基于机器学习的支撑支架膝关节肌肉骨骼工效学分析

Mythili C, P. P
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引用次数: 0

摘要

肌肉骨骼问题包括从疼痛到行动能力问题。及时诊断肌肉骨骼疾病对预防和治疗具有重要意义。耐用品的人体工程学分析一直是一项费时费力的复杂工作。在本研究中,为了了解参考健康人群和受影响人群的基本姿势舒适性,对带外支撑支架的膝关节进行了基于机器学习的人体工程学分析。该研究对不同年龄组的研究人群进行膝关节三维扫描,每组包括健康参考人群和膝关节问题患病率人群。根据诊断出的活动障碍的严重程度,将疾病患病率分为低、中、极端病例。以特定姿势存在的时间也会被记录下来。在用户重要的压力接触处进行基于压电的压力测量。将数据输入MATLAB机器学习工具对系统进行训练,获得最佳训练结果后进行测试和验证,获得符合人体工程学舒适性的性能特征。的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning based Musculoskeletal Ergonomic Analysis of Knee Joint with Support Brace
Musculoskeletal issues ranges from pains to mobility issues. Timely diagnosis of musculoskeletal disorders are important in prevention and treatment. Analysis of ergonomics of consumer durables fitting to human are always a complex task associated with time consuming and laborious work. In this present work, a machine learning based ergonomic analysis on knee with external support brace was carried out to understand the user comport of basic postures among a reference healthy and affected population. The study involves 3D scanning of knee joint of study population grouped in to different age groups and each group containing both healthy reference and population with prevalence of knee joint issues. The disease prevalence was categorized into low, medium and extreme cases based on the severity of mobility issues diagnosed. Duration of present in a particular posture is also recorded. Piezoelectric based pressure measurements carried out at important pressure contacts of the user. The data were feed in to MATLAB machine learning tool to train the system, after obtaining optimum training outcome testing and validation were performed to obtain the performance characteristics in terms of ergonomic comfort. The
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