A review on mental stress detection using wearable sensors and machine learning techniques

S Gedam, S Paul - IEEE Access, 2021 - ieeexplore.ieee.org
Stress is an escalated psycho-physiological state of the human body emerging in response
to a challenging event or a demanding condition. Environmental factors that trigger stress …

Review of eye tracking metrics involved in emotional and cognitive processes

V Skaramagkas, G Giannakakis… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
Eye behaviour provides valuable information revealing one's higher cognitive functions and
state of affect. Although eye tracking is gaining ground in the research community, it is not …

State-of-the-art of stress prediction from heart rate variability using artificial intelligence

Y Haque, RS Zawad, CSA Rony, H Al Banna… - Cognitive …, 2024 - Springer
Recent advancements in the manufacturing and commercialisation of miniaturised sensors
and low-cost wearables have enabled an effortless monitoring of lifestyle by detecting and …

[HTML][HTML] Cross dataset analysis for generalizability of HRV-based stress detection models

M Benchekroun, PE Velmovitsky, D Istrate, V Zalc… - Sensors, 2023 - mdpi.com
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 …

ECG and EEG based detection and multilevel classification of stress using machine learning for specified genders: A preliminary study

A Hemakom, D Atiwiwat, P Israsena - Plos one, 2023 - journals.plos.org
Mental health, especially stress, plays a crucial role in the quality of life. During different
phases (luteal and follicular phases) of the menstrual cycle, women may exhibit different …

[HTML][HTML] A review of methods and applications for a heart rate variability analysis

SK Nayak, B Pradhan, B Mohanty, J Sivaraman… - Algorithms, 2023 - mdpi.com
Heart rate variability (HRV) has emerged as an essential non-invasive tool for
understanding cardiac autonomic function over the last few decades. This can be attributed …

Predicting mental health disorders using machine learning for employees in technical and non-technical companies

R Katarya, S Maan - 2020 IEEE International Conference on …, 2020 - ieeexplore.ieee.org
Mental health has always been an important and challenging issue, especially in the case of
working Professionals. The modernized (hectic) lifestyle and workload take a toll over …

Strategies for reliable stress recognition: A machine learning approach using heart rate variability features

M Bahameish, T Stockman, J Requena Carrión - Sensors, 2024 - mdpi.com
Stress recognition, particularly using machine learning (ML) with physiological data such as
heart rate variability (HRV), holds promise for mental health interventions. However, limited …

Biometric data as real-time measure of physiological reactions to environmental stimuli in the built environment

SGL Persiani, B Kobas, SC Koth, T Auer - Energies, 2021 - mdpi.com
The physiological and cognitive effects of environmental stimuli from the built environment
on humans have been studied for more than a century, over short time frames in terms of …

Designing AI for mental health diagnosis: challenges from sub-Saharan African value-laden judgements on mental health disorders

ET Ugar, N Malele - Journal of medical ethics, 2024 - jme.bmj.com
Recently clinicians have become more reliant on technologies such as artificial intelligence
(AI) and machine learning (ML) for effective and accurate diagnosis and prognosis of …