Smart devices and wearable technologies to detect and monitor mental health conditions and stress: A systematic review

BA Hickey, T Chalmers, P Newton, CT Lin, D Sibbritt… - Sensors, 2021 - mdpi.com
Recently, there has been an increase in the production of devices to monitor mental health
and stress as means for expediting detection, and subsequent management of these …

[PDF][PDF] A sco** review on monitoring mental health using smart wearable devices

N Long, Y Lei, L Peng, P Xu, P Mao - Math. Biosci. Eng, 2022 - aimspress.com
With the continuous development of the times, social competition is becoming increasingly
fierce, people are facing enormous pressure and mental health problems have become …

Automated arrhythmia classification based on a combination network of CNN and LSTM

C Chen, Z Hua, R Zhang, G Liu, W Wen - Biomedical Signal Processing …, 2020 - Elsevier
Arrhythmia is an abnormal heartbeat rhythm, and its prevalence increases with age. An
electrocardiogram (ECG) is a standard tool for detecting cardiac activity. However, because …

Diagnosis of arrhythmias with few abnormal ECG samples using metric-based meta learning

Z Liu, Y Chen, Y Zhang, S Ran, C Cheng… - Computers in biology and …, 2023 - Elsevier
A major challenge in artificial intelligence based ECG diagnosis lies that it is difficult to
obtain sufficient annotated training samples for each rhythm type, especially for rare …

Human state anxiety classification framework using EEG signals in response to exposure therapy

F Muhammad, S Al-Ahmadi - Plos one, 2022 - journals.plos.org
Human anxiety is a grave mental health concern that needs to be addressed in the
appropriate manner in order to develop a healthy society. In this study, an objective human …

[HTML][HTML] Pattern recognition of cognitive load using EEG and ECG signals

R ** training using ECG signals
W Feng, K Zeng, X Zeng, J Chen, H Peng, B Hu… - … Signal Processing and …, 2023 - Elsevier
Physical fatigue is a crucial factor that leads to a decrease in performance, especially in
athletes. This study proposes effective physiological indicators and methods to predict …

A critical review of multimodal-multisensor analytics for anxiety assessment

H Senaratne, S Oviatt, K Ellis, G Melvin - ACM Transactions on …, 2022 - dl.acm.org
Recently, interest has grown in the assessment of anxiety that leverages human
physiological and behavioral data to address the drawbacks of current subjective clinical …

Machine learning-based anxiety detection in older adults using wristband sensors and context feature

RK Nath, H Thapliyal - SN Computer Science, 2021 - Springer
This paper explores a novel method for anxiety detection in older adults using simple
wristband sensors such as electrodermal activity (EDA) and photoplethysmogram (PPG) and …