Quantitative Assessment for Self-Tracking of Acute Stress based on Triangulation Principle in a Wearable Sensor System

	Quantitative Assessment for Self-Tracking of Acute Stress based on Triangulation Principle in a Wearable Sensor System
	Wanqing Wu; Heye Zhang; Subhas Chandra Mukhopadhyay; Sandeep Pirbhulal
刊名	IEEE Journal of Biomedical and Health Informatics
	2018
文献子类	期刊论文
英文摘要	Stress is linked to human’s health through behavioral and physiological responses; various researches showed that long-term exposure to stress and its related diseases are responsible of dramatic increase of mortality. Continuously monitoring of daily stress can assist to identify the mental condition at an early stage before getting serious disorder. However, managing individual’s stress is not an easy task since its measurement is not straight forward, more important, the lack of simple and effective quantization method has been the obstacle for real time stress level estimation. Therefore, in this study, an exploratory, mixed method has been proposed to investigate the feasibility of using well-designed wearable sensing platform for periodic monitoring and assessment of stress level, alongside a respiratory manipulation program for stress regulation. The logistic regression formula defined as mental stress index (MSI) was established based on analyzing on the intrinsic relationship of biochemical indicator (salivary cortisol), psychological scale (SRI) and physiological features (heart rate variability, HRV), which were considered as the representatives of hypothalamus-pituitary-adrenal axis, emotion and autonomic nervous system functions to stress responses, respectively. Based on the developed wearable sensor system, the accuracy of MSI-based stress estimation and the efficacy of respiratory related stress regulation were verified under the negative stimuli triggered by IAPS. The current data showed that HRV SDNN, LF/HF ratio and MSI value were sensitive to acute stress, and MSI value could predict which stress group a normal subject belongs to with approximately 97% accuracy. Furthermore, deep breathing with long expiration could increase the overall HRV and parasympathetic activation, and then decrease MSI value furthest, which may provide a valuable and more plausible tool for self tracking and training of acute stress in dynamic settings.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/14168]
专题	深圳先进技术研究院_医工所
推荐引用方式 GB/T 7714	Wanqing Wu,Heye Zhang,Subhas Chandra Mukhopadhyay,et al. Quantitative Assessment for Self-Tracking of Acute Stress based on Triangulation Principle in a Wearable Sensor System[J]. IEEE Journal of Biomedical and Health Informatics,2018.
APA	Wanqing Wu,Heye Zhang,Subhas Chandra Mukhopadhyay,&Sandeep Pirbhulal.(2018).Quantitative Assessment for Self-Tracking of Acute Stress based on Triangulation Principle in a Wearable Sensor System.IEEE Journal of Biomedical and Health Informatics.
MLA	Wanqing Wu,et al."Quantitative Assessment for Self-Tracking of Acute Stress based on Triangulation Principle in a Wearable Sensor System".IEEE Journal of Biomedical and Health Informatics (2018).