Title :
Posture Classification via Wearable Strain Sensors for Neurological Rehabilitation
Author :
Giorgino, Toni ; Lorussi, Federico ; De Rossi, Danilo ; Quaglini, Silvana
Author_Institution :
Dipt. di Inf. e Sistemistica, Pavia Univ.
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
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
Keywords :
biomedical equipment; conducting polymers; mechanoception; neurophysiology; patient rehabilitation; strain sensors; conductive elastomers; motor rehabilitation; neurological accidents; neurological rehabilitation; posture classification; real-time feedback; rehabilitation exercise; sensorized garment; stroke patients; supervised learning techniques; upper-limb postural reconstruction; wearable strain sensors; Biomedical monitoring; Capacitive sensors; Clothing; Computerized monitoring; Costs; Fabrics; Industrial accidents; Medical services; Strain measurement; Wearable sensors;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260620