Literature DB >> 32321637

Portable, automated foot progression angle gait modification via a proof-of-concept haptic feedback-sensorized shoe.

Haisheng Xia1, Jesse M Charlton2, Peter B Shull1, Michael A Hunt3.   

Abstract

Modifying the foot progression angle (FPA) is a non-pharmacological, non-surgical treatment option for knee osteoarthritis, however current widespread adoption has been limited by the requirement of laboratory-based motion capture systems. We present the first customized haptic feedback-sensorized shoe for estimating and modifying FPA during walking gait, which includes an electronic inertial and magnetometer module in the sole for estimating FPA, and two vibration motors attached to the medial and lateral shoe lining for providing vibrotactile feedback. Feasibility testing was performed by comparing FPA performance while wearing the haptic feedback-sensorized shoe with the training targets. Participants performed five walking trials with five randomly-presented FPA targets (10° toe-in, 0°, 10° toe-out, 20° toe-out, and 30° toe-out) of 2 min each on a treadmill. Overall average FPA performance error across all conditions was 0.2 ± 4.1°, and the overall mean absolute FPA performance error across all conditions was 3.1 ± 2.6°. Reducing the size of the no-feedback window resulted in less performance error during walking. This study demonstrates that a novel haptic feedback-sensorized shoe can be used to effectively train FPA modifications. The haptic feedback-sensorized shoe could potentially be used for FPA gait modification outside of specialized camera-based motion capture laboratories as a conservative treatment for knee osteoarthritis or other related clinical applications requiring FPA assessment and modification in daily life.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Gait modification; Knee osteoarthritis; Wearable sensing and feedback

Mesh:

Year:  2020        PMID: 32321637     DOI: 10.1016/j.jbiomech.2020.109789

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  4 in total

1.  Changes in foot progression angle during gait reduce the knee adduction moment and do not increase hip moments in individuals with knee osteoarthritis.

Authors:  Kirsten Seagers; Scott D Uhlrich; Julie A Kolesar; Madeleine Berkson; Janelle M Kaneda; Gary S Beaupre; Scott L Delp
Journal:  J Biomech       Date:  2022-06-20       Impact factor: 2.789

Review 2.  Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review.

Authors:  Michael J Rose; Kerry E Costello; Samantha Eigenbrot; Kaveh Torabian; Deepak Kumar
Journal:  JMIR Rehabil Assist Technol       Date:  2022-06-02

3.  Predicting knee adduction moment response to gait retraining with minimal clinical data.

Authors:  Nataliya Rokhmanova; Katherine J Kuchenbecker; Peter B Shull; Reed Ferber; Eni Halilaj
Journal:  PLoS Comput Biol       Date:  2022-05-16       Impact factor: 4.779

4.  A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images.

Authors:  Peter Ardhianto; Raden Bagus Reinaldy Subiakto; Chih-Yang Lin; Yih-Kuen Jan; Ben-Yi Liau; Jen-Yung Tsai; Veit Babak Hamun Akbari; Chi-Wen Lung
Journal:  Sensors (Basel)       Date:  2022-04-05       Impact factor: 3.576

  4 in total

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