A Smart Insole for Remote Gait Monitoring of Paralyzed Patients

Paralysis occurs when the nervous system is disrupted, preventing patients from making voluntary movements. The most common causes of paralysis are stroke and spinal cord injuries. Paralysis can result in a partial or complete loss of control over movement, often leading to an unsteady gait. Side falls, a severe consequence of this imbalance, frequently cause broken bones and head injuries. Real-time gait monitoring with integrated analysis could greatly improve the rehabilitation process for such patients. The proposed smart insole is designed to provide real-time and remote gait monitoring for paralyzed individuals. This innovative approach holds promise for enhancing personalized rehabilitation programs and enabling early detection of impaired movement and balance control.This study will assess various locomotion scenarios to detect potential gait impairments and early signs of balance loss. A smart insole, featuring multiple sensors precisely designed and strategically placed, is developed to measure key gait parameters. A proof-of-concept model of the insole has been created to conduct experimental tests and demonstrate its functionality in different human activities. The model includes a 3D-printed insole equipped with a nano Arduino controller and integrated gyroscopes and accelerometers embedded in the insole. Additional sensors are positioned at specific locations to measure other critical parameters. A Fiber Bragg Grating (FBG) sensor array is embedded in the insole to provide accurate, real-time detection of foot deformation, allowing for the identification of imbalances.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/metrocon62511.2024.10883913
Citations
1
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.25
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article

A Smart Insole for Remote Gait Monitoring of Paralyzed Patients

Abolghassem Zabihollah, Joe W. Priest, Haitham Abu Ghazaleh, Aubrey Eckert et al.
1 citations
Context-Aware Activity Recognition Systems
0.25
article

A Smart Insole for Remote Gait Monitoring of Paralyzed Patients

Abolghassem Zabihollah, Joe W. Priest, Haitham Abu Ghazaleh, Aubrey Eckert, Oluwaseyi Oyetunji, Austin Rain, William Feris
article en
1 citations

Abstract

Paralysis occurs when the nervous system is disrupted, preventing patients from making voluntary movements. The most common causes of paralysis are stroke and spinal cord injuries. Paralysis can result in a partial or complete loss of control over movement, often leading to an unsteady gait. Side falls, a severe consequence of this imbalance, frequently cause broken bones and head injuries. Real-time gait monitoring with integrated analysis could greatly improve the rehabilitation process for such patients. The proposed smart insole is designed to provide real-time and remote gait monitoring for paralyzed individuals. This innovative approach holds promise for enhancing personalized rehabilitation programs and enabling early detection of impaired movement and balance control.This study will assess various locomotion scenarios to detect potential gait impairments and early signs of balance loss. A smart insole, featuring multiple sensors precisely designed and strategically placed, is developed to measure key gait parameters. A proof-of-concept model of the insole has been created to conduct experimental tests and demonstrate its functionality in different human activities. The model includes a 3D-printed insole equipped with a nano Arduino controller and integrated gyroscopes and accelerometers embedded in the insole. Additional sensors are positioned at specific locations to measure other critical parameters. A Fiber Bragg Grating (FBG) sensor array is embedded in the insole to provide accurate, real-time detection of foot deformation, allowing for the identification of imbalances.

Tarleton State University (US)
Openalex Percentile: Top 42%
Context-Aware Activity Recognition Systems
0.25
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