Title |
Recent developments in biofeedback for neuromotor rehabilitation
|
---|---|
Published in |
Journal of NeuroEngineering and Rehabilitation, June 2006
|
DOI | 10.1186/1743-0003-3-11 |
Pubmed ID | |
Authors |
He Huang, Steven L Wolf, Jiping He |
Abstract |
The original use of biofeedback to train single muscle activity in static positions or movement unrelated to function did not correlate well to motor function improvements in patients with central nervous system injuries. The concept of task-oriented repetitive training suggests that biofeedback therapy should be delivered during functionally related dynamic movement to optimize motor function improvement. Current, advanced technologies facilitate the design of novel biofeedback systems that possess diverse parameters, advanced cue display, and sophisticated control systems for use in task-oriented biofeedback. In light of these advancements, this article: (1) reviews early biofeedback studies and their conclusions; (2) presents recent developments in biofeedback technologies and their applications to task-oriented biofeedback interventions; and (3) discusses considerations regarding the therapeutic system design and the clinical application of task-oriented biofeedback therapy. This review should provide a framework to further broaden the application of task-oriented biofeedback therapy in neuromotor rehabilitation. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | <1% |
United States | 3 | <1% |
Switzerland | 3 | <1% |
France | 3 | <1% |
Italy | 2 | <1% |
Austria | 2 | <1% |
Germany | 2 | <1% |
Portugal | 1 | <1% |
Brazil | 1 | <1% |
Other | 8 | 2% |
Unknown | 413 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 105 | 24% |
Student > Master | 66 | 15% |
Researcher | 62 | 14% |
Student > Bachelor | 34 | 8% |
Student > Doctoral Student | 28 | 6% |
Other | 89 | 20% |
Unknown | 58 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 158 | 36% |
Medicine and Dentistry | 65 | 15% |
Neuroscience | 27 | 6% |
Nursing and Health Professions | 22 | 5% |
Computer Science | 21 | 5% |
Other | 65 | 15% |
Unknown | 84 | 19% |