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基于眼电图的人机界面控制严重脊髓损伤患者的智能家居环境

An EOG-Based Human-Machine Interface to Control a Smart Home Environment for Patients With Severe Spinal Cord Injuries.

出版信息

IEEE Trans Biomed Eng. 2019 Jan;66(1):89-100. doi: 10.1109/TBME.2018.2834555. Epub 2018 May 9.

Abstract

OBJECTIVE

This paper presents an asyn-chronous electrooculography (EOG)-based human-machine interface (HMI) for smart home environmental control with the purpose of providing daily assistance for severe spinal cord injury (SCI) patients.

METHODS

The proposed HMI allows users to interact with a smart home environment through eye blinking. Specifically, several buttons, each corresponding to a control command, randomly flash on a graphical user interface. Each flash of the buttons functions as a visual cue for the user to blink. To issue a control command, the user can blink synchronously with the flashes of the corresponding button. Through detecting blinks based on the recorded EOG signal, the target button and its corresponding control command are determined. Seven SCI patients participated in an online experiment, during which the patients were required to control a smart home environment including household electrical appliances, an intelligent wheelchair, as well as a nursing bed via the proposed HMI.

RESULTS

The average false operation ratio in the control state was 4.1%, whereas during the idle state, no false operations occurred.

CONCLUSION

All SCI patients were able to control the smart home environment using the proposed EOG-based HMI with satisfactory performance in terms of the false operation ratio in both the control and the idle states.

SIGNIFICANCE

The proposed HMI offers a simple and effective approach for patients with severe SCIs to control a smart home environment. Therefore, it is promising to assist severe SCI patients in their daily lives.

摘要

目的

本文提出了一种基于异步眼电图(EOG)的人机界面(HMI),用于智能家居环境控制,旨在为严重脊髓损伤(SCI)患者提供日常帮助。

方法

所提出的 HMI 允许用户通过眨眼与智能家居环境进行交互。具体来说,几个按钮,每个按钮对应一个控制命令,随机在图形用户界面上闪烁。按钮的每次闪烁都作为用户眨眼的视觉提示。要发出控制命令,用户可以与相应按钮的闪烁同步眨眼。通过基于记录的 EOG 信号检测眨眼,确定目标按钮及其对应的控制命令。七名 SCI 患者参加了在线实验,要求他们通过所提出的 HMI 控制智能家居环境,包括家用电器、智能轮椅和护理床。

结果

在控制状态下,平均误操作率为 4.1%,而在空闲状态下,没有误操作发生。

结论

所有 SCI 患者都能够使用基于 EOG 的提出的 HMI 控制智能家居环境,在控制和空闲状态下的误操作率方面都表现出令人满意的性能。

意义

所提出的 HMI 为严重 SCI 患者提供了一种简单有效的方法来控制智能家居环境,因此有望帮助严重 SCI 患者的日常生活。

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