Real-Life Stress Level Monitoring Using Smart Bands in the Light of Contextual Information

Abstract

An automatic stress detection system that uses unobtrusive smart bands will contribute to human health and well-being by alleviating the effects of high stress levels. However, there are a number of challenges for detecting stress in unrestricted daily life which results in lower performances of such systems when compared to semi-restricted and laboratory environment studies. The addition of contextual information such as physical activity level, activity type and weather to the physiological signals can improve the classification accuracies of these systems. We developed an automatic stress detection system that employs smart bands for physiological data collection. In this study, we monitored the stress levels of 16 participants of an EU project training every day throughout the eight days long event by using our system. We collected 1440 hours of physiological data and 2780 self-report questions from the participants who are from diverse countries. The project midterm presentations (see Figure 3) in front of a jury at the end of the event were the source of significant real stress. Different types of contextual information, along with the physiological data, were recorded to determine the perceived stress levels of individuals. We further analyze the physiological signals in this event to infer long term perceived stress levels which we obtained from baseline PSS-14 questionnaires. Session-based, daily and long-term perceived stress levels could be identified by using the proposed system successfully.

Potential Applications of Mobile and Wearable Devices for Psychological Support During the COVID-19 Pandemic: A Review

“…Fitbit's smartwatch also has the highest number of studies, validating their reliability in comparison to the other vendors [144]. Currently, however, Fitbit still does not provide access to the PPG and EDA raw data (used in the reviewed study [63]) and only provides access to the derived HRV data and stress analysis data (from EDA) on their official app. It might be possible to use the derived data from Fitbit Sense instead of the raw data.…”

“…Additionally, patients with stress and anxiety symptoms were found to display lower HRV than that of the control group [32], [35]. In most of the previous studies, the wearable devices used in the researches are research-grade, in which they can provide one or both of these two information (i.e., Affectiva Q Sensor and Empatica E4) [63], [64], [103]. Affectiva Q Sensor can measure the acceleration, SC, and ST at the sampling frequency of 32 Hz [105].…”

“…Thus, they are the prime target participants for stress assessment. Can et al developed an automatic stress detection system using smart bands for physiological data collection [63]. The stress level of 16 doctorate students was determined by the detected HRV and skin conductance (SC) during an 8-day period.…”

Biosensing and Actuation—Platforms Coupling Body Input-Output Modalities for Affective Technologies

“…These, although not an exhaustive list, are to some extent physiological signals that have become standard for physiology tracking research—slowly crossing disciplines and making their way into affective health tracking, interaction design, and other domains of interest. Moreover, with objectives that range from out-of-the-lab psychophysiology tracking [ 57 , 58 , 59 ] to new perspectives in interaction design [ 43 , 49 , 60 ] our work has often addressed biosignals through other available biosignal research platforms beyond BITalino, such as biosignalsplux [ 61 ], Empatica E4 [ 62 ], Arduino accessories like the Grove GSR [ 63 ], or even commercial wearables such as the Samsung Gear S2 [ 64 ] among others.…”

HRV and Stress: A Mixed-Methods Approach for Comparison of Wearable Heart Rate Sensors for Biofeedback

“…In order to address these research questions, we combined quantitative and qualitative data analysis techniques across six heart rate monitoring devices on key bodily locations. All of which are widely used in the literature for HRV analysis [17], [28]- [32] and have been validated in prior research [33]- [35]. In total, we recruited 32 participants and asked them to wear six different heart rate monitoring devices.…”