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Center of Pressure Estimation and Gait Pattern Recognition Using Shoes with Photo-reflective Sensors (OzCHI2018)

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Center of Pressure Estimation and
Gait Pattern Recognition Using Shoes
with Photo-reflective Sensors
K o n o m i I n a b a...

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• Having a good walking posture will promote health.
• Center of Pressure
2
[1] http://www.kao.co.jp/rd/eiyo/about-hoco/ho...

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• The measurable environment
is limited.
3
[3] A Mobile Force Plate System and Its Application to Quantitative Evaluation ...

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Center of Pressure Estimation and Gait Pattern Recognition Using Shoes with Photo-reflective Sensors (OzCHI2018)

  1. 1. Center of Pressure Estimation and Gait Pattern Recognition Using Shoes with Photo-reflective Sensors K o n o m i I n a b a †1 A k i h i k o M u r a i †2 Y u t a S u g i u r a †1 †1 K e i o U n i v e r s i t y †2 A I S T
  2. 2. • Having a good walking posture will promote health. • Center of Pressure 2 [1] http://www.kao.co.jp/rd/eiyo/about-hoco/hoco02.html Gait Analysis Gait measurement system using camera [1] Difference in CoP trajectory depending on subject group [2] • Measure pressure and its center position during walking [2] The initiation of gait in young, elderly, and Parkinson's disease subjects Suzanne E Halliday, David A Winter, James S Frank, Aftab E Patla, François Prince GAIT&POSTURE 1998
  3. 3. • The measurable environment is limited. 3 [3] A Mobile Force Plate System and Its Application to Quantitative Evaluation of Normal and Pathological Gait, T. Liu, Y, Inoue, K. Shibata, Y. Hirota, K. Shiojima, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2010 Measurement of CoP Measurement by force plate and motion capture [3] by Force Plate by Using Insole • Durability may be an issue. [4] Gait Analysis Using a Shoe-Integrated Wireless Sensor System. Stacy J. Morris Bamberg, Ari Y.Benbasat, Donna Moxley Scarborough, David E. Krebs, and Joseph A. Paradiso, Senior. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE. 2008 Insole with built-in sensor [4]
  4. 4. 4 Our Purpose and Methods Purpose • Highly durable devices • CoP estimation and gait pattern identification using it Methods • Embed photo-reflective sensor (PRS) in outsole of shoes • Estimate CoP by regression analysis • Recognize gait pattern using Support Vector Machine(SVM)
  5. 5. • Measures the deformation of the sole by photo sensor. 5 Shoe Hardware Device
  6. 6. 6 Method of CoP Estimation
  7. 7. 7 Experiment for accuracy evaluation of CoP estimation Conditions Participant 2 (Male) Estimation Y-axis only Ground truth CoP coordinates calculated from the force plate Data set per participant 450frame (35fps, 0.43s/step, 30step) Learning Random forest regression Ground truth and estimation CoP when the decision coefficients is the highest (left) and lowest (right) (mm) (mm) Estimation result Ground truth Max Ave Coefficient 0.94 0.69 Error(mm) 32.7 11.4 • A lag occurs from movement to detection of deformation. • Accuracy may increase by including the lag into the preprocessing of learning and estimation. Result
  8. 8. 8 Method of Gait Pattern Identification Learn
  9. 9. • Generate an image by converting sensor values to pixel values 9 Conversion of Sensor Values to Image Data 1 2 3 ・ ・ ・ 1 2 3 Sensor value max min Heel contactNormal Toe contact … n frame sensor
  10. 10. 10 Experiment for Accuracy Evaluation of Gait Pattern Identification Participants 5 (Male) Gait pattern 9 Data set per class 15 step Learning SVM Evaluation 5-fold cross validation Condition Normal Heel contactToe contact Inner locus Outer locus Pigeon-toedBowlegged Left turn Right turn
  11. 11. 11 Result and Discussion 2 Normal Toe contact Heel contact Bowlegg ed Pigeon- toed Inner locus Outer locus Left turn Right turn Normal 87% 0% 3% 3% 3% 1% 1% 1% 1% Toe contact 1% 97% 0% 0% 1% 0% 1% 0% 0% Heel contact 3% 1% 79% 2% 3% 2% 3% 2% 4% Bowlegg ed 1% 0% 1% 75% 7% 4% 1% 5% 6% Pigeon- toed 4% 1% 5% 12% 55% 9% 3% 5% 7% Inner locus 3% 0% 2% 7% 8% 74% 2% 1% 3% Outer locus 0% 0% 4% 2% 1% 3% 87% 3% 1% Left turn 3% 0% 1% 5% 5% 4% 3% 71% 7% Right turn 2% 0% 1% 3% 7% 3% 2% 7% 76% • The identification accuracy was 78% on average. • The accuracy of pigeon- toed was 55%. • It is still challenging to differentiate walking above the shoes.
  12. 12. 12 Conclusion Background • CoP estimation is important in medical field. Purpose • CoP estimation and Gait recognition using shoes with photo-reflective sensors. Experiment • CoP estimation error is 11.4mm. • Accuracy of Gait pattern recognition is 78%.

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