Evidence map›Paper›PMID 39695070›Full record

ArticleMedical & biological engineering & computing2025

Understanding the implication of task conditions on asymmetry in gait of post-stroke individuals using an Integrated Wearable System.

Shashi Ranjan, Priya Darji, Shraddha J Diwan, Uttama Lahiri

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Article in Medical & biological engineering & computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Shashi RanjanDepartment of Electrical Engineering, Indian Institute of Technology, Gandhinagar, India. shashi.r@iitgn.ac.in.ORCID http://orcid.org/0000-0002-2231-804X
Priya DarjiDepartment of Physiotherapy, S.B.B College of Physiotherapy, Ahmedabad, India.
Shraddha J DiwanClinical Neuro-Physiotherapist and Lecturer Department of Physiotherapy, S.B.B College of Physiotherapy, Ahmedabad, India.
Uttama LahiriDepartment of Electrical Engineering, Indian Institute of Technology, Gandhinagar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hemiplegic individuals often demonstrate gait abnormality causing asymmetry in lower-limb muscle activation-related (implicit) and gait-related (explicit) measures (offering complementary information on one's gait) while walking. Added to hemiplegia, such asymmetry can be aggravated while walking under varying task conditions, namely, walking without speaking (single task), walking while counting backwards (dual task), and walking while holding an object and counting backwards (multiple task). This emphasizes the need to quantify the extent of aggravated implication of multiple-task and dual-task on gait asymmetry compared to single task. Here, we used Integrated Wearable System and carried out a study with a group of age-matched hemiplegic (Grp_S) and healthy (Grp_H) individuals to understand the potential of our system in quantifying asymmetry in explicit and implicit measures of gait, implication of hemiplegic condition and varying task conditions on these asymmetry measures along with their clinical relevance. Results showed the potential of our system in quantifying asymmetry in both explicit and implicit measures of gait, and these measures were statistically higher (p-value < 0.05) in Grp_S than Grp_H irrespective of the task conditions. Also, for Grp_S, these asymmetry measures became more pronounced as task demand increased, and again, these measures have shown a correlation with their risk of fall specifically during more attention-demanding tasks that could be clinically relevant.

Indexed as

GaitGait Disorders, NeurologicStrokeWearable Electronic DevicesAdultAgedFemaleHemiplegiaHumansMaleMiddle AgedStroke RehabilitationTask Performance and AnalysisWalkingAsymmetryGait disorderStrokeTask conditionsWearable system

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.