Inertial sensor orientation for cricket bowling monitoring.

Andrew Wixted, Daniel James Centre for Wireless Monitoring and Applications

Griffith University Nathan, Australia

a.wixted@griffith.edu.au

Marc Portus Praxis Sport Science Pty Ltd

Sport Science Sport Science Unit, Cricket Australia Brisbane, Australia

marc.portus@praxis-sport.com

Abstract— Inertial sensors are a potential method of measuring the elbow angle during cricket bowling, currently an indicator of illegal bowling. To detect the elbow angle it was necessary to orient sensors relative to the elbow axis. An elbow orientation exercise was developed and the sensor orientation relative to the elbow axis calculated for upper-arm, forearm and wrist mounted sensors for different muscle loading and wrist rotation. Inertial rate-gyroscope outputs were compared for sensors before and after adjustment for elbow-axis orientation. This output was compared to the results obtained from a Vicon motion capture analysis system.

Adjusting the sensor orientation based on the output from the orientation exercise improved the correlation between outputs of the upper-arm and forearm sensors but also indicated that the sensors were susceptible to muscle loading and wrist rotation effects that will need to be accounted for in any sensor based illegal bowling detection system.

I. INTRODUCTION Cricket bowlers suspected of bowling with an illegal

action are assessed in technology intensive motion capture laboratories. This is an expensive process and generally limited to players at the elite level. Low cost inertial sensors have the potential to detect illegal bowling in situ, which would make bowling assessment available to developing players and provide opportunity for remediation. Illegal bowling involves the extension (“straightening”) of the elbow in excess of 15 degrees during the bowling action. There are potentially multiple ways to detect illegal bowling using inertial sensors but the required accuracy is likely to be influenced by numerous factors including an individual’s bowling action and arm morphology.

We have shown that for a legal delivery featuring the hand upward at the arm horizontal position and where the hand continues to face forward during the delivery arc, the output of inertial rate-gyroscopes mounted on the forearm and upper-arm tracked together [1]. The outputs of accelerometers also tracked proportionally. For an illegal delivery where the elbow starts flexed and straightens as the arm comes forward there is a distinct divergence in the gyroscope outputs as well as a phase shift in accelerometer outputs.

Other deliveries start with the arm back but with the wrist or arm rotated and the hand facing downward. Some deliveries have internal and external rotation of the arm as the shoulder rotates. Some bowlers, due to their anthropometry, cannot fully straighten their elbow and can use an upper-arm internal rotation to gain speed at the wrist [2]. Some bowlers deliver the ball with the back of their arm facing the batsman, using a wrist rotation or wrist extension to direct the ball forward. Illegal bowling actions tend to occur at different points in the delivery. As described above, fast bowlers may start the bowling action with the elbow flexed; any type of bowler may experience a flex-extend action as the arm approaches vertical, or, for slower bowlers bowling with the back of the arm facing the batsman (a “doosra”), elbow extension can be used through ball release [3]. Further complications arise because the elbow joint is not a simple hinge joint. Some bowlers have elbows that can bend sideways (abduction and adduction) or backwards (hyperextension).

There are numerous issues related to detecting illegal bowling with inertial sensors. These include identifying the critical time points of arm horizontal and ball release during bowling action [4], confirming that sensor outputs match the existing standard of motion capture, calibrating the sensors to the arm, identifying the most appropriate arm position for sensors and understanding how the sensor orientation is affected by the changes in muscle tension and wrist position.

This paper reports on a simple elbow axis alignment technique and the effect of wrist rotation and muscle tension on the sensor alignment. A sensor to elbow axis alignment factor was applied to upper-arm and forearm mounted gyroscopes and the output of these sensors compared for known good and illegal deliveries. Analysis of elbow angle is ongoing work and will not be addressed in this paper.

II. METHOD Sensors were developed using the highest specification

devices available at the time. The sensors included a ± 100g accelerometer (Analog Devices ADXL190) aligned to capture the arm’s centrifugal acceleration. Orthogonal to this was a dual axis ± 18g accelerometer (Analog Devices ADXL321). Also included were 3 axes of ± 2000 deg/s rate gyroscopes

This work is funded by the International Cricket Council (ICC) and the Marylebone Cricket Club (MCC) with funding administered by Cricket Australia.

978-1-4244-9289-3/11/$26.00 ©2011 IEEE

(Inversense IDG650). The 100g accelerometer was a relatively large device (12x10x3 mm) and the direction of sensing required the chip to be mounted orthogonal to the arm’s surface. This subsequently affected the packaging size (Fig.1). A Hall Effect device was used to capture external magnetic pulses which were used for synchronization of the sensors. Data were logged to an on-board 2G Byte flash memory for later downloading. A lithium polymer battery capable of sustaining continuous operation for 40 minutes was included.

Figure 1. Wrist sensor mounted on motion capture marker cluster. The cluster base was attached with double sided tape and then secured with tape. The sensor was similarly attached and secured. The sensor package size was

due to the verticaly mounted sensor board (hidden by tape).

The sensor tests were performed in conjunction with existing 3D motion capture bowler testing procedures where 11 bowlers performed a mixture of their bowling actions with a total of 24 deliveries each. Sensors were located on the back of the wrist and the back of the forearm and upper-arm, either side of the elbow (Fig.2a). The sensor on the wrist was attached to a motion-capture cluster of markers (Fig.1) allowing direct comparison between the outputs of the sensor and the motion capture system. Sensors either side of the elbow axis were attached with double sided tape but then held on firmly using medical tape around the arm segment. The sensors and the motion capture system were run at 200Hz sampling.

An elbow axis calibration procedure was performed where the upper arm was held still and the elbow repeatedly flexed and extended (Fig.2a). For two bowlers this was performed with the wrist in three different orientations, with the hand supinated (palm up), with the hand vertical and with the hand pronated (palm down) (Fig.2b). The set of three flex and extend exercises was repeated with the bowlers holding a 5kg weight. The resultant data were processed to extract the angles of the sensor relative to the elbow axis of rotation for each combination of weight and wrist rotation. The upper-arm sensor was also calibrated to the elbow axis with a single set of flex-extend repetitions. These were performed with the forearm held firmly in position and the upper-body rocking back and forth to create the flex-extend motion.

Assuming an arrangement sensor location relative to axis of rotation such shown in Fig.3, the arm flex-extend exercise, where one arm segment is fixed, created a fixed axis of rotation for the sensor on the moving segment. For a triaxial gyroscope this arrangement would result in signal only on the

Y channel, labeled ‘Pitch’ in this diagram. Misalignment of the sensor relative to the axis of rotation would result in signals on the other channels. For example, if the sensor had some roll applied, the orientation exercise would generate signal on both the pitch and yaw axes. By analyzing the signal on all three channels, the alignment of the sensor to the elbow axis could be extracted.

Figure 2. (a) Upper-arm and forearm sensor mounting with effect of flex and extend exercise illustrated. (b) Arm, looking from below, with hand

moving from supinated to pronated position. The solid line was drawn on with a ruler, the dashed line represents an estimate of the arm centre line. In

(a) the sensors were physically closer to the elbow point than illustrated.

Initially the above method was trialed on a wooden arm with sensors arranged at different orientations. The extracted angles were compared with angles obtained from analysis of the photographs of the sensors in-situ. Pitch angle cannot be resolved in the absence of other misalignments because the orientation calibration routine only generates signal on the pitch axis.

III. PROCESSING

A. Sensor Calibration Accelerometers were calibrated used the six point

stationary orientation method [5]. Gyroscopes were calibrated by rotating them a fixed number of times on a turntable and then scaling the result so the integrated angle matched the angle of rotation. This was performed for each axis.

Figure 3. Axes of gyroscope sensor relative to axis of rotation (elbow joint). For a pure hinge joint only the Y (pitch) axis should detect rotation.

B. Sensor Orientation Rapid flexing and extending of the elbow with the upper

arm held stationary generated signals on the wrist and forearm gyroscopes and accelerometers. For the purpose of this processing it was assumed that the elbow was a one degree of freedom hinge joint.

The processing for angle extraction involved two steps. The first step generated estimated angles of sensor pitch, roll and yaw from the magnitude of the signal on each channel. This estimate was then used with an iterative process to optimize the sensor orientation angles.

Initially an envelope detector using a Hilbert transform was used to estimate the signal magnitudes for the angle extraction. A simplified method of only calculating the angle when the signal exceeded some threshold appeared to give a better starting point. Angles were calculated using the arc-tan trig function where the signal on two channels was used to estimate the angle of the third. This process is outlined below:

• Find samples where the signal on any channel exceeds the threshold.

• Calculate the pitch, roll and yaw angle for each sample from above using the arc-tan trig function.

• Average the results for each angle.

The approximate angles from the above process were then used as the starting position of an iterative process to find the angles that produced maximum RMS signal on the pitch axis and the minimum RMS signal on the yaw and roll axes of the gyroscopes. This process was repeated for the six combinations of wrist position and weight for the forearm and wrist sensors. The process was also used to calculate the orientation angle of the upper-arm sensor.

IV. RESULTS Two aspects of the results were considered: (1) the effect

of adjusting sensor output by the orientation angles on the relationship of the forearm and upper-arm sensors, and (2), the effect of muscle tension and wrist rotation on the sensor orientation.

A. Comparison of gyroscope outputs Unadjusted gyroscope outputs from the forearm and

upper-arm sensors sometimes showed poor correspondence even for legal bowling actions (Fig.4a). After orientation calibration adjustment the signals became more correlated at the critical points of the bowling action. Fig.4 and Fig.5 show the pitch axis of the forearm and upper-arm gyroscopes for a legal and an illegal delivery as defined by the motion capture analysis. Although elbow angle was not entirely dependent on this axis, it was a good indicator of bowling techniques where the forearm and upper-arm were moving together.

B. Effect of muscle tension and wrist rotation on sensor orientation Orientation angle results for the forearm and wrist sensors

of two bowlers are reported in tables 1 to 4. An example of the gyroscope signal before and after orientation adjustment

appears in Fig.6. As was expected for the wrist sensor, the main orientation changes were recorded on the roll axis. As the wrist pronated the attached sensor went with it. The amount of roll at the wrist (Tables 2 & 4) indicated less flexibility than was anticipated, with one bowler only producing 91 to 93 degrees of forearm pronation at the wrist and the other 104-107 degrees.

Figure 4. Gyroscope sensor “pitch” axis signal for a typical legal bowling action before (a) and after (b) adjustment of orientation angle.

Figure 5. Gyroscope sensor “pitch” axis signal for an illegal bowling action before (a) and after (b) adjustment of orientation angle.

TABLE I. BOWLER 1 – FOREARM SENSOR

Position Supinated Vertical Pronated Load Yaw Pitch Roll Yaw Pitch Roll Yaw Pitch Roll

No_weight 0 0 0 3 -1 6 12 0 -22 Weight 1 -8 4 4 -4 -3 12 11 -21

For all tables, the supinated, no weight condition is the reference or zero value.

TABLE II. BOWLER 1 – WRIST SENSOR

Position Supinated Vertical Pronated Load Yaw Pitch Roll Yaw Pitch Roll Yaw Pitch Roll

No_weight 0 0 0 -6 -16 -49 -14 -33 -104 Weight 0 -6 0 -7 -14 -52 -10 -44 -107

TABLE III. BOWLER 2 – FOREARM SENSOR

Position Supinated Vertical Pronated Load Yaw Pitch Roll Yaw Pitch Roll Yaw Pitch Roll

No_weight 0 0 0 2 -8 -6 6 -15 -14 Weight 0 -8 2 1 -9 -6 6 3 -15

TABLE IV. BOWLER 2 – WRIST SENSOR

Position Supinated Vertical Pronated Load Yaw Pitch Roll Yaw Pitch Roll Yaw Pitch Roll

No_weight 0 0 0 -4 -19 -59 1 4 -93 Weight -1 -4 -2 -2 -16 -56 2 -1 -91

Figure 6. (a) The raw wrist sensor gyroscope signal and (b) the rotated signal for the flex-extend exercise for the unloaded supinated hand.

For the forearm sensor mounted at the elbow there was substantial movement of the sensor. Both muscle tension and wrist rotation affected the sensor orientation. Muscle tension predominately affected the pitch of the sensor and wrist rotation predominately affected the roll and yaw of the sensor. The amount of the roll, as a percentage of wrist rotation, increased with increasing wrist rotation.

For some bowlers during bowling, the recorded rotation rates exceeded the specification for the gyroscopes. This applied to any sensor location. Recorded acceleration for the wrist sensor for some bowlers exceeded the 18g specification of the transverse accelerometer axes.

V. DISCUSSION While adjusting for sensor orientation improved the

alignment of signals in Fig.4, it did not bring both sensors into complete alignment through the critical period. Inspection of the other channels of the gyroscope indicated wrist rotation occurred and from the results above relating to wrist rotation, the forearm sensor was most probably changing orientation through the bowling action. While some types of bowling deliveries could potentially be monitored now, simply turning the wrist changed the relationship of the sensors to each other and therefore affected the ability to interpret the output. Using rigid-body common-mode-rejection based models for angle extraction requires that the sensor is firmly attached to its segment and that there is only one degree of freedom. Sensors

mounted on the arm moved about on all three axes therefore a movement detection and compensation algorithm would need to be developed.

The flex-extend exercise took the elbow through approximately 135 degrees and would have generated some dynamic morphology related sensor orientation changes. A smaller range of movement generated insufficient signal to extract any angles reliably. The changes would have contributed to error in the extracted orientation angle and were probably a source of some of the noise in Fig.6b (rotated signal). The flex-extend process could also explain the limited range of measured roll at the wrist (Tables 2&4) as a fully flexed elbow limits forearm pronation and a fully extended elbow limits forearm supination [6]. The flex-extend exercise would result in these limits applying concurrently.

During these trials, the sensors were taped on the arm and it could be assumed that the taping made the sensor respond, at least in part, to movements of the arm cross section at that point. In the future it is expected that smaller, lower profile sensors would be used for in-situ monitoring which will require thorough investigation of the best methods to attach them to minimize soft tissue artifact.

VI. CONCLUSIONS Some form of elbow-axis to sensor orientation calibration

process was necessary and this exercise appeared beneficial. Sensor mounting location, muscle loading and longitudinal rotation of the forearm all influenced the data generated from the inertial sensors during functional movements and the cricket bowling action. Work is ongoing to minimize the effect of these factors to allow inertial sensors to be used as a bowling training aid and illegal action assessment tool. Work is also ongoing to understand which aspects of the movement are individual or generic so on-field monitoring with inertial sensors is effective in cricket.

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