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Model Development of Lower Body Exercise for the Rehabilitation of Level 6 Filipino Post-Stroke Patients Using Microsoft Kinect Sensor V2

机译:使用Microsoft Kinect Sensor V2对6级菲律宾中风后患者进行康复的下半身运动模型开发

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This study focused on developing models for three different lower body exercises that can be used in rehabilitation of level 6 Filipino post-stroke patients with left hemiparesis. Level 6 was chosen since this is the stage where muscle coordination is improved, and motor control is almost fully restored, requiring only minimal assistance. In addition, this study aimed to determine the relationship of the demographic information of users in relation to the recognition of correct/incorrect exercise and discover significant patterns that reflect the relationship between human body frames and execution of exercise. Decision Tree classifier was used on the training sets from the data collected from 48 non-stroke participants with varying demographics and body frames. Overall results showed that demographics have relationship with recognition of correct and incorrect exercise movements. Also, body frames in terms of Body Mass Index (BMI) was significant in recognition.
机译:这项研究的重点是为三种不同的下半身运动开发模型,这些模型可用于6级菲律宾卒中后左偏瘫患者的康复。选择6级是因为这是改善肌肉协调性,几乎完全恢复运动控制的阶段,只需要很少的帮助。此外,本研究旨在确定与正确/不正确运动的识别有关的用户人口统计信息的关系,并发现反映人体框架与运动执行之间关系的重要模式。在训练集上使用了决策树分类器,该分类树是从48名不同人群和身体框架的非卒中参与者收集的数据中获得的。总体结果表明,人口统计信息与正确和不正确的运动动作的识别有关。同样,就身体质量指数(BMI)而言,身体框架也很重要。

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