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Neural network control of wheelchairs using telemetric head movement

机译:使用遥测头运动的轮椅神经网络控制

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Powered wheelchairs are traditionally used by people with insufficient upper body strength and dexterity to operate a manual wheelchair. However, the operation of these wheelchairs can still be a difficult and stressful task. Head movement is a natural form of pointing and can be used to directly replace the joystick whilst still allowing for similar control. Through the use of artificial intelligence, a trainable wheelchair controller can be designed which provides an alternative control method with improved posture, ease of use and attractiveness. A computer simulation of this head controlled wheelchair has been successfully designed and tested. It consists of a motion detector for head motion measurement, a telemetry system for the elimination of wiring, and neural networks to provide the system with the ability to be trained for each individual operator irrespective of their disability.
机译:动力轮椅传统上,人们的上身强度不足和灵巧的人使用手动轮椅。然而,这些轮椅的操作仍然可以是一个困难和压力的任务。头部运动是一种自然形式的指向,可用于直接更换操纵杆,同时仍然允许类似的控制。通过使用人工智能,可以设计一种可训练的轮椅控制器,该控制方法提供了一种改进的姿势,易用性和吸引力的替代控制方法。这款头控制轮椅的计算机仿真已成功设计和测试。它包括用于头部运动测量的运动检测器,用于消除布线的遥测系统,以及神经网络,以提供系统的能力,该系统对于每个单独的操作员而言,无论它们的残疾如何。

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