Sorry, you need to enable JavaScript to visit this website.

facebooktwittermailshare

A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury

Abstract: 

Assistive technologies such as wheelchairs, canes, and walkers have significantly improved the mobility, function, and quality of life for individuals with spinal cord injury (SCI). In this article, we propose a framework which combines machine learning algorithms with wearable sensors to capture and track mobility in individuals with SCI. Pilot testing in two individuals without SCI indicated that four to seven features obtained from sensors worn on the body or placed on the assistive technology could successfully detect mobility and mobility modes. The classification accuracy for Naïve Bayes and Decision Tree algorithms to detect mobility from non-mobility activity varied from 87.4% to 97.6%. The classification accuracy for detecting six mobility modes within mobility ranged from 88.5% to 90.6%. The proposed
framework has the potential to assist researchers and clinicians to study complex mobility patterns of individuals with SCI and provide adaptive rehabilitation and physical activity interventions in the community.

up
0 users have voted:

Paper Details

Authors:
Amir Mohammad Amiri, Noor Shoaib, Shivayogi V. Hiremath
Submitted On:
13 November 2017 - 10:28am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Shivayogi Hiremath
Paper Code:
1461
Document Year:
2017
Cite

Document Files

MobilityFramework_0.5_PDF.pdf

(5 downloads)

Subscribe

[1] Amir Mohammad Amiri, Noor Shoaib, Shivayogi V. Hiremath, "A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2337. Accessed: Nov. 23, 2017.
@article{2337-17,
url = {http://sigport.org/2337},
author = {Amir Mohammad Amiri; Noor Shoaib; Shivayogi V. Hiremath },
publisher = {IEEE SigPort},
title = {A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury},
year = {2017} }
TY - EJOUR
T1 - A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury
AU - Amir Mohammad Amiri; Noor Shoaib; Shivayogi V. Hiremath
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2337
ER -
Amir Mohammad Amiri, Noor Shoaib, Shivayogi V. Hiremath. (2017). A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury. IEEE SigPort. http://sigport.org/2337
Amir Mohammad Amiri, Noor Shoaib, Shivayogi V. Hiremath, 2017. A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury. Available at: http://sigport.org/2337.
Amir Mohammad Amiri, Noor Shoaib, Shivayogi V. Hiremath. (2017). "A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury." Web.
1. Amir Mohammad Amiri, Noor Shoaib, Shivayogi V. Hiremath. A Framework to Enhance Assistive Technology-based Mobility Tracking in Individuals with Spinal Cord Injury [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2337