Literature DB >> 25014949

A noncontact capacitive sensing system for recognizing locomotion modes of transtibial amputees.

Enhao Zheng, Long Wang, Kunlin Wei, Qining Wang.   

Abstract

This paper presents a noncontact capacitive sensing system (C-Sens) for locomotion mode recognition of transtibial amputees. C-Sens detects changes in physical distance between the residual limb and the prosthesis. The sensing front ends are built into the prosthetic socket without contacting the skin. This novel signal source improves the usability of locomotion mode recognition systems based on electromyography (EMG) signals and systems based on capacitance signals obtained from skin contact. To evaluate the performance of C-Sens, we carried out experiments among six transtibial amputees with varying levels of amputation when they engaged in six common locomotive activities. The capacitance signals were consistent and stereotypical for different locomotion modes. Importantly, we were able to obtain sufficiently informative signals even for amputees with severe muscle atrophy (i.e., amputees lacking of quality EMG from shank muscles for mode classification). With phase-dependent quadratic classifier and selected feature set, the proposed system was capable of making continuous judgments about locomotion modes with an average accuracy of 96.3% and 94.8% for swing phase and stance phase, respectively (Experiment 1). Furthermore, the system was able to achieve satisfactory recognition performance after the subjects redonned the socket (Experiment 2). We also validated that C-Sens was robust to load bearing changes when amputees carried 5-kg weights during activities (Experiment 3). These results suggest that noncontact capacitive sensing is capable of circumventing practical problems of EMG systems without sacrificing performance and it is, thus, promising for automatic recognition of human motion intent for controlling powered prostheses.

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Year:  2014        PMID: 25014949     DOI: 10.1109/TBME.2014.2334316

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  12 in total

1.  Real-Time Gait Phase Estimation for Robotic Hip Exoskeleton Control During Multimodal Locomotion.

Authors:  Inseung Kang; Dean D Molinaro; Srijan Duggal; Yanrong Chen; Pratik Kunapuli; Aaron J Young
Journal:  IEEE Robot Autom Lett       Date:  2021-02-26

2.  Continuous locomotion mode classification using a robotic hip exoskeleton.

Authors:  Inseung Kang; Dean D Molinaro; Gayeon Choi; Aaron J Young
Journal:  Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatron       Date:  2020-10-15

3.  Loading Effect of Prosthetic Feet's Anthropomorphicity on Transtibial Osseointegrated Implant.

Authors:  Mark Pitkin; Laurent Frossard
Journal:  Mil Med       Date:  2021-01-25       Impact factor: 1.437

4.  Locomotor activities of individuals with lower-limb amputation.

Authors:  Bantoon Srisuwan; Glenn K Klute
Journal:  Prosthet Orthot Int       Date:  2021-06-01       Impact factor: 1.672

5.  PSO-SVM-Based Online Locomotion Mode Identification for Rehabilitation Robotic Exoskeletons.

Authors:  Yi Long; Zhi-Jiang Du; Wei-Dong Wang; Guang-Yu Zhao; Guo-Qiang Xu; Long He; Xi-Wang Mao; Wei Dong
Journal:  Sensors (Basel)       Date:  2016-09-02       Impact factor: 3.576

6.  Whole Body Awareness for Controlling a Robotic Transfemoral Prosthesis.

Authors:  Andrea Parri; Elena Martini; Joost Geeroms; Louis Flynn; Guido Pasquini; Simona Crea; Raffaele Molino Lova; Dirk Lefeber; Roman Kamnik; Marko Munih; Nicola Vitiello
Journal:  Front Neurorobot       Date:  2017-05-30       Impact factor: 2.650

Review 7.  Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices-A Systematic Review.

Authors:  Floriant Labarrière; Elizabeth Thomas; Laurine Calistri; Virgil Optasanu; Mathieu Gueugnon; Paul Ornetti; Davy Laroche
Journal:  Sensors (Basel)       Date:  2020-11-06       Impact factor: 3.576

8.  Locomotion Mode Recognition with Inertial Signals for Hip Joint Exoskeleton.

Authors:  Gang Du; Jinchen Zeng; Cheng Gong; Enhao Zheng
Journal:  Appl Bionics Biomech       Date:  2021-05-24       Impact factor: 1.781

9.  Forearm Motion Recognition With Noncontact Capacitive Sensing.

Authors:  Enhao Zheng; Jingeng Mai; Yuxiang Liu; Qining Wang
Journal:  Front Neurorobot       Date:  2018-07-27       Impact factor: 2.650

10.  On-board Training Strategy for IMU-Based Real-Time Locomotion Recognition of Transtibial Amputees With Robotic Prostheses.

Authors:  Dongfang Xu; Qining Wang
Journal:  Front Neurorobot       Date:  2020-10-22       Impact factor: 2.650

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