Accurate Stress detection from Novel Real-Time Electrodermal Activity Signals and Multi-task Learning Models

Stefan de Vries, R. Smits, Michalina Tataj, M. Ronckers, Mayra Van Der Pol, Fransje van Oost, E. Adam, H. Smaling, E. Meinders
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引用次数: 2

Abstract

Stress often is associated with physical and mental health issues. To prevent these issues, an early detection of stress is essential. However, for people with an intellectual disability effectively expressing stress can be difficult and therefore, the necessary intervention can be delayed. An automatic stress detection system could help caregivers in early detection of stress development. This can be achieved using wearable sensors that continuously record physiology. The changes in physiological signals, like in skin conductance can be used to classify moments of stress. The devices recording these signals are however, not always suitable for long term measurements. The present study evaluates a newly developed sock integrated skin conductance sensor (SentiSock) that does not restrict movement and stays comfortable over time. To assess if the sensor can be used for stress detection a comparison was made with the Empatica E4, a commonly used wrist-based skin conductance sensor. Both sensors were worn by 28 participants (mean age 39.25 ± 17.04) in a lab study where stress was induced using mathematical exercises. The data was used to train a multitask learning neural network for each device, following an identical procedure. The models were validated using a 5-fold cross validation that resulted in an average balanced accuracy of 0.824 (SD = 0.018) for Empatica E4 and 0.834 (SD = 0.019) for SentiSock. This demonstrated that both sensors can be used to detect stress adequately in lab conditions. Given these results, SentiSock will be further investigated for long term measurements.
基于新型实时皮肤电活动信号和多任务学习模型的准确应力检测
压力通常与身体和精神健康问题有关。为了预防这些问题,早期发现压力是至关重要的。然而,对于有智力障碍的人来说,有效地表达压力是很困难的,因此,必要的干预可能会被推迟。自动压力检测系统可以帮助护理人员在早期发现压力的发展。这可以通过持续记录生理的可穿戴传感器来实现。生理信号的变化,比如皮肤电导的变化,可以用来对压力时刻进行分类。然而,记录这些信号的设备并不总是适合长期测量。目前的研究评估了一种新开发的袜子集成皮肤电导传感器(SentiSock),它不会限制运动,并且随着时间的推移保持舒适。为了评估传感器是否可以用于应力检测,与Empatica E4(一种常用的手腕皮肤电导传感器)进行了比较。在实验室研究中,28名参与者(平均年龄39.25±17.04)佩戴了这两种传感器,并通过数学练习诱导压力。这些数据被用于为每个设备训练一个多任务学习神经网络,遵循相同的程序。采用5倍交叉验证对模型进行验证,Empatica E4和SentiSock的平均平衡精度分别为0.824 (SD = 0.018)和0.834 (SD = 0.019)。这表明,这两种传感器都可以在实验室条件下充分检测压力。鉴于这些结果,将进一步研究SentiSock进行长期测量。
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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