Document Detail

Posture classification via wearable strain sensors for neurological rehabilitation.
MedLine Citation:
PMID:  17946755     Owner:  NLM     Status:  MEDLINE    
Stroke and other neurological accidents account for a wide fraction of the healthcare costs in industrialised societies. The last step in the chain of recovery from a neurological event often includes motor rehabilitation. While current motion-sensing technologies are inadequate for automated monitoring of rehabilitation exercises at home, conductive elastomers are a novel strain-sensing technology which can be embedded unobtrusively into a garment's fabric. A sensorized garment was realized to simultaneously measure the strains at multiple points of a shirt covering the thorax and upper limb. Supervised learning techniques were employed to analyse the strain measures in order to reconstruct upper-limb posture and provide real-time feedback on exercise progress.
Toni Giorgino; Federico Lorussi; Danilo De Rossi; Silvana Quaglini
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  1     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2006  
Date Detail:
Created Date:  2007-10-23     Completed Date:  2008-02-29     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  6273-6     Citation Subset:  IM    
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MeSH Terms
Computer Simulation
Equipment Design
Models, Statistical
Monitoring, Ambulatory / instrumentation*,  methods
Nervous System Diseases / rehabilitation*
Programming Languages
Thorax / pathology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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