Mental Health Prediction Using Artificial Intelligence- Machine Learning: Pain and Stress Detection Using Wearable Sensors and Devices—A Review

YMER Digital Pub Date : 2022-08-12 DOI:10.37896/ymer21.08/45
Selvia AM AMAlANATHAN, Abdulaziz Asiri, Amer Al Ali
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Abstract

Pain is a subjective feeling; it is a sensation that every human being must have experienced all their life. Yet, its mechanism and the way to immune to it is still a question to be answered. This re- view presents the mechanism and correlation of pain and stress, their assessment and detection approach with medical devices and wearable sensors. Various physiological signals (i.e., heart activity, brain activity, muscle activity, electrodermal activity, respiratory, blood volume pulse, skin tempera- ture) and behavioral signals are organized for wearables sensors detection. By reviewing the wearable sensors used in the healthcare domain, we hope to find a way for wearable healthcare-monitoring system to be applied on pain and stress detection. Since pain leads to multiple consequences or symptoms such as muscle tension and depression that are stress related, there is a chance to find a new approach for chronic pain detection using daily life sensors or devices. Then by integrating modern computing techniques, there is a chance to handle pain and stress management issue. Keywords: Mental health, machine learning, pain detection; stress detection; wearable sensor; physiological signals; behavioral signals
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使用人工智能进行心理健康预测-机器学习:使用可穿戴传感器和设备进行疼痛和压力检测-综述
疼痛是一种主观感觉;这是一种每个人一生中都必须经历过的感觉。然而,其机制和免疫途径仍是一个有待回答的问题。本文综述了疼痛和应激的机制和相关性,以及医疗设备和可穿戴传感器对疼痛和应激的评估和检测方法。各种生理信号(即心脏活动、大脑活动、肌肉活动、皮肤电活动、呼吸、血容量脉搏、皮肤温度)和行为信号被组织起来供可穿戴传感器检测。通过对医疗领域中应用的可穿戴传感器的回顾,我们希望找到一种将可穿戴医疗监测系统应用于疼痛和压力检测的方法。由于疼痛会导致多种后果或症状,例如与压力相关的肌肉紧张和抑郁,因此有机会找到一种使用日常生活传感器或设备检测慢性疼痛的新方法。然后通过整合现代计算技术,就有机会处理疼痛和压力管理问题。关键词:心理健康,机器学习,疼痛检测;压力检测;可穿戴式传感器;生理信号;行为的信号
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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