVL SKH SAH SHH SVH

   B  o   d  y   d   i  s  c  o  m   f  o  r   t   (  s

  c  a   l  e   0   t  o   1   0   )

UBACK LBACK

 Figure 24: Body discomfort rating for upper and lower back as a function of work surface height and type

of input device (0= No discomfort 10= Severe discomfort) with conditions: CKL= Chair

(Sitting), Keyboard—Low Surface; CAL= Chair (Sitting) , Angled Screen—Low surface; CHL=

Chair (Sitting), Horizontal Screen—Low surface; CVL= Chair (Sitting), Vertical Screen—Low

Surface; SKL= Standing, Keyboard—Low Surface; SAL= Standing , Angled Screen—Low

surface; SHL= Standing, Horizontal Screen—Low surface; SKH= Standing, Keyboard—High

Surface; SAH= Standing , Angled Screen—High surface; SHH= Standing, Horizontal Screen—

High surface; SVH= Standing, Vertical Screen—High Surface.

0

1

2

3

4

5

CKL CAL CHL CVL SKL SAL SHL SVL SKH SAH SHH SVH

   B  o   d  y   d   i  s  c  o  m   f  o  r   t   (  s  c  a   l  e

   0   t  o   1   0   )

HAND ELBOW NECK SHLDR

 Figure 25: Body discomfort rating for hand, elbow, neck, and shoulder as a function of work surface height

and type of input device (0= No discomfort 10= Severe discomfort) with conditions: CKL=

Chair (Sitting), Keyboard—Low Surface; CAL= Chair (Sitting) , Angled Screen—Low surface;

CHL= Chair (Sitting), Horizontal Screen—Low surface; CVL= Chair (Sitting), Vertical

Screen—Low Surface; SKL= Standing, Keyboard—Low Surface; SAL= Standing , Angled

Screen—Low surface; SHL= Standing, Horizontal Screen—Low surface; SKH= Standing,

Keyboard—High Surface; SAH= Standing , Angled Screen—High surface; SHH= Standing,

Horizontal Screen—High surface; SVH= Standing, Vertical Screen—High Surface.

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also increased the discomfort when in a sitting posture or standing at the low work surface

height.

The discomfort in the legs, knee, and hips also showed a similar trend with the vertical

touch screen when standing at the low surface height having the greatest discomfort in these

regions (Figure 26). The standing at the low work surface height had slightly more discomfort

than the sitting conditions with the two standing heights being approximately the same in

discomfort (with the expectation of the vertical touch screen while standing at low work surface

height). In all, the vertical touch screen position produced the most discomfort in all body

regions while many of the sitting conditions had the least discomfort.

 3.4. Error Rate:

The error rate revealed an interesting trend across the surface heights and input device

conditions (Figure 27). For all work surface heights, the vertical touch screen had the highest

error rates (about 15% more than other input devices). The standing at the low surface height had

the highest error rates among all input devices, showing above 15% error rates. The non-vertical

touch screen input devices under the sitting and standing at the high work surface had error rates

around 10%. As expected, the complexity of the data entry influenced the error rates (Figure

28). The easiest orders had an error rate around 8% while the complex orders had an error rate of

about 20%. No other effects influenced the error rate.

 3.5. Usability Index:

The usability index as rated by the participants was greatest for the angled and horizontal

touch screens while standing at the high work surface and lowest for the vertical touch screen

while standing at the low work surface height (Figure 29). While there were other trends among

the usability for the other conditions, none were statistically significantly different from each

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other. It is worth noting that the vertical touch screen was generally the worse rated usability in

all the surface height conditions.

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0

1

2

3

4

5

CKL CAL CHL CVL SKL SAL SHL SVL SAH SHH SKH SVH

   B  o   d  y   d   i  s  c  o  m   f  o  r   t   (  s  c  a   l  e   0   t  o   1   0   )

LEG KNEE HIP

 

Figure 26: Body discomfort rating for leg, knee, and hip as a function of work surface height and type ofinput device (0= No discomfort 10= Severe discomfort) with conditions: CKL= Chair (Sitting),

Keyboard—Low Surface; CAL= Chair (Sitting) , Angled Screen—Low surface; CHL= Chair

(Sitting), Horizontal Screen—Low surface; CVL= Chair (Sitting), Vertical Screen—Low

Surface; SKL= Standing, Keyboard—Low Surface; SAL= Standing , Angled Screen—Low

surface; SHL= Standing, Horizontal Screen—Low surface; SKH= Standing, Keyboard—High

Surface; SAH= Standing , Angled Screen—High surface; SHH= Standing, Horizontal Screen—

High surface; SVH= Standing, Vertical Screen—High Surface.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

CKL CAL CHL CVL SKL SAL SHL SVL SKH SAH SHH SVH   E  r  r  o  r   R  a   t  e  s   f  o  r   C  o  m  p   l  e   t   i  n  g

   T  r   i  a   l   (   %   )

 Figure 27: Error rate as a function of work surface height and type of input device. CKL= Chair (Sitting),

Keyboard—Low Surface; CAL= Chair (Sitting) , Angled Screen—Low surface; CHL= Chair

(Sitting), Horizontal Screen—Low surface; CVL= Chair (Sitting), Vertical Screen—Low

Surface; SKL= Standing, Keyboard—Low Surface; SAL= Standing , Angled Screen—Low

surface; SHL= Standing, Horizontal Screen—Low surface; SKH= Standing, Keyboard—High

Surface; SAH= Standing , Angled Screen—High surface; SHH= Standing, Horizontal Screen—

High surface; SVH= Standing, Vertical Screen—High Surface.

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0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

EASY MEDIUM COMPLEXType of Order

 Figure 28: Error rate as a function of work surface height and type of order (difficulty based on the number

of items included). Alpha characters that are similar are not significantly different. 

3

4

5

6

7

CKL CAL CHL CVL SKL SAL SHL SVL SKH SAH SHH SVH

   U  s  a   b   i   l   i   t  y   I  n   d  e  x

   (  a  v  e  r  a  g  e  o   f   1   8   i   t  e  m  s  w   i   t   h  s  c  o  r  e  s   1   t  o   7   )

 Figure 29: Usability Index as a function of work surface height and type of input device (values between 1

and 7). CKL= Chair (Sitting), Keyboard—Low Surface; CAL= Chair (Sitting) , Angled Screen—Low surface; CHL= Chair (Sitting), Horizontal Screen—Low surface; CVL= Chair (Sitting),

Vertical Screen—Low Surface; SKL= Standing, Keyboard—Low Surface; SAL= Standing ,

Angled Screen—Low surface; SHL= Standing, Horizontal Screen—Low surface; SKH=

Standing, Keyboard—High Surface; SAH= Standing , Angled Screen—High surface; SHH=

Standing, Horizontal Screen—High surface; SVH= Standing, Vertical Screen—High Surface.

A

AB

B

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 3.6. Rating of Preference:

The angled touch screen while sitting at low surface height and standing at high work

surface was ranked as the “most favorite” while the vertical touch screen while standing at

the low surface height was “least favorite” and was ranked worst for almost all participants

(See Figure 30). The keyboard input devices for the sitting and standing at the high surface

height was also found to be “favorable” by the participants. Several of the conditions were in

the middle rankings of favorability including the angled and horizontal at low surface height

and vertical while sitting and standing at high surface height.

Rank

0

2

4

6

8

10

12

CAL SAH SKH CKL SHH CHL SAL CVL SVH SHL SKL SVL

 Figure 30: Rank of Preference based on subject’s perception as a function of work surface height and type

of input device (1=Favorite to 12-Least favorite). CKL= Chair (Sitting), Keyboard—Low

Surface; CAL= Chair (Sitting) , Angled Screen—Low surface; CHL= Chair (Sitting), Horizontal

Screen—Low surface; CVL= Chair (Sitting), Vertical Screen—Low Surface; SKL= Standing,

Keyboard—Low Surface; SAL= Standing , Angled Screen—Low surface; SHL= Standing,

Horizontal Screen—Low surface; SKH= Standing, Keyboard—High Surface; SAH= Standing ,

Angled Screen—High surface; SHH= Standing, Horizontal Screen—High surface; SVH=

Standing, Vertical Screen—High Surface.

AB

BBB

BCBC

BCCD

CD

DD

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4.0 DISCUSSION 

The results of the study provided interesting insight into the multiple factors that impact

the postural response, pain responses and effectiveness of data entry in environments such as call

centers, restaurants, and other order taking operations. The type of input device had impact on

several key kinematic variables. First, the joint angles were impacted by the input device utilized

to enter the order. The vertical touchscreen placed several joints, such as the neck, right and left

elbows, and right shoulder, in less advantageous positions as compared to the angled and

horizontal touch screens. In some cases, these poor postures were similar to or worse than the

keyboard data entry method (e.g. right shoulder). The right wrist, which was the dominant hand

in 85% of the participants and was typically utilized to operate the input devices, was flexed the

least when utilizing the horizontal touch screen and the keyboard during the standing high work

surface conditions. Based on the results and visual observation through video, the left hand

typically remained bent at or around a 90°  angle and rested on the desk while the right arm

performed the data entry in an extended position. The extended elbow position produced higher

angles in the shoulders although this remained relatively stationary.

Extended static postures in awkward postures for extended periods of time produce

increased stress on the joints, potentially causing fatigue and ultimately increasing the risk of

injury for that particular joint (Granta, 1996). The upper extremity joints such as the shoulder,

elbows, and wrists are particularly susceptible to postural loading during data entry. In order to

put the posture results into context, the values were compared to the published work by

McAtamney: Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment

(RULA). These tools suggest that a range of 60°-100°  elbow flexion is considered to be the

“safe” range. Based on these recommendations, none of the input devices were ideal for either

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the right or left elbows. Based on the recommendations from REBA and RULA, the shoulder

posture for the vertical touch screen would be considered risky (angle > 45o) while the other

three input devices would have elevated risk (angle between 20o  and 45

o). The neck flexion

would be considered to be poor for all input devices based on the REBA and RULA

recommendations of 20°  flexion, although the vertical touch screen and keyboard devices were

far worse than the others. In general, the right wrist postures would be considered in the

relatively “safe” range based on the 15o REBA and RULA recommendations.

Second, the input devices also impacted the joint motions (e.g. angular velocities).

Basically, faster movements (increased angular velocities and accelerations) during work tasks

place the employee at a higher risk of discomfort and musculoskeletal disorders (Brophy, 1996).

For many of the joints, the vertical touch screen and the keyboard produced the greatest

velocities, thus increasing the stress on the joint. In Figure 14, these two input devices were

found to increase the velocities in 5 different joints. To a lesser extent, the accelerations of these

 joints followed a similar pattern with the keyboard having the highest accelerations followed by

the vertical touch screen.

With data entry, the upper extremities and neck joints would be the most important to

consider with respect to injury. Based on the results in Figures 7, 14, 19, and 20, it is apparent

that the vertical touch screen and keyboard input devices are less than optimal with regard to

kinematics and were inadequate compared to the angled and horizontal touch screen input

devices. In general, there was virtually no difference between the horizontal and angled touch

screens for the joint angles, angular velocities, and angular accelerations.

Another factor that influenced the joint kinematics was the surface height or more

specifically the combination of sitting or standing and the height of the work surface. One of the

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most obvious results of the study was how surface work height impacted the posture for the hips

and knees. As one would expect, the knees and hips were straighter during the standing

conditions. While this is totally expected, the results do provide an indication that changing the

work height to a sitting and standing height can change the muscles groups during these tasks.

Since data entry in call centers often requires long hours with infrequent breaks, changes in the

work surface height can produce changes in the work postures, thus altering the lower extremity

posture load and exposure to static loads. Based on the results in Figure 4, the standing at the low

work surface height produced slightly more squatted leg postures than the standing at the high

work surface height. If the postures under the low surface height conditions remained static, the

more squatted positions may become an issue, thus, the standing at a higher work surface height

would be better. The angular velocities and accelerations for the hips and knees (particularly the

right leg joints) were also found to be higher for the standing conditions than the sitting

conditions. Again, this potentially indicates very distinct muscle recruitment patterns in the leg

and hip muscles between these lower extremity postures (e.g. sitting vs. standing).

The height of the surface was also found to impact the neck posture where the greatest

neck flexion was found for the low surface, either standing or sitting. Less neck flexion was

found for the standing while working at the high work surface. However, the worst neck flexion

occurred when the keyboard was utilized under the sitting or standing at the low work surface

height or when the vertical touch screen while standing at low work surface height. Thus, the low

work surface had the most impact when utilizing the vertical touch screen or keyboard input

devices. Also, as expected, the standing at the low height work surface resulted in the most

extended elbow (right and left) angles along with increased shoulder flexion. As seen in Figure

5, the sitting at low work surface height produced the most neutral elbow angles but elevated

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shoulder flexion as compared to the standing at high work surface height. The right elbow

angular velocity was also greater in the sitting a standing at low work surface height in

comparison to the standing at the high work surface height. The overall trends support the

working postures of either sitting at the low work surface height or standing at the high work

surface height.

While there were several significant interactions between gender and either work surface

height or type of input device, the impact of gender was nominal. Oftentimes, the difference in

kinematic responses between males and females were minimal and probably relate more to

differences in anthropometry rather than factors inherent to a specific gender. A very telling

figure about a potential anthropometric effect is in Figure 11 where no differences were seen

between males and females for the standing at the high surface height while differences existed

during the standing at low work surface and sitting at low surface. The former condition was

adjusted to the height of the participant while the latter conditions were fixed height and

independent of participant. Overall, gender had few interactions that were significant and the

ones that were significant had a relatively limited impact. Thus, the results are robust and not

gender dependent.

The body discomfort responses support the postural load responses. For many of the body

regions, the body discomfort was highest for the vertical touch screen conditions and the

standing at the low surface height. The worst condition was the vertical touch screen when

standing at the low work surface for all body regions, indicating increased whole body

discomfort. For the back, shoulder, and neck regions, the angled touch screen resulted in a lower

discomfort at the various work surface heights than the other input devices. The only work

surface height condition that was favorable for vertical touch screen was the sitting at the low

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work surface. In all, the body discomfort results indicate more favorable conditions when sitting

at the low surface and standing at the high work surface and utilizing the angle touch screen.

The error rates indicate the horizontal touch screen was the best for the sitting at the low

surface height and standing at the high surface height. In all three surface height conditions, the

vertical touch screen produced the highest error rates. This may have been due to the fact that the

subjects’ line of vision was some what obstructed, especially in the standing at the low height

work surface (which had the highest error rate). The keyboard and angled touch screen had

slightly more errors than the horizontal touch screen.

Finally, the usability of the devices as rated by the participants indicated that the vertical

touch screen was the lowest while angled and horizontal touch screen input devices were the

highest. The ratings were only slightly impacted by the height of the work surface and whether

the condition was sitting or standing. The device type appeared to be the more dominant factor

for usability. The other perceptual rating of the conditions was the rankings of the 12 different

conditions where the participants ranked the angled touch screen input devices as the preferred

devices, especially for the sitting low work surface and the standing high work surface. The

worse condition was the vertical touch screen when standing at the low work surface.

With so many results, it is necessary to determine the trade-offs between the different

input devices and surface height conditions. To help understand the key findings two tables were

developed that compare each of the 12 conditions (combination of input device and work surface

height) to a standard condition which was the keyboard while sitting at the low work surface

(CKL) as the “reference condition”. This condition was chosen since it is the position most

commonly used in call centers and other data entry environments. All of the kinematic variables

(each joint angle, velocity, and acceleration) data is in Table 9 while the usability, body

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Table 9 : Summary of Kinematics

Angles

CKL CAL CHL CVL SKH SAH SHH SVH SKL SAL SHL SVL

RKNEE --- ↑↑↑↑  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ LKNEE --- --- ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RHIP --- ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↓  ↓  ↑↑↑↑ 

LHIP --- ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RSHLDR --- --- --- ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

LSHLDR --- ↑↑↑↑  --- ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RELBOW --- --- ↑↑↑↑  ↑↑↑↑  --- ↓  ↓  ↓  --- ↓  ↓  ↑↑↑↑ 

LELBOW --- --- --- ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RWRIST --- --- --- --- --- --- --- ↓  --- ↓  --- ↓ 

LWRIST --- --- --- --- --- --- --- --- --- --- --- ---

NECK --- ↓  ↓  ↓  ↓  ↓  ↓  ↓  --- ↓  ↓  ↓ 

Accelerations

CKL CAL CHL CVL SKH SAH SHH SVH SKL SAL SHL SVL

RKNEE --- ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

LKNEE --- ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RHIP --- ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↓  ↑↑↑↑  ↑↑↑↑  ↓  ↑↑↑↑ 

LHIP --- ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↑↑↑↑ 

RSHLDR --- ↑↑↑↑  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

LSHLDR --- ↑↑↑↑  --- ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RELBOW --- ↓  ↓  ↓  ↑↑↑↑  ↓  ↓  ↓  ↓  ↓  ↓  ↑↑↑↑ 

LELBOW --- ↓  ↓  ↓  ↑↑↑↑  ↓  ↓  ↓  ↓  ↓  ↓  ↑↑↑↑ 

RWRIST --- ↓  ↓  ↓  ↑↑↑↑  ↓  ↓  ↓  ↓  ↓  ↓  ↓ 

LWRIST --- ↓  ↓  ↓  ↑↑↑↑  ↓  ↑↑↑↑  ↓  ↓  ↓  ↓  ↑↑↑↑ 

NECK --- ↓  ↓  ↓  ↑↑↑↑  ↓  ↓  ↓  ↑↑↑↑  ↓  ↓  ↓ 

Velocities

CKL CAL CHL CVL SKH SAH SHH SVH SKL SAL SHL SVL

RKNEE --- ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

LKNEE --- ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  --- ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RHIP --- ↑↑↑↑  ↓  ↑↑↑↑  ↑↑↑↑  ↓  --- --- ↑↑↑↑  --- ↓  ↑↑↑↑ 

LHIP --- --- ↓  --- --- ↓  ↓  ↓  ↑↑↑↑  --- ↓  ↑↑↑↑ 

RSHLDR --- ↑↑↑↑  --- ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

LSHLDR --- ↑↑↑↑  ↓  --- ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ RELBOW --- --- --- ↑↑↑↑  ↑↑↑↑  ↓  ↓  ↑↑↑↑  ↓  --- ↓  ↑↑↑↑ 

LELBOW --- ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↓  ↑↑↑↑ 

RWRIST --- ↓  ↓  ↓  ↓  ↓  ↓  ↑↑↑↑  ↓  ↓  ↓  ↓ 

LWRIST --- ↓  ↓  ↓  --- ↓  ↓  ↑↑↑↑  ↓  ↓  ↓  ↑↑↑↑ 

NECK --- ↓  ↓  ↓  ↓  ↓  ↓  --- ↑↑↑↑  ↓  ↓  ↓ 

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Table 10: Summary of Results

CKL CAL CHL CVL SKH SAH SHH SVH SKL SAL SHL SVL

USABILITY --- ↑↑↑↑ 

↑↑↑↑ 

↑↑↑↑ 

↑↑↑↑ 

↑↑↑↑ 

↑↑↑↑ 

↓ 

↓ 

↓ 

↑↑↑↑ 

↓ 

DISCOMFORT --- ↓  ↑↑↑↑  ↓  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

ERROR RATE  --- ↓  ↓  ↑↑↑↑  ↓  ↑↑↑↑  ↓  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑  ↑↑↑↑ 

RANKING --- ↑↑↑↑  ↓  ↓  ↑↑↑↑  ↑↑↑↑  ↓  ↓  ↓  ↓  ↓  ↓ 

region discomfort, error rate, and ranking data is in Table 10. The bold “up” arrows indicate that

a considerable increase was found, while the “down” arrows indicate that a decrease was found.

A line in the box indicates “no significant difference”, representing values having the same

relative magnitude.

The sitting conditions show lower results in nearly all comparisons, especially among

accelerations and velocities. The CAL condition (sitting with an angled screen and a low surface)

shows exceptionally good results, with majority of body joints with lower velocities and

accelerations, a higher preference ranking, lower error rate and discomfort, and a higher usability

score than the CKL (standard condition). Thus, the sitting with angled touch screen would be

considered one of the best options overall. The standing at high work surface condition had one

input device—angled touch screen (SAH) with similar results to the CAL with better kinematic

variables, higher usability, lower discomfort, lower error rates and higher preference than CKL,

although the horizontal and keyboard conditions also had similar results during high height

condition. Based on all the results, the worse condition (by far) was the vertical touch screen

while standing at the low height work surface. The results as a whole indicated that angled touch

screen was the best option among the input devices tested for order entry tasks. These results are

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also supported by the research by Schultz (1998) who reported that the optimal viewing angle of

a monitor is in an angled position.

 4.1 Limitations:

There were a few limitations to the study that should be mentioned. First, the subjects

who participated in this study were not experience in data entry, especially with order entry in a

restaurant or call center. While some subjects did mention that they had previous experience

doing similar tasks, none of them had extensive experience (e.g. greater than 1 year). Although

the impact of experience could not be evaluated in the current study, it is important to understand

that the postures that adopted by the current subjects may not reflect individuals with more

experience, particularly when utilizing the keyboard input device. The subjects in the current

study were recruited from the university area that typically had knowledge of computers and

keyboards but very limited interaction and knowledge of touch screens.

The study represented a short term evaluation of the data entry conditions with only 6

total order entries for each of the conditions (combination of type of input device and work

surface height). Longer exposures that produce fatigue may alter the postures, discomfort and

preferences for the individual conditions. Thus, future work needs to investigate all day

interactions with each of the input devices and surface heights to truly understand the long-term

ramifications of these conditions.

There were also several intrinsic factors relating to the subjects that were not necessarily

controlled by the current study. For example, factors such as height, body part dimensions, and

body weight may have influenced the individual postures adopted by the participants. This was

particularly the case for the low working surface height which was standardized (consistent for

all subjects). Other subject-dependent variables that were not controlled for include the quality of

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vision, physical and mental capability, familiarity with a computer or touch screen, and previous

experience using devices. While all these factors could contribute to the results, the within

subjects design allows comparisons between the work height and input device type was more

robust and would minimize the effects of these factors.

The results could also be a function of the input device selected, in that, a specific model

of touch screen, the layout of items on screen, the model of keyboard, and the layout of keys on

keyboard could influence the postures and kinematics adopted during data entry and the

discomfort felt. The study was designed to simulate real world order entry conditions typically

found in food order processing call centers utilizing existing programs and devices specifically

designed for this activity. The keyboard was a standard keyboard that had hot keys that

corresponded to the same entry buttons that were displayed on the touch screen. Thus, all steps

were taken to ensure that the task was realistic and the same in all conditions.

Post-hoc analyses of the distance between the participant and the input device revealed a

constant distance. The distance was captured by a reflective marker on the left hip and a marker

placed on the keyboard or touch screen monitor. In addition, the chair and table height were

allowed to be adjusted between the different conditions but based on observation and digitizing

of markers, the chair height in the seated conditions and the high surface height in the standing

condition remained consistent for a given participant. Thus, the comparisons represent responses

to the different conditions and corresponding demands rather than a systematic change in the

conditions.

 4.2. Future Work:

As more and more call centers around the world begin to update their systems and

consider installing touch screens, the next step in this research would be to follow up on the

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impact of these data entry devices on the daily activities and response in actual real world

situations. The use of the different input devices and working at different work heights should be

investigated for a full work cycle rather than the short duration exposures in the similar study.

The long-term effects of these conditions may shed more light into the effectiveness of the

devices and alternative work surface heights in reducing musculoskeletal disorder exposures and

injuries. The assessment could also better delineate the impact of experience by looking at new

hirers as compared to seasoned workers who have extensively utilized the keyboard entry device.

Future work should also include more extensive analyses that would include fatigue and

 joint loading. The current study evaluated outcomes that would be considered surrogates to the

actual joint loading (e.g. loading on joints related to posture and angular velocity).

Biomechanical modeling and electromyography would allow for the quantification of the loads

as well as the muscle response to the demands in the different conditions. Electromyography

would also allow for the documentation of fatigue in the different muscle groups, especially

when performing data entry under the different conditions for extended periods of time (e.g. 8

hour shift).

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5.0 CONCLUSION

The results of the comprehensive study of the postural load, body discomfort, usability,

and error rates provided multiple insights into the utility of different input devices and work

conditions during data entry of restaurant orders. While there was not any input device that

completely reduced the risk to the multiple body joints to minimal levels, several of touch screen

devices were better than the traditional keyboard while sitting at the low desk height. When

working in the sitting—low work surface height condition, the angled touch screen reduced

many of the joint angles (e.g. placed the joint in more neutral posture with greater biomechanical

advantage) and joint velocities and accelerations, reduced the error rates, reduced the discomfort

slightly, and increased the preference and usability ratings. For the standing at the high work

surface condition, there were three input devices that produced relatively the same results in

kinematics, discomfort, error, and ratings. These were the angled touch screen, horizontal touch

screen, and keyboard. Based on the results as a whole, the angled touch screen was the best input

device. Touch screens also have the advantage of taking up less space on the work surface, an

easier interface that provides information at the workers finger tips, and more options through

menus rather than reliance on hot keys. In general, the standing at the lower work surface was

not considered to be effective in reducing the joint postural stress and corresponding discomfort.

The lower work surface height produced extended reaches and squatted lower extremity

postures. In all, the worse condition was the vertical touch screen when standing at the lower

work surface height.

The documentation of kinematic responses between the sitting and standing at high work

surface indicated that there may be the potential to alternate the loading on the lower extremity

and other body joints if the work surface was adjusted throughout the day between these two

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conditions. If such a change on work surface height occurred, the angled touch screen would be

the preferred input device since it was considered the best device in both conditions. An

adjustable touch screen monitor may also be beneficial under these circumstances.

The results of the current study may have some broader ramifications to the data entry

industry, especially for companies that enter food orders. As these facilities update into new

technologies, faster and more intuitive input devices will hit the market such as touch screens

that will increase the efficiency and accuracy of order recording. Touch screen technology has

expanded to be more versatile and comprehensive in providing information to the end user— the

data entry operator. The change to these types of input devices could have resulted in ergonomic

consequences. However, the current study verified that the opposite was the case with angled

touch screens reducing many of the postural loads as well as the discomfort of multiple body

 joints. Study results also indicate that there may be some biomechanical benefit to having

adjustable work surfaces in work environments that have continuous static sitting posture for

long durations. There were very distinct differences between the sitting at low height work

surface and standing at the high work surface, indicating adjusting the height throughout the day

would change the postures of the workers, potentially increasing the muscle oxygenation and

reducing the effects of static postures.

The take home message of the study is that the angled touch screen input device provided

the best option for food order entry, based on the multitude of outcome variables evaluated.

Future research is still need to further delineate the effectiveness of touch screen input devices in

real world situations, understand the role of experience, and identify the completed

biomechanical stress on the joints when interacting with these types of devices.

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REFERENCES

1.  Jensen, C., Finsen, L., Sogaard, K., Christensen, H., (1992), Musculoskeletal symptoms

and duration of computer and mouse use. International Journal of Industrial Ergonomics,

30(4-5), 265-275.2.  National Institute for Occupational Safety and Health. Musculoskeletal disorders and

workplace factors: A critical review of epidemiological evidence for work-related

musculoskeletal disorders of the neck, upper extremity, and low back, Cincinnati, OH:

NIOSH Technical Report No. 97-141, US Department of Health and Human Services,National Institute for Occupational Safety and Health, 1997 

3.  McLean, L., Tingley, M., Scott, R.N., Rickards, J., (2001), Computer terminal work andthe benefit of microbreaks. Applied Ergonomics, 32, 225-237. 

4.  Schultz, K.L., Batten, D.M., Sluchak, T.J., (1998), Optimal viewing angle for touch-screen displays: Is there such a thing? International Journal of Industrial Ergonomics, 22,

343-350. 5.  Liao, M.H., Drury, C.G., (2000), Posture, discomfort and performance in a VDT task.

Ergonomics, 43 (3), 345-359. 

6.  Balci, R., Aghazadeh, F., (2004), Effects of exercise breaks on performance, muscular

load, and perceived discomfort in data entry and cognitive tasks. Computers & Industrial

Engineering, 46, 399-411. 

7.  Scheirman, L., (2003), Peak Motus Motion Measurement System: 510(k) Summary. Peak

Performance Technologies, Inc., 3:1-3 

8.  Henning, R.A., Jacques, P., Kissel, G.V., Sullivan, A.B., Alteras-Webb, S.M., (1997).Frequent short rest breaks from computer work: effects on productivity and well-being at

two field sites. Ergonomics 40 (1), 78-91. 9.  Shneiderman, B., (1991). Touch screens now offer compelling uses. IEEE Software, 8 (2)

93-94,107 

10. Fischetti, M., (2001). At your fingertips. Scientific American, 284 (4), 102 

11. Colle, H.A., Hiszem, K.J., (2004), Standing at a kiosk: Effects of key size and spacingon touch screen numeric keypad performance and user preference. Ergonomics, 47 (13),

1406-1423.

12.  McDaniel Executive Recruiters’ 2004 North American Call Center Report, 9-23-2004 13. Alibaba Website; Call Centers: Catalysts for Corporate Change; May 21, 2007

http://resources.alibaba.com/topic/46104/Call_Centers_Catalysts_for_Corporate_Change

_.htm14. Jackson, K.E., (2006). Overturn the high cost of employee turnover.

http://multichannelmerchant.com

15. Healy, A.F., Kole, J.A., Buck-Gengler, C.J., Bourne Jr., L.E., (2004), Effects of

prolonged work on data entry speed and accuracy. Journal of Experimental Psychology:Applied, Vol.10 (3), 188-199.

16. Cail F, (2003), Biomechanical stresses in computer-aided design and in data entry.

International Journal Of Occupational Safety And Ergonomics, Vol. 9 (3), pp. 235-55

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http://slidepdf.com/reader/full/hammer-matthew-justin 74/77

 

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17. Brophy, M, Grant, C, (1996), Office ergonomics, pp. 387-401. Occupational Ergonomics:

Theory and Applications, Bhattacharya, A., McGlothlin, J.D.18. Hammett, Wilma. "Ergonomics in the Office: A Guide for Improved Efficiency and

Well-Being of Workers." The Forum for Family and Consumer Issues 3.2 (1998): 22

pars. 9 July 1998 <http://www.ces.ncsu.edu/depts/fcs/pub/1998/ergonom.html>.

19. Konrad, K., Population Segment Accommodation for Keyboard Entry at VariousWorkstations, The Knoll Group, 1992.

20. Henning, R.A., Sauter, S.L., Salvendy, G., King, E.F., (1989). Microbreak length,performance and stress in a data entry tasks. Ergonomics 328:855-864.

21. Li, Z., Bowerman, S., Heber. D., (2005). Health ramifications of the obesity epidemic.

The Surgical Clinics of North America 85 (4): 681-701.22. Schulte, PA, Wagner, GR, Ostry, A., Blanciforti, LA, Cutlip, RG, Krajnak, KM, Luster,

M., Munson, AE, O’Callaghan, JP, Parks, CG, Simeonova, PP, Miller, DB (2007). Work,

obesity, and occupational safety and health. American Journal of Public Health. 97 (3):

428-36.23.  Granata, K.P., Marras, W.S., (1996), Biomechanical Models in Ergonomics, pp. 115-

136. Occupational Ergonomics: Theory and Applications, Bhattacharya, A., McGlothlin,J.D.24. Hignett, S., McAtamney, L., (2000), Rapid Entire Body Assessment (REBA). Applied

Ergonomics, 31, 201-205

25. McAtamney, L., Corlett, E.N., (1993). RULA: a survey method for the investigation ofwork-related upper limb disorders. Applied Ergonomics, 24(2), p. 91-99

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APPENDICES

Appendix 1.0 Current Symptom Survey (Body Discomfort)

Appendix 2.0 User Satisfaction Survey (IBM Usability Survey)

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Appendix 1.0: Current Symptom Survey (Body Discomfort)

CURRENT SYPTOM SURVEY

Subject ID_______________________________________ Date_____________________

This survey will assess your current pain in various body regions. Please circle the number under the scale

describing your current level of pain.

Example: Body RegionNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

1. NeckNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

2. ShoulderNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

3. ElbowNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

4. Hand and WristNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

5. Upper BackNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

6. Low BackNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

7. HipNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

8. KneeNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

9. Lower Leg and FootNone Mild Moderate Severe

0 1 2 3 4 5 6 7 8 9 10

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Appendix 2.0: User Satisfaction SurveyUser Satisfaction Survey (IBM Usability Survey)

Please mark your responses to the following statements about the technical aspects of using the

current data entry device in this form.

 strongly disagree strongly agree

1. Overall, I am satisfied with how easy it is to use

this entry device.

N/A 1 2 3 4 5 6 7

2. It was simple to use this data entry device. N/A 1 2 3 4 5 6 7

3. I can effectively complete my work using this data

entry device.

N/A 1 2 3 4 5 6 7

4. I am able to complete my work quickly using this

entry device.

N/A 1 2 3 4 5 6 7

5. I am able to efficiently complete my work usingthis entry device. N/A 1 2 3 4 5 6 7

6. I feel comfortable using this data entry device. N/A 1 2 3 4 5 6 7

7. It was easy to learn to use this data entry device. N/A 1 2 3 4 5 6 7

8. I believe I became productive quickly using this

data entry device.

N/A 1 2 3 4 5 6 7

9. (INTENTIONALLY BLANK) N/A 1 2 3 4 5 6 7

10. Whenever I make a mistake using this data entry

device, I recover easily and quickly.

N/A 1 2 3 4 5 6 7

11. The information (such as online help, on-screenmessages, and other documentation) provided

with this data entry device is clear.

N/A 1 2 3 4 5 6 7

12. It is easy to find the information I needed. N/A 1 2 3 4 5 6 7

13. The information provided for the entry device is

easy to understand.

N/A 1 2 3 4 5 6 7

14. The information is effective in helping me

complete the tasks and scenarios.

N/A 1 2 3 4 5 6 7

15. The organization of the information on the dataentry device screen is clear.

N/A 1 2 3 4 5 6 7

16. The interface of this data entry device is pleasant. N/A 1 2 3 4 5 6 7

17 I like using the interface of this entry device N/A 1 2 3 4 5 6 7