Possibilities of using biomechanical human motion capture systems in medical rehabilitation (review)

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Abstract

Biomechanical motion capture is the most accurate non-contact instrumental method of studying human locomotion and is increasingly being used in the medical rehabilitation of patients with various diseases. Human motion capture systems are promising tools for clinical use to assess and control the correct execution of movements, as well as to identify injury risk factors.

Currently, human motion capture systems are mainly used only in scientific research. The development and implementation of biomechanical motion capture systems in clinical practice can help doctors determine the best solution when planning medical rehabilitation and, thereby, reduce the recovery time of patients.

This review aims to present up-to-date data on motion capture techniques and features of their application in the medical rehabilitation of patients with diseases of the nervous system. The review provides a brief overview of the existing technologies for the study of locomotor functions. The principles of operation, advantages and disadvantages of optoelectronic, electromagnetic, inertial and ultrasonic measuring systems are presented. The review describes in detail the possibilities of biomechanical motion capture in conducting a personalized diagnostic process, planning and evaluating the results of medical rehabilitation in patients with stroke, Parkinson's disease, cerebral palsy, spinal cord injury and multiple sclerosis.

The search was conducted in the databases eLibrary, PubMed, Scopus, Web of Science and Google Academy (Google Scholar). The review includes studies in which motion capture systems were used and spatial-temporal, kinematic, kinetic and electromyographic parameters were analyzed.

About the authors

Gennadii E. Sheiko

Privolzhsky Research Medical University

Author for correspondence.
Email: sheikogennadii@yandex.ru
ORCID iD: 0000-0003-0402-7430
SPIN-code: 8575-1319

MD, Cand. Sci. (Med.)

Russian Federation, Nizhny Novgorod

Anna N. Belova

Privolzhsky Research Medical University

Email: anbelova@mail.ru
ORCID iD: 0000-0001-9719-6772
SPIN-code: 3084-3096

MD, Dr. Sci. (Med.), Professor

Russian Federation, Nizhny Novgorod

Natalia N. Rukina

Privolzhsky Research Medical University

Email: rukinann@mail.ru
ORCID iD: 0000-0002-0719-3402
SPIN-code: 5028-4577

MD, Cand. Sci. (Med.), Senior Research Associate

Russian Federation, Nizhny Novgorod

Nadezhda L. Korotkova

Privolzhsky Research Medical University; The First Sechenov Moscow State Medical University (Sechenov University)

Email: korotkova-home@mail.ru
ORCID iD: 0000-0001-7812-1433
SPIN-code: 8709-8397

MD, Dr. Sci. (Med.), Professor

Russian Federation, Nizhny Novgorod; Moscow

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Supplementary files

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2. Fig. 1. The position of markers and a three-dimensional human model built by the Simi Motion program (Germany).

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3. Fig. 2. Active (left) and passive (right) markers of the Simi Motion video analysis system (Germany).

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4. Fig. 3. An example of the placement of active markers of the Simi Motion video analysis system (Germany) on the subject.

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5. Fig. 4. Video analysis of walking with an assessment of movements in the left lower limb using active markers, built by the Simi Motion program (Germany).

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Copyright (c) 2022 Sheiko G.E., Belova A.N., Rukina N.N., Korotkova N.L.

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