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Measurements and Signal processing (part 2) MCE 493/593 & ECE 492/592 Prosthesis Design and Control September 30, 2014. Antonie J. (Ton) van den Bogert Mechanical Engineering Cleveland State University. Today. Laboratory techniques for human motion Camera-based motion capture

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Measurements and Signal processing (part 2) MCE 493/593 & ECE 492/592 Prosthesis Design and Control September 30, 2014

Antonie J. (Ton) van den Bogert

Mechanical Engineering

Cleveland State University


Today
Today

  • Laboratory techniques for human motion

    • Camera-based motion capture

    • Force plates& instrumented treadmills

    • Balance testing

    • Strength testing

  • Lab tour

    • 7:20 PM

    • FH 269


History of motion capture
History of motion capture

  • Muybridge, 1870s

    • multiple cameras, 2D

  • Marey, 1870s

    • strobe lights as markers

  • Braune & Fischer, 1895

    • strobe lights, 3D


Distance based measurement
Distance-based measurement

  • Measure distance to three (or more) sources

    • solve XYZ from 3 nonlinear equations with 3 unknowns

  • GPS

    • resolution insufficient

      for human motion

  • Ultrasound

    • www.zebris.de


A ctive marker systems
Active marker systems

  • Markers are LEDs

    • flashing sequentially

  • Camera

    • projects marker on image plane or line

  • Most common: three 1-D cameras in one box

    • high resolution

    • high frame rate

    • markers must be seen from box

Optotrak

Codamotion (no lenses!)


Passive marker systems
Passive marker systems

  • All markers visible

    • 2D cameras

  • 16 mm film, analog video

    • manually digitized

  • Digital video cameras

    • reflective markers

    • infrared strobe lights

    • high contrast, thresholding

    • 2D marker centroid coordinates

      • combined into XYZ of markers

    • Vicon, Motion Analysis, Qualisys


z

y

x

3D measurement requires at least two (2D) cameras

3-D space

v

u

  • Two cameras:

  • u,v are measured in each camera

  • Solve x,y,z from 4 equations

  • More cameras:

  • better accuracy

  • less chance of marker loss

lens

image plane

camera model:

DLT (direct linear transformation)

a1…a11 are calibration constants

(different for each camera)


Capture Lab

at Electronic Arts:

132 Vicon cameras

Fenn Hall 269:

10 Motion Analysis cameras


Recent developments
Recent developments

  • Markerless motion capture

  • Improved IMU data processing

  • IMU combined with range sensor

    • www.xsens.com

  • Microsoft Kinect

  • Optical, camera-based measurement with markers is still the “gold standard” for human motion labs

    • still very expensive


Camera based motion capture in 2d
Camera-based motion capture in 2D

markers

assumed to

stay

in XY plane

y

x

v

lens

u

camera image plane

parallel to XY plane

Camera model:

Camera parameters:

S: scale factor (meters per pixel)

θ: angle between X-axis and U-axis

uO,vO: image coordinates of XY origin

determined by imaging a rod

of known length, one end at origin,

aligned with X-axis


Matlab code for measuring u v from video
Matlab code for measuring U,V from video

movie = VideoReader(‘testfile.avi'); % load the video file

nframes = movie.NumberOfFrames;

height = movie.Height;

npoints = 10; % how many points must be measured in each frame

uvdata = []; % make a matrix to store the data

% display each frame and measure U and V of all points

for i = 1:nframes

d = read(movie,i); % extract frame i from the movie

image(d); % put the image on the screen

disp(['Frame ',num2str(i),':']);

disp(['Click on ',num2str(npoints),' points']);

disp('Click to the left of the image to stop.')

g = ginput(npoints); % collect data until user has clicked on all points

if (min(g(:,1)) < 0) % if any point had a negative U-coordinate, stop

break

end

disp('Done')

g(:,2) = height - g(:,2); % invert V coordinates so V-axis will point upward

uvdata= [uvdata; reshape(g’, 1, 2*npoints)];% add a row to the data matrix

end


Clinical Orthopaedics andRelated Research, 1983

  • Techniques used:

  • 16 mm film at 50 frames per second

  • camera car alongside walking subject

  • markers on wall behind subject for calibration

  • Numonics Digitizer & microcomputer

  • IBM 370 for processing

  • about 2 mm random error in coordinates

  • 5 Hz low pass filter


Angle measurement
Angle measurement

Two markers on a body segment  segment angle

Joint angle = difference between two segment angles

Matlab:

theta21 = atan2(y1-y2, x1-x2);

theta43 = atan2(y3-y4, x3-x4);

theta_knee = theta21 – theta43;

  • atanwould give results between –π/2 and π/2, requires extra “if-then” logic

  • atan2 function gives results between –π and π, can represent full range of rotation

  • use “unwrap” function on time series if angle jumps between –π and π

  • If you use Excel:

Winter, 3rd Edition, Fig. 2.31


Some real data
Some real data

1: RGTRO

right greater trochanter

Y

2,3: RLEK

right lateral epicondyle

of the knee

4: RLM

right lateral malleolus

X

theta21 = atan2(y1-y2, x1-x2);

theta43 = atan2(y3-y4, x3-x4);

theta_knee = theta21 – theta43;

What is the knee angle at time = 2959.594329?

theta21 = atan2(0.90533-0.51603, -0.19465-0.01730)

theta43 = atan2(0.51603-0.12862, 0.01730--0.09302)

theta_knee = theta21 - theta43


Force plate
Force plate

AMTI

  • Measures ground reaction forces

    • rigid plate supported by four (or three) 3D force sensors

    • main vendors: Kistler, AMTI, Bertec

    • measures 6 variables: resultant 3D force (Fx,Fy,Fz) and moment (Mx,My,Mz) on the axes of the force plate

    • also available as instrumented treadmill

    • http://www.kwon3d.com/theory/grf.html

Fxyz, Mxyz

forces acting on foot

forces in load cells

force and torque acting at center of pressure (COP)

Equivalent force systems:

(b) = (c) = (d)

Fz,Mz

Fx,Mx

Fy,My


Resultant 3d force and moment from four load cells
Resultant 3D force and moment from four load cells

  • 3D force F, applied at r, is equivalent to a 3D force F applied at the origin, plus a 3D moment M = r x F

  • Resultant of all four:


Cop center of pressure representation
COP (center of pressure) representation

  • 3D force F is assumed at COP rather than origin

  • Definition of COP (x,y)

    • z=0 and Mx=My=0 at COP (zero moment point)

  • Remaining moment Tz about vertical axis

    • “free moment”

  • still 6 variables


Diy grf measurement and save 50 000
DIY GRF measurement(and save $50,000)

Brodt et al. (2013) Instrumented foot bar for Pilates exercise

XXIV ISB Congress, Natal, Brazil


Simple force plate
Simple force plate

FORCE

  • Vertical force only

  • Three points of support (no static indeterminacy)

  • Gives accurate COP in certain conditions

    (Zsensor * Fx << My and Zsensor * Fy << Mx)

Zsensor


Instrumented treadmills
Instrumented treadmills

  • Treadmill frame sits on three or four 3-axis load cells

    • must be stiff and light

  • Separate belts for left and right

  • Very good for clinical research

    • each step is a measurement

    • speed can be controlled or self-paced

    • weight support is possible

  • Prosthetics research

    • controlled speed

    • prosthetic device can be tethered

      to power supply and computer

ADAL treadmill at Cleveland VA

Medical Center


Strength testing
Strength testing

Maximal isometric torque

Cybex

Kincom

Speed dependent torque

motor and

torque sensor

force from

leg

Isometric test: constant joint angle

Isokinetic test: constant joint angular velocity

lengthening

(eccentric)

muscle shortening

(concentric)


B alance testing clinical
Balance testing (clinical)

  • Platform with controlled rotation

  • Built-in force plate (vertical force only?)

  • COP calculation

  • screening for risk of falling

  • balance training

  • knee injuries

  • concussion testing

Biodex SD

$12,500

http://youtu.be/cBBlTYMulsE


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