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Abstract Stress is one of the main causes that increase the risk of serious health problems. Recent wearable devices have been used to monitor stress levels via electrodermal activities on the skin. Although many biosensors provide adequate sensing performance, they still rely on uncomfortable, partially flexible systems with rigid electronics. These devices are mounted on either fingers or palms, which hinders a continuous signal monitoring. A fully‐integrated, stretchable, wireless skin‐conformal bioelectronic (referred to as “SKINTRONICS”) is introduced here that integrates soft, multi‐layered, nanomembrane sensors and electronics for continuous and portable stress monitoring in daily life. The all‐in‐one SKINTRONICS is ultrathin, highly soft, and lightweight, which overall offers an ergonomic and conformal lamination on the skin. Stretchable nanomembrane electrodes and a digital temperature sensor enable highly sensitive monitoring of galvanic skin response (GSR) and temperature. A set of comprehensive signal processing, computational modeling, and experimental study provides key aspects of device design, fabrication, and optimal placing location. Simultaneous comparison with two commercial stress monitors captures the enhanced performance of SKINTRONICS in long‐term wearability, minimal noise, and skin compatibility. In vivo demonstration of continuous stress monitoring in daily life reveals the unique capability of the soft device as a real‐world applicable stress monitor.
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WiStress: Contactless Stress Monitoring Using Wireless Signals
Stress plays a critical role in our lives, impacting our productivity and our long-term physiological and psychological well-being. This has motivated the development of stress monitoring solutions to better understand stress, its impact on productivity and teamwork, and help users adapt their habits toward more sustainable stress levels. However, today's stress monitoring solutions remain obtrusive, requiring active user participation (e.g., self-reporting), interfering with people's daily activities, and often adding more burden to users looking to reduce their stress. In this paper, we introduce WiStress, the first system that can passively monitor a user's stress levels by relying on wireless signals. WiStress does not require users to actively provide input or to wear any devices on their bodies. It operates by transmitting ultra-low-power wireless signals and measuring their reflections off the user's body. WiStress introduces two key innovations. First, it presents the first machine learning network that can accurately and robustly extract heartbeat intervals (IBI's) from wireless reflections without constraints on a user's daily activities. Second, it introduces a stress classification framework that combines the extracted heartbeats with other wirelessly captured stress-related features in order to infer a subject's stress level. We built a prototype of WiStress and tested it on 22 different subjects across different environments in both stress-induced and free-living conditions. Our results demonstrate that WiStress has high accuracy (84%-95%) in inferring a person's stress level in a fully-automated way, paving the way for ubiquitous sensing systems that can monitor stress and provide feedback to improve productivity, health, and well-being.
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- Award ID(s):
- 1844280
- PAR ID:
- 10319378
- Date Published:
- Journal Name:
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
- Volume:
- 5
- Issue:
- 3
- ISSN:
- 2474-9567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3478121
