Using Wearable Sensors to Measure Motor Abilities following Stroke

Authors:
Todd Hester;Richard Hughes;Delsey M. Sherrill;Bethany Knorr;Metin Akay;Joel Stein;Paolo Bonato
Affiliations:
Spaulding Rehabilitation Hospital, Boston MA;Spaulding Rehabilitation Hospital, Boston MA;Spaulding Rehabilitation Hospital, Boston MA;Dartmouth College, Hanover NH;Harvard-MIT Division of Health Science and Technology, Cambridge MA;Spaulding Rehabilitation Hospital, Boston MA;Harvard-MIT Division of Health Science and Technology, Cambridge MA
Venue:
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
Year:
2006

Citing 0
Cited 6

Wearable wireless sensor network to assess clinical status in patients with neurological disorders

Proceedings of the 6th international conference on Information processing in sensor networks
Resource discovery in activity-based sensor networks

Mobile Networks and Applications
Wireless device for people affected by neurodegenerative diseases

CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Mercury: a wearable sensor network platform for high-fidelity motion analysis

Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Stroke Therapy through Motion-Based Games: A Case Study

ACM Transactions on Accessible Computing (TACCESS)
Tool use as gesture: new challenges for maintenance and rehabilitation

BCS '10 Proceedings of the 24th BCS Interaction Specialist Group Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

Motor abilities of stroke survivors are often severely affected. Post-stroke rehabilitation is guided by the use of clinical assessments of motor abilities. Clinical assessment scores can be predicted by models based on features extracted from the wearable sensor data. Wearable sensors would allow monitoring of subjects in the home and provide accurate assessments to guide the rehabilitation process. We propose the use of a wearable sensor system to assess the motor abilities of stroke victims. Preliminary results from twelve subjects show the ability of this system to predict clinical scores of motor abilities.