title: Identifying activity levels and steps of people with stroke using a novel shoe-based sensor.
abstract: OBJECTIVE
  Advances in sensor technologies provide a method to accurately assess activity levels of people with stroke in their community. This information could be used to determine the effectiveness of rehabilitation interventions as well as provide behavior-enhancing feedback. The purpose of this study was to assess the accuracy of a novel shoe-based sensor system (SmartShoe) to identify different functional postures and steps in people with stroke. The SmartShoe system consists of five force-sensitive resistors built into a flexible insole and an accelerometer on the back of the shoe. Pressure and acceleration data are sent via Bluetooth to a smart phone.
  
  
  METHODS
  Participants with stroke wore the SmartShoe while they performed activities of daily living (ADLs) in sitting, standing, and walking positions. Data from four participants were used to develop a multilayer perceptron artificial neural network (ANN) to identify sitting, standing, and walking. A signal-processing algorithm used data from the pressure sensors to estimate the number of steps taken while walking. The accuracy, precision, and recall of the ANN for identifying the three functional postures were calculated with data from a different set of participants. Agreement between steps identified by SmartShoe and actual steps taken was analyzed by the Bland Altman method.
  
  
  RESULTS
  The SmartShoe was able to accurately identify sitting, standing, and walking. Accuracy, precision, and recall were all greater than 95%. The mean difference between steps identified by SmartShoe and actual steps was less than one step.
  
  
  CONCLUSIONS
  The SmartShoe was able to accurately identify different functional postures, using a unique combination of pressure and acceleration data, of people with stroke as they performed different ADLs. There was a strong level of agreement between actual steps taken and steps identified by the SmartShoe. Further study is needed to determine whether the SmartShoe could be used to provide valid information on activity levels of people with stroke while they go about their daily lives in their home and community.
authors.affiliation: Physical Therapy Department, Clarkson University, Potsdam, NY 13699, USA. gfulk@clarkson.edu
authors.forename: George D
authors.initials: GD
authors.lastname: Fulk
authors.forename: S Ryan
authors.initials: SR
authors.lastname: Edgar
authors.forename: Rebecca
authors.initials: R
authors.lastname: Bierwirth
authors.forename: Phil
authors.initials: P
authors.lastname: Hart
authors.forename: Paulo
authors.initials: P
authors.lastname: Lopez-Meyer
authors.forename: Edward
authors.initials: E
authors.lastname: Sazonov
mesh_terms: D000203:Activities of Daily Living; D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000592:standards; D016571:Neural Networks, Computer; D011187:Posture / Q000502:physiology; D012775:Shoes; D020521:Stroke / Q000175:diagnosis*; D016138:Walking / Q000502:physiology