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A Robust Kalman Algorithm to Facilitate Human-Computer Interaction for People with Cerebral Palsy, Using a New Interface Based on Inertial Sensors

机译:使用基于惯性传感器的新接口的鲁棒卡尔曼算法,以促进脑瘫患者的人机交互

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This work aims to create an advanced human-computer interface called ENLAZA for people with cerebral palsy (CP). Although there are computer-access solutions for disabled people in general, there are few evidences from motor disabled community (e.g., CP) using these alternative interfaces. The proposed interface is based on inertial sensors in order to characterize involuntary motion in terms of time, frequency and range of motion. This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction. This paper presents a robust Kalman filter (RKF) design to facilitate fine motor control based on the previous characterization. The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten. The interface is validated with CP users who were unable to control the computer using other interfaces. The interface ENLAZA and the RKF enabled them to use the computer.
机译:这项工作旨在为脑瘫(CP)患者创建一个称为ENLAZA的高级人机界面。尽管总体上有针对残疾人的计算机访问解决方案,但很少有来自运动残疾人社区(例如CP)使用这些替代界面的证据。所提出的接口基于惯性传感器,以便根据时间,频率和运动范围来表征非自愿运动。此特征用于设计一种过滤技术,以减少非自愿运动对人机交互的影响。本文提出了一种鲁棒的卡尔曼滤波器(RKF)设计,以基于先前的特性促进精细的电机控制。该过滤器提高了鼠标指针的指向性,目标获取时间减少了十分之一。该接口已被无法使用其他接口控制计算机的CP用户验证。 ENLAZA和RKF界面使他们能够使用计算机。

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