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Patient's intention detection and control for sit-stand mechanism of an assistive device for paraplegics

机译:患者的临床辅助装置施特站式机制的意图检测与控制

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Rehabilitation and assistive technologies are touching new bounds of excellence due to the advent of more user friendly human-machine interfaces (HMI) and ergonomic design principles. Among the most fundamental movements which are required in performing activities of daily living is the sit and stand motion, a device is proposed in this study which enables a patient to perform his activities of daily living (ADL) tasks by enabling them to sit, stand and move without the need of an assistant. The device, in this study, is proposed to be activated by an electroencephalogram (EEG) based intention acquisition system. The intention is acquired from eye blinks. The EEG based intention detection system converts eye blinks to respective commands after classification of eye blink signals collected using EMOTIVE (R) EPOCH+ headset. These control commands then trigger the control algorithm which then actuates and controls the system states. For the later, two control schemes namely proportional integral derivative (PID) control and sliding mode control (SMC) are tested in this study. The simulation and experimental results are given. The experimental setup consists of an offline EEG signal classification module, Simulink (R) model and the prototype of the actual device. It is concluded that SMC performs far better than PID for control of the assistive device in ensuring patient comfort during motion.
机译:由于更多用户友好的人机界面(HMI)和符合人体工程学设计原则,康复和辅助技术正在触及新的卓越界。在执行日常生活活动中所需的最基本的动作中,在本研究中提出了一种设备,使患者能够通过使他们坐下来执行他的日常生活(ADL)任务的活动并在没有助手的情况下移动。在该研究中,该装置被提出通过基于脑电图(EEG)的意图采集系统激活。意图是从眼睛眨眼获得的。基于EEG的意图检测系统转换眼睛闪烁在使用Emotive(R)epoch +耳机收集的眼睛闪烁信号的分类后闪烁到各个命令。然后,这些控制命令触发控制算法,然后执行启动和控制系统状态。对于稍后,在本研究中测试了两种控制方案即比例积分衍生物(PID)控制和滑动模式控制(SMC)。给出了模拟和实验结果。实验设置包括离线EEG信号分类模块,Simulink(R)模型和实际设备的原型。得出结论,SMC比PID更好地执行,以控制辅助装置在动作期间确保患者的舒适性。

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