[HTML][HTML] Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review
Introduction Wearable sensors have shown promise as a non-intrusive method for collecting
biomarkers that may correlate with levels of elevated stress. Stressors cause a variety of …
biomarkers that may correlate with levels of elevated stress. Stressors cause a variety of …
A Reproducible Stress Prediction Pipeline with Mobile Sensor Data
Recent efforts to predict stress in the wild using mobile technology have increased; however,
the field lacks a common pipeline for assessing the impact of factors such as label encoding …
the field lacks a common pipeline for assessing the impact of factors such as label encoding …
[HTML][HTML] FLIRT: A feature generation toolkit for wearable data
Abstract Background and Objective: Researchers use wearable sensing data and machine
learning (ML) models to predict various health and behavioral outcomes. However, sensor …
learning (ML) models to predict various health and behavioral outcomes. However, sensor …
[HTML][HTML] An interpretable machine learning approach to multimodal stress detection in a simulated office environment
Background and objective: Work-related stress affects a large part of today's workforce and
is known to have detrimental effects on physical and mental health. Continuous and …
is known to have detrimental effects on physical and mental health. Continuous and …
GLOBEM dataset: multi-year datasets for longitudinal human behavior modeling generalization
Recent research has demonstrated the capability of behavior signals captured by
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
Application level performance evaluation of wearable devices for stress classification with explainable AI
Stress has become one of the most prominent problems of modern societies and a key
contributor to major health issues. Dealing with stress effectively requires detecting it in real …
contributor to major health issues. Dealing with stress effectively requires detecting it in real …
Machine learning-based detection of acute psychosocial stress from body posture and movements
Investigating acute stress responses is crucial to understanding the underlying mechanisms
of stress. Current stress assessment methods include self-reports that can be biased and …
of stress. Current stress assessment methods include self-reports that can be biased and …
Detecting receptivity for mHealth interventions in the natural environment
Just-In-Time Adaptive Intervention (JITAI) is an emerging technique with great potential to
support health behavior by providing the right type and amount of support at the right time. A …
support health behavior by providing the right type and amount of support at the right time. A …
[HTML][HTML] Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices
Introduction: Advances in wearable sensor technology have enabled the collection of
biomarkers that may correlate with levels of elevated stress. While significant research has …
biomarkers that may correlate with levels of elevated stress. While significant research has …
[HTML][HTML] Cross dataset analysis for generalizability of HRV-based stress detection models
Stress is an increasingly prevalent mental health condition across the world. In Europe, for
example, stress is considered one of the most common health problems, and over USD 300 …
example, stress is considered one of the most common health problems, and over USD 300 …