Identifying Activity Levels and Steps of People With Stroke Using a Novel Shoe-Based Sensor

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dc.contributor.authorFulk, George D.
dc.contributor.authorEdgar, S. Ryan
dc.contributor.authorBierwirth, Rebecca
dc.contributor.authorHart, Phil
dc.contributor.authorLopez-Meyer, Paulo
dc.contributor.authorSazonov, Edward
dc.contributor.otherClarkson University
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2023-09-28T22:02:24Z
dc.date.available2023-09-28T22:02:24Z
dc.date.issued2012
dc.description.abstractBackground/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 SmartShoewas 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.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationFulk, G. D., Edgar, S. R., Bierwirth, R., Hart, P., Lopez-Meyer, P., & Sazonov, E. (2012). Identifying Activity Levels and Steps of People With Stroke Using a Novel Shoe-Based Sensor. In Journal of Neurologic Physical Therapy (Vol. 36, Issue 2, pp. 100–107). Ovid Technologies (Wolters Kluwer Health). https://doi.org/10.1097/npt.0b013e318256370c
dc.identifier.doi10.1097/NPT.0b013e318256370c
dc.identifier.orcidhttps://orcid.org/0000-0001-7792-4234
dc.identifier.orcidhttps://orcid.org/0000-0001-9139-2238
dc.identifier.urihttps://ir.ua.edu/handle/123456789/12132
dc.languageEnglish
dc.language.isoen_US
dc.publisherLippincott Williams & Wilkins
dc.subjectPHYSICAL-ACTIVITY
dc.subjectGAIT ASSESSMENT
dc.subjectWEIGHT-LOSS
dc.subjectACCELEROMETRY
dc.subjectREHABILITATION
dc.subjectRELIABILITY
dc.subjectINTERVENTION
dc.subjectTECHNOLOGY
dc.subjectVALIDATION
dc.subjectPEDOMETERS
dc.subjectClinical Neurology
dc.subjectRehabilitation
dc.titleIdentifying Activity Levels and Steps of People With Stroke Using a Novel Shoe-Based Sensoren_US
dc.typeArticle
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