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Journal Article

Citation

Carozzo S, Chisari C, Iosa M. Front. Hum. Neurosci. 2022; 16: e1078539.

Copyright

(Copyright © 2022, Frontiers Research Foundation)

DOI

10.3389/fnhum.2022.1078539

PMID

36569475

PMCID

PMC9768472

Abstract

The interest in computer-assisted quantitative gait evaluation sharply increased sharply in recent years (Figure 1). Its widespread use provides evidence of applicability to obtain objective and comparable measures supplementing clinical scales and subjective judgments.

The aim of this Research Topic was to collect papers exploring the utility of computerized gait analysis for exploring the impact of neurological diseases on gait functions. We have selected 13 articles that have been found to be of high quality for publication in this Research Topic. These papers covered different aspects related to protocols and technologies, and many different pathologies (stroke, cerebral palsy, Parkinson's disease, multiple sclerosis, spinal cord injury, Charcot Marie Tooth disease, Duchenne muscular dystrophy).

Systematic research has implemented procedures and paradigms generating a large number of potential variables for kinematic analysis; some debate on their relevance and proper selection is going on; several algorithms and equipment configurations to automatically identify the timing of gait events are being tested to comply with the clinician's needs. Whether individual markers of combinations of markers and their position on different body districts can influence the accuracy of the algorithms and therefore, the clinical and scientific findings remain unclear (Visscher et al.).

Usual gait analysis often reports the kinematics of hip, knee and ankle, but the influence of the pelvis as a biomechanical constraint during gait also needs to be deeply investigated (Favetta et al.)...


Language: en

Keywords

machine learning; computerized gait analysis; gait analysis; neurological pathologies; rehab

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