Machine Learning Based Intelligent Insole for Gait Analysis

This research introduces a machine learning based approach that not only monitors the walking pattern but also generates electricity from walking .Subtle changes in the walking pattern may indicate neurological conditions, recovery progress after injury etc. Traditional gait analysis are subjected to hospital visits where the patients rely on expensive lab equipments. Equipped with pressure sensors, accelerometers and piezoelectric materials the insole collects data through real time gait monitoring while producing enough power to support its own operation. Thus through the combination of self-sustainability and gait analysis, this system has the potential to make healthcare monitoring more accessible and effective.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-02-04
DOI
https://doi.org/10.1051/itmconf/20268203005/pdf
Primary Topic
Gait Recognition and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning Based Intelligent Insole for Gait Analysis

S. Tephillah, Saajini G, Shinie kiruba E
Springer Link (Chiba Institute of Technology)
Gait Recognition and Analysis
article

Machine Learning Based Intelligent Insole for Gait Analysis

S. Tephillah, Saajini G, Shinie kiruba E
article en

Abstract

This research introduces a machine learning based approach that not only monitors the walking pattern but also generates electricity from walking .Subtle changes in the walking pattern may indicate neurological conditions, recovery progress after injury etc. Traditional gait analysis are subjected to hospital visits where the patients rely on expensive lab equipments. Equipped with pressure sensors, accelerometers and piezoelectric materials the insole collects data through real time gait monitoring while producing enough power to support its own operation. Thus through the combination of self-sustainability and gait analysis, this system has the potential to make healthcare monitoring more accessible and effective.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 66%
Gait Recognition and Analysis
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