Add to ORKGThis paper presents a real-time system that guides stroke patients during upper extremity rehabilitation. The system automatically modifies exercise parameters to account for the specific needs and abilities of different individuals. We describe a partially observable Markov decision process (POMDP) model of a rehabilitation exercise that can capture this form of customization. The system will be evaluated in user trials during summer 2008 in Toronto, Canada
Stroke rehabilitation seeks to accelerate motor recovery by training functional activities, but may ...
Purpose: Post-stroke survivors report that feedback helps to increase training motivation. A wearabl...
This paper presents a novel rehabilitative platform designed to provide a functional upper-limb task...
Stroke is the primary cause of adult disability. To support this large population in recovery, robo...
Abstract—This paper presents an automated system for a rehabilitation robotic device that guides str...
Abstract Background Stroke is the primary cause of adult disability. To support this large populatio...
We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that reli...
We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that reli...
This paper presents a Partially Observable Markov Decision Process(POMDP) model for action planning ...
Abstract Background Few existing interactive rehabilitation systems can effectively communicate mult...
Stroke is one of the leading causes of upper extremity disability around the world. Whenever a strok...
Background The motivation of patients during robot-assisted rehabilitation after neurological disor...
This work investigates how Hidden Semi-Markov Model (HSMM) can be used to monitor and evaluate physi...
Researchers at the Centre for Studies in Aging and at Simon Fraser University are developing ubiquit...
Post-stroke survivors report that feedback helps to increase training motivation. A wearable system ...
Stroke rehabilitation seeks to accelerate motor recovery by training functional activities, but may ...
Purpose: Post-stroke survivors report that feedback helps to increase training motivation. A wearabl...
This paper presents a novel rehabilitative platform designed to provide a functional upper-limb task...
Stroke is the primary cause of adult disability. To support this large population in recovery, robo...
Abstract—This paper presents an automated system for a rehabilitation robotic device that guides str...
Abstract Background Stroke is the primary cause of adult disability. To support this large populatio...
We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that reli...
We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that reli...
This paper presents a Partially Observable Markov Decision Process(POMDP) model for action planning ...
Abstract Background Few existing interactive rehabilitation systems can effectively communicate mult...
Stroke is one of the leading causes of upper extremity disability around the world. Whenever a strok...
Background The motivation of patients during robot-assisted rehabilitation after neurological disor...
This work investigates how Hidden Semi-Markov Model (HSMM) can be used to monitor and evaluate physi...
Researchers at the Centre for Studies in Aging and at Simon Fraser University are developing ubiquit...
Post-stroke survivors report that feedback helps to increase training motivation. A wearable system ...
Stroke rehabilitation seeks to accelerate motor recovery by training functional activities, but may ...
Purpose: Post-stroke survivors report that feedback helps to increase training motivation. A wearabl...
This paper presents a novel rehabilitative platform designed to provide a functional upper-limb task...