Inertial Measurement Units (IMUs)

1
Inertial Measurement Units(IMUs) Theory and
Practice
H.J. Sommer III, Ph.D. The Pennsylvania State
University University Park, PA 16802 hjs1_at_psu.edu
www.mne.psu.edu/sommer
2
Inertial Measurement Unit ?

• Kinematic measurements using inertial references
• Attitude and magnetic heading
• Angular velocity
• Acceleration
• Fuse data to provide more reliable results

3
Inertial Measurement Unit ?
14x28 mm
4
Inertial Measurement Unit ?
5
Inertial Measurement Unit ?
6
Inertial Measurement Unit ?
7
Inertial Measurement Unit ?
8
Traditional KinematicMeasurements

• Photogrammetry
• Absolute location of point markers
• Goniometry
• Relative angles across body segments
• Electromagnetic digitizers
• 6DOF of discrete sensors

9
Photogrammetry
10
Photogrammetry Quiz(for Oldtimers)

• Vanguard or RightGuard?
• DLT or BLT?
• Lo-Cam or Hi-Cam?

11
Photogrammetry

• Positive
• Absolute location and attitude of body segments
• Multiple IR cameras with ambient lighting
• Automatic marker tracking
• No cables to subject
• gt 100 Hz, high resolution
• Markerless motion capture (MMC)

12
Photogrammetry

• Negative
• Calibration relative to anatomy (joints and mass
  centers)
• Requires finite differences for velocity and
  acceleration
• Marker occlusion
• Soft tissue artifact
• Limited workspace in a gait lab

13
Goniometry
14
Goniometry

• Positive
• Direct measurement of joint motion
• Easy to use
• Negative
• Does not measure absolute position/attitude
• Physical attachment to subject

15
Electromagnetic Digitizers
16
Electromagnetic Digitizers

• Positive
• 6 DOF for each body segment
• Negative
• Limited workspace
• Cables (new wireless)
• Physical attachment to subject
• Accuracy degraded by speed

17
IMUs
Integrated Kinematic Sensor (IKS) Wu and Ladin,
1993
18
IMUs

• Attitude relative to gravity vector
• Magnetic heading
• Rotational velocity
• Translational acceleration

19
IMUs

• Positive
• Absolute attitude of body segments
• Direct measurement of angular velocity
• Direct measurement of acceleration
• No marker occlusion
• Large work space in unstructured environment

20
IMUs

• Negative
• Does not provide absolute location, translational
  velocity or rotational acceleration
• Calibration relative to anatomy
• Soft tissue artifact
• Data communication
• lt 100 Hz, medium resolution

21
History of IMUs

• Vehicle navigation
• Intercontinental ballistic missiles (ICBM)
• Nuclear submarines
• Cruise missiles
• MicroElectroMechanical Systems (MEMS)
• Automotive
• Consumer products

22
MEMS IMUs - Automotive

• Automotive
• Accelerometers to deploy airbags
• Vehicle roll handling

23
MEMS IMUs Consumer Products

• Games (WiiMote)
• PDA (iPhone)
• Camera stabilization
• Hard disks

24
MEMS Fabrication
25
MEMS Comb Sensor/Drive
26
MEMS accelerometer(proof mass)
gravity
acceleration
27
MEMS accelerometer
28
MEMS gyro (tuning fork)
29
MEMS magnetometer (magnetoresistive)
30
MEMS IMU Outputs

• Signal
• Analog voltage (0 to 3V)
• Fixed frequency, variable duty cycle
• Digital (internal A/D converter)
• Bandwidth
• lt 150 Hz

31
Two-Dimensional (2D) IMU

• Biaxial accelerometer
• Uniaxial gyro

32
Three-Dimensional (3D) IMU

• Triaxial accelerometer
• Triaxial gyro
• Triaxial magnetometer
• Required to determine spin about gravity vector

33
MEMS 9DOF IMU

• Triaxial accelerometer
• 3g, 300 mV/g, 550 Hz
• Triaxial gyro
• 300 deg/sec (dps), 3.3mV/dps, 140 Hz
• Triaxial magnetometer
• 50 Hz
• On-board CPU, serial I/O

34
Break Time
Stand up Stretch Say hello to your neighbor
35
Data Fusion

• Sensor uncertainty
• Geometric
• Rigid body
• Articulated model
• State space
• Kalman filter

36
Sensor Uncertainty

• s measured signal
• b zero drift or bias (function of temp)
• f scale factor (function of temp)
• w Gaussian white noise
• s2 variance

37
LSY530 gyro 300 degps

• Nonlinearity 1
• b 1.23 V, 0.05 degps/C
• f 300 degps/V, 0.05 /C
• s 0.035 degps/sqrt(Hz) pink noise

38
Rigid Body Fusion

• Multiple IMUs per body
• Parallel axes
• Rejects gravity effects

39
Articulated Model - Pendulum
40
Multiple Segment Model
41
Kalman Filter

• Uses state space model
• Position
• Velocity
• Adaptive time domain filter
• Combines states
• Tracks variance-covariance
• Rejects zero drift

42
Kalman Filter - 2D IMU
43
Kalman Filter - Simplified
44
Kalman Filter Prediction
probability
q latitude
45
Kalman Filter - Measurement
probability
q latitude
46
Kalman Filter - Correction
probability
q latitude
47
Kalman Filter - Prediction
probability
constant speed fixed time
q latitude
48
Kalman Filter 2D IMU
probability
q angle
49
Kalman Filter - Extended

• State space
• Include acceleration
• Nonlinear state relationships
• ax-ay-qdot versus q-qdot
• Include geometric multisegment model
• Include states for multiple bodies

50
Kalman Filter
51
Kalman Filter
52
Applications

• Stationary
• Simple attitude
• Simple motion
• Coordinated movement
• Inverse dynamics

53
Stationary

• Minimal change in sensor orientation
• Hand/arm tremor
• Extended arm, tracing spiral
• Triaxial accelerometer, gt150 Hz
• Postural sway
• Supracranial accelerometer
• Lumbar accelerometer

54
Simple Attitude

• Body position during sleep
• Treatment for sleep apnea
• Triaxial accelerometer, very low sample rate
• Not interested in spin about gravity vector
• Restless Leg Syndrome (RLS)
• Monitor sudden movement
• High frequency sample rate
• Interested in event itself, not characterization

55
Simple Motion

• Planar lifting or reaching
• Simple articulated model
• 2D IMU provides position, velocity, acceleration
• Passive manipulation or drop
• Assess spasticity
• Compute jerk from acceleration

56
Coordinated Movement

• Basic assessment
• Triaxial accelerometer, gt100 Hz
• Number of strides, timing
• Asymmetry of motion
• Rehabilitation, prosthetic fitting
• Full body motion
• Thirteen 9DOF IMUs
• Multiple segment model

57
Inverse Dynamics

• 2D
• Lower data throughput (3ch versus 9ch)
• Require sagittal and frontal IMUs
• Does not require magnetometers
• 3D
• Lifting or reaching most promising
• Difficulty in assessing absolute location of feet

58
Practical Considerations

• Motion variables
• Consider alternate signals to describe motion
• Number of IMUs
• May require two per segment
• Synchronization
• In-shoe pressure transducers

59
Data Transfer

• Umbilical with local A/D
• Belt-pack data logger
• SD card
• Belt-pack wireless
• Bluetooth, longer battery life
• Network wireless
• Dropouts, battery life

60
Commercial Systems

• Xsens MVN
• Biosyn FAB
• NexGen Ergonomics
• Microstrain wireless
• MEMSense
• Sparkfun WiTilt
• Nintendo WiiMote