Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method

Abstract

Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results.

Document Details

• Document Type: Pub Defense Publication
• Publication Date: Nov 05, 2020
• Source ID: 10.1177/1545968320962483

Entities

People

• Alexander W. Dromerick
• Elaine M. Bochniewicz
• Jessica Barth
• Lin-ching Chang
• Liqi Shu
• Peter S Lum
• Tan Tran

Organizations

• Brown University
• Georgetown University
• National Rehabilitation Hospital
• The Catholic University of America
• United States Army Medical Research and Development Command
• United States Department of Health and Human Services
• United States Department of Veterans Affairs

Tags

Readers

• Rehabilitation and Prosthetic Care for Military Service Members and Veterans with Limb Loss or Disability.
• Sensor Fusion and Tracking Systems.
• Software Engineering.

Technology Areas

• AI & ML
• AI & ML - Bayesian Inference