biomechatronics - lecture 11. artificial sensing

Biomechatronics

Delft University of Technology, 2007

Wb 2432

Artificial Sensory Systems

Frans van der Helm

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Sensing for assistive motor systems

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why?

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Sensory signalsderived from the human body

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Angle recording

standing

sitting

Standing(right legin front)

Standing(left legin front)

sitdown

Step right

standup

Step left

Buttons in crutches

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Measure physiological signals

Brain signals EEG

Intention detection

Think left or right

Pfurtscheller et al.(Graz)

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Measure physiological signalsmuscle activation: EMG

EMG processing

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Intention detection

MIT media labsexpressive footwear:

Measuring motions and forces

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Intention detection

MIT media labsexpressive footwear

Byron in action

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• use body's own sensors and CNS signals

• artificial sensors


physiological sensors

(Sinkjaer et al., Aalborg Universtiy)

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physiological sensors

(Sinkjaer et al., Aalborg Universtiy)

Measure body's own sensory signals

tripolar measurement cuff

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Universityof Aalborg

Measure body's own sensory signals

skin pressuresensors

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1. Muscle stimulation2. Neural sensing of

tactile stimuli3. Controller4. Spinal cord lesion5. Intent detection

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Rutten et al., University of Twente

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Sensory feedback to the userby stimulation of skin sensors

sensor

Dorindo Buma

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sensor

Sensing for assistive motor systemsSensory feedback to the user by stimulation of skin sensors

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Influence of stimulation level on sensation

Dorindo Buma

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Sensing for assistive motor systemsSensory feedback to the user by stimulation of skin sensors

Influence of intermittent stimulation on sensation

Dorindo Buma

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• use body's own sensors and CNS signals

• artificial sensors


Triaxial accelerometer

(Lötters et al., 1998, University of Twente)

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Artificial sensors for assistive motor systems

force sensors

Force sensitive resistors (FSR)

• Interface forces:

• Bending moments

Force sensitive capacitors

also shear forces !Piezo electric

E.g. Strain gauges

•Tendon force

only perpendicularforces

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Artificial sensors for assistive motor systems

movement sensors• goniometers

• Inertial sensorsaccelerometers

gyroscope

• Magnetic sensors

Hall effect based joint angle sensor(Case Western Reserve University, Cleveland)

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Inertial sensing

accelerometer

Rate gyroscope(angular velocity sensor)

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The human vestibular systemis an 3D inertial sensor system

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University of Twente BIOS group

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Inertial sensing

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Detector posture - movement

Example resultdetection posture - movement

Distinguish postures by analysinginclinations of body segments

tangentialthigh

Detection of postures and movementsusing uni-axial accelerometers

(Veltink et al., 1996)

radialsacrum

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hemiplegic gait: drop foot stimulatoraccelerometer at shank

Willemsen et al., IEEE-BME, 1990

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time (s)

push-off detection

swing phase detectiondescending part

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time delay

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(Luinge et al., 1999, University of Twente)

Kalmanfilter

optimalestimationof orientation

3D rate gyroscopesignals

signals3D accelerometer

signal analysis

Inertial sensor: quantitative sensingestimation of orientation

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�� Reconstruction of knee angle from 3D inertial sensors on thigh and shank• Sensor axes were directed arbitrarily. • Initial reference measurement with flexing/extending knee required

3D inertial sensor system(accelerometer - rate gyroscope)

reconstruction of knee angle during gait

gonio (reference)

gyro + accel

Integrationgyro signal

(Luinge et al.1999)

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DiscussionThe best sensor is no sensor??

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Discussion

The best sensor is no sensor??

Sensor and control can result inreproducible, reliable and flexible performance.

Challenge: the complexity of the systemas observed by the user should not increase,rather decrease!

This is possible:e.g. - intention detection: no explicit commands

- sensor in stimulator or orthotic components- choose optimal sensors: small, possibly implantable, giving optimal amount of info

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Sensing for assistive motor systemswhy?

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Sensor Physical quantity Transduction principles Interaction with the body

CNS signals /muscle activation

EEG / MEG Brain signals Electric / Magnetic Electrodes / coilsENG / MNG Signals from nerves Electric / Magnetic Electrodes / coilsEMG / MMG Muscle activation Electric / Magnetic Electrodes / coils

Sensor Physical quantity Transduction principles Interaction with the body

ForceStrain gauges Strain of material →

measure for Force /moment

Resistive/ piezoresistive Attachment on prosthetic /orthotic elements

Pressure sensors Pressure - Force Sensitive resistors(FSR)- Force Sensitive Capacity

Attach between segmentand environment oncontact surface

PhysiologicalSkin sensors

Skin stress (phasicrather than staticcomponents)

Physiological sensors Derive via electrodesaround sensory nerves(Hoffer, Stein et al. 1996;Sinkjaer 1999)


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Sensing for assistive motor systemsSensor Physical quantity Transduction principles Interaction with the body

MovementGoniometer Joint angle (1, 2 or

3D)- Resistive- Hall effect + magnet(Johnson, Peckham et al.1999)

Attach to two segmentsconnected by joint

Orientationsensor

Orientation withrespect to earthcoordinate system

- Hall effect (earth magneticfield)- inertial: gravityacceleration

Attach sensor to bodysegment

Rate of turnGyroscope

Angular velocity (1 –3D)

- inertial, coriolis /piezoresistive (Soderkvist1994)

Attach to body segment(Baten, Oosterhoff et al.1996)

Accelerometer Acceleration (inertial+ gravitational: 1 –3D)

Inertial / piezoresistive,piezoelectric or capacitive(Lotters, Olthuis et al. 1995)

Attach to body segment

Position sensor - relative distance toobjects inenvironment- absolute position inspace

- radar using ultrasonictransmitters/sensors (Piezoelectric)- GPS: Global PositioningSystem using satellitecommunication

-ultrasonic transmitters /senors mounted on body(Shoval, Borenstein et al.1998)- GPS system mounted onbody

biomechatronics - lecture 11. artificial sensing

Education

assistive motor systemswhy

optimal sensors

discussionthe best sensor

measure bodys

explicit commands sensor

shank sensor axes

detection of postures

d accelerometer luinge