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Smartphone-based sensory augmentation technology for home-based balance training

机译:基于智能手机的感官增强技术,用于家庭平衡训练

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This paper describes the design and development of a smartphone-based sensory augmentation technology through vibrotactile biofeedback to support home-based balance training for individuals with balance disorders. The proposed system comprises a smartphone and a 3rd party sensor/actuator module. The smartphone's application software communicates with the wearable module wirelessly via Bluetooth, provides instructions for a recommended balance training exercises (i.e., dynamic weight-shifting exercises) in clinical and/or home-based balance rehabilitation settings, and displays knowledge of results after the completion of the exercise. The 3rd party sensor/actuator module incorporates a nine degrees-of-freedom inertial measurement unit (IMU) and four vibrating actuators (tactors) for vibrotactile biofeedback. To estimate the body motion, a sensor fusion algorithm is developed based on an Extended Kalman Filter (EKF) to yield accurate and reliable orientation of the IMU. For dynamic weight-shifting exercises, a motion generation algorithm is developed by taking a user's limits of stability (LOS). Furthermore, an algorithm for continuous coding scheme to control real-time vibrotactile biofeedback is developed to provide a user with the error magnitude while he/she is performing the recommended balance training exercises. The proposed system is the first step towards developing a portable balance training technology with vibrotactile biofeedback that could eventually be used at home.
机译:本文介绍了通过触觉生物反馈基于智能手机的感觉增强技术的设计和开发,该技术可为患有平衡障碍的个体提供基于家庭的平衡训练。所提出的系统包括智能电话和第三方传感器/致动器模块。智能手机的应用程序软件通过蓝牙与可穿戴模块进行无线通信,为临床和/或家庭式平衡康复设置中的建议平衡训练练习(即动态举重锻炼)提供说明,并在完成后显示结果知识练习。第三方传感器/执行器模块包含九个自由度惯性测量单元(IMU)和四个振动执行器(触觉器),用于触觉式生物反馈。为了估计人体运动,开发了基于扩展卡尔曼滤波器(EKF)的传感器融合算法,以产生IMU的准确而可靠的方向。对于动态举重锻炼,通过考虑用户的稳定性极限(LOS)来开发运动生成算法。此外,开发了一种用于控制实时振动触觉生物反馈的连续编码方案的算法,以在用户执行推荐的平衡训练练习时为他/她提供误差幅度。拟议的系统是开发带有触觉生物反馈的便携式平衡训练技术的第一步,该技术最终可以在家庭中使用。

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