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Data Glove System Embedded With Inertial Measurement Units for Hand Function Evaluation in Stroke Patients

机译:内置惯性测量单元的数据手套系统,用于中风患者手功能评估

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This paper proposes a data glove system integrated with six-axis inertial measurement unit sensors for evaluating the hand function of patients who have suffered a stroke. The modular design of this data glove facilitates its use for stroke patients. The proposed system can use the hand's accelerations, angular velocities, and joint angles as calculated by a quaternion algorithm, to help physicians gain new insights into rehabilitation treatments. A clinical experiment was performed on 15 healthy subjects and 15 stroke patients whose Brunnstrom stages (BSs) ranged from 4 to 6. In this experiment, the participants were subjected to a grip task, thumb task, and card turning task to produce raw data and three features, namely, the average rotation speed, variation of movement completion time, and quality of movement; these features were extracted from the recorded data to form 2-D and 3-D scatter plots. These scatter plots can provide reference information and guidance to physicians who must determine the BSs of stroke patients. The proposed system demonstrated a hit rate of 70.22% on average. Therefore, this system can effectively reduce physicians' load and provide them with detailed information about hand function to help them adjust rehabilitation strategies for stroke patients.
机译:本文提出了一种集成有六轴惯性测量单元传感器的数据手套系统,用于评估中风患者的手部功能。该数据手套的模块化设计有利于中风患者使用。拟议的系统可以使用由四元数算法计算的手的加速度,角速度和关节角度,以帮助医生获得有关康复治疗的新见解。对15名健康受试者和15名Brunnstrom分期(BS)在4到6之间的中风患者进行了一项临床实验。在该实验中,参与者需要进行抓握,拇指和翻身任务,以产生原始数据并平均转速,运动完成时间的变化和运动质量这三个特征;从记录的数据中提取这些特征,以形成2D和3D散点图。这些散点图可以为必须确定中风患者的BS的医生提供参考信息和指导。所提出的系统显示出平均70.22%的命中率。因此,该系统可以有效减轻医生的负担,并为他们提供有关手功能的详细信息,以帮助他们调整中风患者的康复策略。

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