Literature DB >> 33498956

A Lightweight Exoskeleton-Based Portable Gait Data Collection System.

Md Rejwanul Haque1, Masudul H Imtiaz2, Samuel T Kwak3, Edward Sazonov4, Young-Hui Chang3, Xiangrong Shen1.   

Abstract

For the controller of wearable lower-limb assistive devices, quantitative understanding of human locomotion serves as the basis for human motion intent recognition and joint-level motion control. Traditionally, the required gait data are obtained in gait research laboratories, utilizing marker-based optical motion capture systems. Despite the high accuracy of measurement, marker-based systems are largely limited to laboratory environments, making it nearly impossible to collect the desired gait data in real-world daily-living scenarios. To address this problem, the authors propose a novel exoskeleton-based gait data collection system, which provides the capability of conducting independent measurement of lower limb movement without the need for stationary instrumentation. The basis of the system is a lightweight exoskeleton with articulated knee and ankle joints. To minimize the interference to a wearer's natural lower-limb movement, a unique two-degrees-of-freedom joint design is incorporated, integrating a primary degree of freedom for joint motion measurement with a passive degree of freedom to allow natural joint movement and improve the comfort of use. In addition to the joint-embedded goniometers, the exoskeleton also features multiple positions for the mounting of inertia measurement units (IMUs) as well as foot-plate-embedded force sensing resistors to measure the foot plantar pressure. All sensor signals are routed to a microcontroller for data logging and storage. To validate the exoskeleton-provided joint angle measurement, a comparison study on three healthy participants was conducted, which involves locomotion experiments in various modes, including overground walking, treadmill walking, and sit-to-stand and stand-to-sit transitions. Joint angle trajectories measured with an eight-camera motion capture system served as the benchmark for comparison. Experimental results indicate that the exoskeleton-measured joint angle trajectories closely match those obtained through the optical motion capture system in all modes of locomotion (correlation coefficients of 0.97 and 0.96 for knee and ankle measurements, respectively), clearly demonstrating the accuracy and reliability of the proposed gait measurement system.

Entities:  

Keywords:  exoskeleton; gait measurement; wearable sensors

Year:  2021        PMID: 33498956      PMCID: PMC7865931          DOI: 10.3390/s21030781

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  10 in total

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Journal:  J Biomech       Date:  1999-06       Impact factor: 2.712

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Journal:  J Biomech       Date:  1999-06       Impact factor: 2.712

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Authors:  Margaret A Perrott; Tania Pizzari; Jill Cook; Jodie A McClelland
Journal:  Gait Posture       Date:  2016-10-31       Impact factor: 2.840

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Journal:  J Biomech Eng       Date:  2012-08       Impact factor: 2.097

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Review 7.  Gait analysis using wearable sensors.

Authors:  Weijun Tao; Tao Liu; Rencheng Zheng; Hutian Feng
Journal:  Sensors (Basel)       Date:  2012-02-16       Impact factor: 3.576

8.  Early Detection of the Initiation of Sit-to-Stand Posture Transitions Using Orthosis-Mounted Sensors.

Authors:  Abul Doulah; Xiangrong Shen; Edward Sazonov
Journal:  Sensors (Basel)       Date:  2017-11-23       Impact factor: 3.576

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Authors:  Lars Mündermann; Stefano Corazza; Thomas P Andriacchi
Journal:  J Neuroeng Rehabil       Date:  2006-03-15       Impact factor: 4.262

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Authors:  Elena Ceseracciu; Zimi Sawacha; Claudio Cobelli
Journal:  PLoS One       Date:  2014-03-04       Impact factor: 3.240

  10 in total
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  3 in total

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