Literature DB >> 23475336

Kinetic Gait Analysis Using a Low-Cost Insole.

Adam M Howell, Toshiki Kobayashi, Heather A Hayes, K Bo Foreman, Stacy J Morris Bamberg.   

Abstract

Abnormal gait caused by stroke or other pathological reasons can greatly impact the life of an individual. Being able to measure and analyze that gait is often critical for rehabilitation. Motion analysis labs and many current methods of gait analysis are expensive and inaccessible to most individuals. The low-cost, wearable, and wireless insole-based gait analysis system in this study provides kinetic measurements of gait by using low-cost force sensitive resistors. This paper describes the design and fabrication of the insole and its evaluation in six control subjects and four hemiplegic stroke subjects. Subject-specific linear regression models were used to determine ground reaction force plus moments corresponding to ankle dorsiflexion/plantarflexion, knee flexion/extension, and knee abduction/adduction. Comparison with data simultaneously collected from a clinical motion analysis laboratory demonstrated that the insole results for ground reaction force and ankle moment were highly correlated (all >0.95) for all subjects, while the two knee moments were less strongly correlated (generally >0.80). This provides a means of cost-effective and efficient healthcare delivery of mobile gait analysis that can be used anywhere from large clinics to an individual's home.

Entities:  

Mesh:

Year:  2013        PMID: 23475336     DOI: 10.1109/TBME.2013.2250972

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


  22 in total

1.  Estimating Ground Reaction Force and Center of Pressure Using Low-Cost Wearable Devices.

Authors:  Brandon Oubre; Spencer Lane; Skylar Holmes; Katherine Boyer; Sunghoon Ivan Lee
Journal:  IEEE Trans Biomed Eng       Date:  2022-03-18       Impact factor: 4.538

2.  Biological Hip Torque Estimation using a Robotic Hip Exoskeleton.

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

3.  Estimation of ground reaction forces and ankle moment with multiple, low-cost sensors.

Authors:  Daniel A Jacobs; Daniel P Ferris
Journal:  J Neuroeng Rehabil       Date:  2015-10-14       Impact factor: 4.262

Review 4.  Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis.

Authors:  Camille J Shanahan; Frederique M C Boonstra; L Eduardo Cofré Lizama; Myrte Strik; Bradford A Moffat; Fary Khan; Trevor J Kilpatrick; Anneke van der Walt; Mary P Galea; Scott C Kolbe
Journal:  Front Neurol       Date:  2018-02-02       Impact factor: 4.003

5.  Automatic Classification of Gait Impairments Using a Markerless 2D Video-Based System.

Authors:  Tanmay T Verlekar; Luís D Soares; Paulo L Correia
Journal:  Sensors (Basel)       Date:  2018-08-21       Impact factor: 3.576

6.  Wearables-Only Analysis of Muscle and Joint Mechanics: An EMG-Driven Approach.

Authors:  Reed D Gurchiek; Nicole Donahue; Niccolo M Fiorentino; Ryan S McGinnis
Journal:  IEEE Trans Biomed Eng       Date:  2022-01-20       Impact factor: 4.538

7.  Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications.

Authors:  Alvaro Muro-de-la-Herran; Begonya Garcia-Zapirain; Amaia Mendez-Zorrilla
Journal:  Sensors (Basel)       Date:  2014-02-19       Impact factor: 3.576

8.  Estimation of Foot Plantar Center of Pressure Trajectories with Low-Cost Instrumented Insoles Using an Individual-Specific Nonlinear Model.

Authors:  Xinyao Hu; Jun Zhao; Dongsheng Peng; Zhenglong Sun; Xingda Qu
Journal:  Sensors (Basel)       Date:  2018-02-01       Impact factor: 3.576

9.  The Design and Application of Simplified Insole-Based Prototypes with Plantar Pressure Measurement for Fast Screening of Flat-Foot.

Authors:  Wei-Chun Hsu; Tommy Sugiarto; Jun-Wen Chen; Yi-Jia Lin
Journal:  Sensors (Basel)       Date:  2018-10-25       Impact factor: 3.576

10.  Identifying predictors for postoperative clinical outcome in lumbar spinal stenosis patients using smart-shoe technology.

Authors:  Sunghoon I Lee; Andrew Campion; Alex Huang; Eunjeong Park; Jordan H Garst; Nima Jahanforouz; Marie Espinal; Tiffany Siero; Sophie Pollack; Marwa Afridi; Meelod Daneshvar; Saif Ghias; Majid Sarrafzadeh; Daniel C Lu
Journal:  J Neuroeng Rehabil       Date:  2017-07-18       Impact factor: 5.208

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