title: Low-cost wearable data acquisition for stroke rehabilitation: a proof-of-concept study on accelerometry for functional task assessment.
abstract: BACKGROUND
  An increasingly aging society and consequently rising number of patients with poststroke-related neurological dysfunctions are forcing the rehabilitation field to adapt to ever-growing demands. Although clinical reasoning within rehabilitation is dependent on patient movement performance analysis, current strategies for monitoring rehabilitation progress are based on subjective time-consuming assessment scales, not often applied. Therefore, a need exists for efficient nonsubjective monitoring methods. Wearable monitoring devices are rapidly becoming a recognized option in rehabilitation for quantitative measures. Developments in sensors, embedded technology, and smart textile are driving rehabilitation to adopt an objective, seamless, efficient, and cost-effective delivery system. This study aims to assist physiotherapists' clinical reasoning process through the incorporation of accelerometers as part of an electronic data acquisition system.
  
  
  METHODS
  A simple, low-cost, wearable device for poststroke rehabilitation progress monitoring was developed based on commercially available inertial sensors. Accelerometry data acquisition was performed for 4 first-time poststroke patients during a reach-press-return task.
  
  
  RESULTS
  Preliminary studies revealed acceleration profiles of stroke patients through which it is possible to quantitatively assess the functional movement, identify compensatory strategies, and help define proper movement.
  
  
  CONCLUSIONS
  An inertial data acquisition system was designed and developed as a low-cost option for monitoring rehabilitation. The device seeks to ease the data-gathering process by physiotherapists to complement current practices with accelerometry profiles and aid the development of quantifiable methodologies and protocols.
authors: INESC Technology and Science (INESC TEC), Porto, Portugal Faculdade de Engenharia, Universidade do Porto, Porto, Portugal.
authors: Antonio J
authors: AJ
authors: Salazar
authors: INESC Technology and Science (INESC TEC), Porto, Portugal Faculdade de Engenharia, Universidade do Porto, Porto, Portugal.
authors: Ana S
authors: AS
authors: Silva
authors: Centro de Estudos do Movimento e Actividade Humana (CEMAH), ESTSP-IPP, Vila Nova de Gaia, Portugal.
authors: Claudia
authors: C
authors: Silva
authors: Faculdade de Engenharia, Universidade do Porto, Porto, Portugal.
authors: Carla M
authors: CM
authors: Borges
authors: INESC Technology and Science (INESC TEC), Porto, Portugal Faculdade de Engenharia, Universidade do Porto, Porto, Portugal Biomechanics Laboratory (LABIOMEP), Faculdade de Desporto, Universidade do Porto, Porto, Portugal.
authors: Miguel V
authors: MV
authors: Correia
authors: Centro de Estudos do Movimento e Actividade Humana (CEMAH), ESTSP-IPP, Vila Nova de Gaia, Portugal.
authors: Rubim S
authors: RS
authors: Santos
authors: Biomechanics Laboratory (LABIOMEP), Faculdade de Desporto, Universidade do Porto, Porto, Portugal.
authors: Joao P
authors: JP
authors: Vilas-Boas
mesh_terms: D000465:Algorithms; D003020:Clothing; D001330:Electronic Data Processing / Q000295:instrumentation / Q000379:methods; D006801:Humans; D018670:Monitoring, Ambulatory; D009422:Nervous System Diseases / Q000209:etiology; D020521:Stroke / Q000150:complications*; D000071939:Stroke Rehabilitation; D013686:Telemetry / Q000295:instrumentation / Q000379:methods
keywords: accelerometry data; quantitative strategies; rehabilitation monitoring; stroke; wearable technology