Smartwatches in healthcare medicine: assistance and monitoring; a sco** review

M Masoumian Hosseini… - BMC Medical Informatics …, 2023 - Springer
Smartwatches have become increasingly popular in recent times because of their capacity
to track different health indicators, including heart rate, patterns of sleep, and physical …

[HTML][HTML] Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review

G Vos, K Trinh, Z Sarnyai, MR Azghadi - International Journal of Medical …, 2023 - Elsevier
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 …

A machine-learning approach for stress detection using wearable sensors in free-living environments

M Abd Al-Alim, R Mubarak, NM Salem… - Computers in Biology and …, 2024 - Elsevier
Stress is a psychological condition resulting from the body's response to challenging
situations, which can negatively impact physical and mental health if experienced over …

Occupational stress monitoring using biomarkers and smartwatches: a systematic review

A Morales, M Barbosa, L Morás, SC Cazella, LF Sgobbi… - Sensors, 2022 - mdpi.com
This article presents a systematic review of the literature concerning scientific publications
on wrist wearables that can help to identify stress levels. The study is part of a research …

[HTML][HTML] Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing …

S Mahmud, MEH Chowdhury, S Kiranyaz… - Expert Systems with …, 2024 - Elsevier
Abstract Background and Motivations Physiological signals, such as the
Photoplethysmogram (PPG) collected through wearable devices, consistently encounter …

Privacy-preserving feature selection with secure multiparty computation

X Li, R Dowsley, M De Cock - International Conference on …, 2021 - proceedings.mlr.press
Existing work on privacy-preserving machine learning with Secure Multiparty Computation
(MPC) is almost exclusively focused on model training and on inference with trained models …

MAUS: A dataset for mental workload assessmenton N-back task using wearable sensor

WK Beh, YH Wu - arxiv preprint arxiv:2111.02561, 2021 - arxiv.org
This paper describes an open-access database focusing on the study of mental workload
(MW) assessment system for wearable devices. A wristband photoplethysmogram (PPG) …

Understanding occupants' behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables

N Gao, M Marschall, J Burry, S Watkins, FD Salim - Scientific Data, 2022 - nature.com
We conducted a field study at a K-12 private school in the suburbs of Melbourne, Australia.
The data capture contained two elements: First, a 5-month longitudinal field study In-Gauge …

Cognitive load approach to digital comics creation: A student-centered learning case

D Apostolou, G Linardatos - Applied Sciences, 2023 - mdpi.com
Featured Application The present work has applications in the field of primary and
secondary education. The work describes how educators can take advantage of digital …

[HTML][HTML] Can we ditch feature engineering? end-to-end deep learning for affect recognition from physiological sensor data

M Dzieżyc, M Gjoreski, P Kazienko, S Saganowski… - Sensors, 2020 - mdpi.com
To further extend the applicability of wearable sensors in various domains such as mobile
health systems and the automotive industry, new methods for accurately extracting subtle …