Background/Purpose: 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.
Discussion: 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.
Physical Therapy Department (G.D.F., R.B.) and Electrical and Computer Engineering Department (S.R.E., P.H., E.S.), Clarkson University, Potsdam, New York; and Electrical and Computer Engineering Department (P.L.-M., E.S), University of Alabama at Tuscaloosa.
Correspondence: George D. Fulk, PT, PhD, Physical Therapy Department, Box 5880, Clarkson University, Potsdam, NY 13699 (firstname.lastname@example.org).
This project was supported by Award R15HD061006 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development.
This work was presented in part at the APTA Combined Sections Meeting in February 2012, World Congress of Physical Therapy meeting in June 2011, and IEEE EMBS Conference in September 2011.
The authors have no conflict of interest related to this work.
Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal's Web site (www.jnpt.org).