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基于加速度计的计算机访问设备中的光标点击模式。

Cursor Click Modality in an Accelerometer-Based Computer Access Device.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2020 Jul;28(7):1566-1572. doi: 10.1109/TNSRE.2020.2996820.

DOI:10.1109/TNSRE.2020.2996820
PMID:32634095
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7392159/
Abstract

The purpose of this study is to investigate the effects of different cursor click modalities in an alternative computer access device using accelerometry from head tilt to control cursor movement. Eighteen healthy adults performed a target acquisition task using the device with five different cursor click modalities, while maintaining cursor movement control via accelerometry. Three dwell-based click modalities with dwell times of 0.5 s, 1.0 s, and 1.5 s were tested. Two surface electromyography-based click modalities - with the sensor placed next to the eye for a blink and above the eyebrow for a brow raise - were tested. Performance was evaluated using metrics of target selection accuracy, path efficiency, target selection time, and user effort. Surface electromyography-based click modalities were as fast as the shortest dwell time and as accurate as the longest dwell time, and also minimized user effort. Three of the four performance metrics were not affected by sensor location. Future studies will investigate if these results are similar in individuals with neuromuscular disorders.

摘要

本研究旨在探讨使用加速度计从头部倾斜来控制光标移动的替代计算机接入设备中不同光标点击方式的效果。十八名健康成年人使用该设备进行目标获取任务,同时使用加速度计保持光标移动控制,使用五种不同的光标点击方式。测试了三种基于停留时间的点击方式,停留时间分别为 0.5 秒、1.0 秒和 1.5 秒。还测试了两种基于表面肌电图的点击方式 - 将传感器放置在眼睛旁边用于眨眼,以及放置在眉毛上方用于挑眉。使用目标选择准确性、路径效率、目标选择时间和用户努力的指标来评估性能。基于表面肌电图的点击方式与最短停留时间一样快,与最长停留时间一样准确,并且还最大限度地减少了用户的努力。四个性能指标中的三个不受传感器位置的影响。未来的研究将调查这些结果在患有神经肌肉疾病的个体中是否相似。

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本文引用的文献

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Integrated Head-Tilt and Electromyographic Cursor Control.头倾与肌电光标综合控制。
IEEE Trans Neural Syst Rehabil Eng. 2020 Jun;28(6):1442-1451. doi: 10.1109/TNSRE.2020.2987144. Epub 2020 Apr 13.
2
Diagnosis and management of Guillain-Barré syndrome in ten steps.吉兰-巴雷综合征的诊断和管理十步骤。
Nat Rev Neurol. 2019 Nov;15(11):671-683. doi: 10.1038/s41582-019-0250-9. Epub 2019 Sep 20.
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Prediction of Optimal Facial Electromyographic Sensor Configurations for Human-Machine Interface Control.预测用于人机界面控制的最佳面部肌电传感器配置。
IEEE Trans Neural Syst Rehabil Eng. 2018 Aug;26(8):1566-1576. doi: 10.1109/TNSRE.2018.2849202. Epub 2018 Jun 20.
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Reever control: A biosignal controlled interface.Reever控制:一种生物信号控制接口。
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:706-709. doi: 10.1109/EMBC.2017.8036922.
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Eye Tracking and Head Movement Detection: A State-of-Art Survey.眼动追踪和头部运动检测:最新研究综述。
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Comparison of eye tracking, electrooculography and an auditory brain-computer interface for binary communication: a case study with a participant in the locked-in state.用于二元通信的眼动追踪、眼电图和听觉脑机接口的比较:一项针对闭锁综合征患者的案例研究
J Neuroeng Rehabil. 2015 Sep 4;12:76. doi: 10.1186/s12984-015-0071-z.
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Evaluation of head orientation and neck muscle EMG signals as three-dimensional command sources.将头部方向和颈部肌肉肌电信号评估为三维指令源。
J Neuroeng Rehabil. 2015 Mar 5;12:25. doi: 10.1186/s12984-015-0016-6.
8
Discrete Versus Continuous Mapping of Facial Electromyography for Human-Machine Interface Control: Performance and Training Effects.用于人机接口控制的面部肌电图离散映射与连续映射:性能及训练效果
IEEE Trans Neural Syst Rehabil Eng. 2015 Jul;23(4):572-80. doi: 10.1109/TNSRE.2015.2391054. Epub 2015 Jan 20.
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Phys Med Rehabil Clin N Am. 2012 Aug;23(3):495-563. doi: 10.1016/j.pmr.2012.06.011.
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Surface electromyography for speech and swallowing systems: measurement, analysis, and interpretation.表面肌电图在言语和吞咽系统中的应用:测量、分析和解读。
J Speech Lang Hear Res. 2012 Aug;55(4):1232-46. doi: 10.1044/1092-4388(2011/11-0214). Epub 2012 Jan 9.