• DocumentCode
    3136683
  • 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.
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    6273
  • Lastpage
    6276
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260620
  • Filename
    4463243