利用 FNIRS 和腕部振动器生物反馈检测心理压力并提高绩效

Anita Beigzadeh, Vahid Yazdnian, Kamaledin Setarehdan
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引用次数: 0

摘要

任何人在其日常生活活动中都会经历不同种类和不同程度的精神压力,这些压力会对其工作表现产生破坏性影响。因此,找到一种系统的压力管理和绩效提升方法至关重要。本文介绍了一种全面的便携式实时生物反馈系统,旨在促进压力管理,进而提高绩效。为此,我们开发了实时脑信号采集设备、无线振动生物反馈设备和用于压力水平分类的软件定义程序。更重要的是,整个系统的设计通过将系统的所有重要部分连接在一起,最大限度地减少了时间延迟。我们为在线压力检测应用介绍了不同的信号处理和特征提取技术。此外,我们还在受控实验装置中对 20 名参与者进行了生物反馈系统完整性测试。实验评估结果显示,系统性能良好,研究结果表明,我们的系统能够帮助参与者将压力水平降低 55%,并将准确率提高 24.5%。通过观察可以得出结论,所有关于压力管理和通过奖励学习提高绩效的基本前提都是有效的。
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Mental Stress Detection and Performance Enhancement Using FNIRS and Wrist Vibrator Biofeedback
Any person in his/her daily life activities experiences different kinds and various amounts of mental stress which has a destructive effect on their performance. Therefore, it is crucial to come up with a systematic way of stress management and performance enhancement. This paper presents a comprehensive portable and real-time biofeedback system that aims at boosting stress management and consequently performance enhancement. For this purpose, a real-time brain signal acquisition device, a wireless vibration biofeedback device, and a software-defined program for stress level classification have been developed. More importantly, the entire system has been designed to present minimum time delay by propitiously bridging all the essential parts of the system together. We have presented different signal processing and feature extraction techniques for an online stress detection application. Accordingly, by testing the stress classification section of the system, an accuracy of 83% and a recall detecting the true mental stress level of 92% was achieved. Moreover, the biofeedback system as integrity has been tested on 20 participants in the controlled experimental setup. Experiment evaluations show promising results of system performances, and the findings reveal that our system is able to help the participants reduce their stress level by 55% and increase their accuracy by 24.5%. It can be concluded from the observations that all primary premises on stress management and performance enhancement through reward learning are valid as well.
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