Biomechatronics - Lecture 11. Artificial sensing
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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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Sensing for assistive motor systems
why?
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Sensing for assistive motor systems
Sensory signalsderived from the human body
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Sensing for assistive motor systems
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
Sensing for assistive motor systems
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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Sensing for assistive motor systems
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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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
Sensing for assistive motor systems
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
F
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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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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
p ha s
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time (s)
push-off detection
swing phase detectiondescending part
acce
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ascending part
heel
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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)
Sensing for assistive motor systems
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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