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Development of a low-cost motion capture system for identifying alterations in human gait balance. Application to shoulder pathologies.

par Bernal Castillo, Fredy
Président du jury Van Cant, Joachim
Promoteur Feipel, Véronique ;Plaza Torres, Mauricio
Publication Non publié, 2024-12-12

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Résumé :

Human movements are classified as a coordinated set of interactions within the musculoskeletal system. Injuries or damages occurring in any component of this system lead to a deterioration of balance and stability, or alterations in the mechanical behavior of the overall system, consequently disrupting movements not directly linked. Currently, shoulder pathologies occur in Colombia a rate of 78 per thousand inhabitants.Additionally, according to FASECOLDA (Federacion de Aseguradores Colombianos), they account for 28% of work-related diagnoses, with the most common being rotator cuff syndrome, constituting 35% of these cases. The purpose of this study was to design and implement a portable, low-cost system that, through motion capture, can identify alterations in the gait cycle. An application of this system on detecting potential changes in gait balance caused by rotator cuff syndrome is shown. The advantage of this technology lies in the utilization of Microsoft Kinect V2 as the foundational system. The motion capture and analysis system, "Kincapsys," was developed using MATLAB as the development environment. This combination offers the robust capabilities of Kinect V2 for motion tracking, complemented by the flexibility and computational power provided by the MATLAB environment, resulting in a comprehensive and tailored solution for motion capture and analysis. The implemented system demonstrated a mean squared error between measurements of less than 3.5°.With the completed motion capture and analysis system (Kincapsys) development in this research, measurements were taken from 10 volunteers who had been experiencing rotator cuff syndrome for over 18 months and had no previous surgeries or other orthopedic alterations. These measurements were compared with an 8-camera optoelectronic capture system, the STT 3DMA system. The results revealed that the goniometric movements performed during the gait study did not exhibit significant differences between the pathological and non-pathological sides. This comparison was carried out using a 1-dimensional Statistical Parametric Mapping method and the results were corroborated through a Repeated Measures ANOVA analysis. Additionally, spatial, and temporal parameters of gait were compared, revealing a difference of 4.1% in step length between the pathological and non-pathological sides in a proportional comparison between sides. Other spatial and temporal parameters did not show discernible differences. With the results obtained from the study, it is not possible to confirm the hypothesis proposed, as no significant differences in gait balance were found between pathological and non-pathological sides.