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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

NE-Motion: Visual Analysis of Stroke Patients Using Motion Sensor Networks

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Author(s):
Contreras, Rodrigo Colnago [1] ; Parnandi, Avinash [2] ; Coelho, Bruno Gomes [3] ; Silva, Claudio [3] ; Schambra, Heidi [2] ; Nonato, Luis Gustavo [1]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, Dept Appl Math & Stat, BR-13566590 Sao Carlos, SP - Brazil
[2] NYU, Sch Med, New York, NY 10017 - USA
[3] NYU, Tandon Sch Engn, New York, NY 10012 - USA
Total Affiliations: 3
Document type: Journal article
Source: SENSORS; v. 21, n. 13 JUL 2021.
Web of Science Citations: 0
Abstract

A large number of stroke survivors suffer from a significant decrease in upper extremity (UE) function, requiring rehabilitation therapy to boost recovery of UE motion. Assessing the efficacy of treatment strategies is a challenging problem in this context, and is typically accomplished by observing the performance of patients during their execution of daily activities. A more detailed assessment of UE impairment can be undertaken with a clinical bedside test, the UE Fugl-Meyer Assessment, but it fails to examine compensatory movements of functioning body segments that are used to bypass impairment. In this work, we use a graph learning method to build a visualization tool tailored to support the analysis of stroke patients. Called NE-Motion, or Network Environment for Motion Capture Data Analysis, the proposed analytic tool handles a set of time series captured by motion sensors worn by patients so as to enable visual analytic resources to identify abnormalities in movement patterns. Developed in close collaboration with domain experts, NE-Motion is capable of uncovering important phenomena, such as compensation while revealing differences between stroke patients and healthy individuals. The effectiveness of NE-Motion is shown in two case studies designed to analyze particular patients and to compare groups of subjects. (AU)

FAPESP's process: 15/14358-0 - Using Symmetries for Visual Analytics of Massive Data
Grantee:Rodrigo Colnago Contreras
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC