Application of artificial intelligence in wearable devices: Opportunities and challenges

D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …

[HTML][HTML] Wearable technology applications in healthcare: a literature review

M Wu, J Luo - Online J. Nurs. Inform, 2019 - himss.org
Wearable technologies can be innovative solutions for healthcare problems. In this study,
we conducted a literature review of wearable technology applications in healthcare. Some …

Big data for internet of things: a survey

M Ge, H Bangui, B Buhnova - Future generation computer systems, 2018 - Elsevier
With the rapid development of the Internet of Things (IoT), Big Data technologies have
emerged as a critical data analytics tool to bring the knowledge within IoT infrastructures to …

[HTML][HTML] Wearable artificial intelligence for anxiety and depression: scoping review

A Abd-Alrazaq, R AlSaad, S Aziz, A Ahmed… - Journal of Medical …, 2023 - jmir.org
Background Anxiety and depression are the most common mental disorders worldwide.
Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence …

Heart rate variability for medical decision support systems: A review

O Faust, W Hong, HW Loh, S Xu, RS Tan… - Computers in biology …, 2022 - Elsevier
Abstract Heart Rate Variability (HRV) is a good predictor of human health because the heart
rhythm is modulated by a wide range of physiological processes. This statement embodies …

Recognizing emotions induced by affective sounds through heart rate variability

M Nardelli, G Valenza, A Greco… - IEEE Transactions …, 2015 - ieeexplore.ieee.org
This paper reports on how emotional states elicited by affective sounds can be effectively
recognized by means of estimates of Autonomic Nervous System (ANS) dynamics …

Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression

A Abd-Alrazaq, R AlSaad, F Shuweihdi, A Ahmed… - NPJ Digital …, 2023 - nature.com
Given the limitations of traditional approaches, wearable artificial intelligence (AI) is one of
the technologies that have been exploited to detect or predict depression. The current …

Detecting bipolar depression from geographic location data

N Palmius, A Tsanas, KEA Saunders… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Objective: This paper aims to identify periods of depression using geolocation movements
recorded from mobile phones in a prospective community study of individuals with bipolar …

Evaluating depression with multimodal wristband-type wearable device: screening and assessing patient severity utilizing machine-learning

Y Tazawa, K Liang, M Yoshimura, M Kitazawa, Y Kaise… - Heliyon, 2020 - cell.com
Objective We aimed to develop a machine learning algorithm to screen for depression and
assess severity based on data from wearable devices. Methods We used a wearable device …

Heart rate variability in bipolar disorder: A systematic review and meta-analysis

M Faurholt-Jepsen, LV Kessing, K Munkholm - … & Biobehavioral Reviews, 2017 - Elsevier
Background Heart rate variability (HRV) has been suggested reduced in bipolar disorder
(BD) compared with healthy individuals (HC). This meta-analysis investigated: HRV …