Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number
Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited
specialized care availability remains a major bottleneck thus hindering pre-emptive …
specialized care availability remains a major bottleneck thus hindering pre-emptive …
Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting
G Anmella, A Mas, M Sanabra… - Journal of Affective …, 2024 - Elsevier
Background Bipolar disorder (BD) lacks objective measures for illness activity and treatment
response. Electrodermal activity (EDA) is a quantitative measure of autonomic function …
response. Electrodermal activity (EDA) is a quantitative measure of autonomic function …
Automatic Bipolar Disorder Assessment Using Machine Learning With Smartphone-Based Digital Phenotyping
Bipolar disorder (BD) is one of the most common mental illnesses worldwide. In this study, a
smartphone application was developed to collect digital phenotyping data of users, and an …
smartphone application was developed to collect digital phenotyping data of users, and an …
[HTML][HTML] Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via …
Background Personal sensing, leveraging data passively and near-continuously collected
with wearables from patients in their ecological environment, is a promising paradigm to …
with wearables from patients in their ecological environment, is a promising paradigm to …
Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised …
Personal sensing, leveraging data passively and near-continuously collected with
wearables from patients in their ecological environment, is a promising paradigm to monitor …
wearables from patients in their ecological environment, is a promising paradigm to monitor …
[PDF][PDF] Wearable data from students, teachers or subjects with alcohol use disorder help detect acute mood episodes via self-supervised learning
AV Hidalgo-Mazzei - s3.ca-central-1.amazonaws.com
Background: Personal sensing, leveraging data passively and near-continuously collected
with wearables from patients in their ecological environment, is a promising paradigm to …
with wearables from patients in their ecological environment, is a promising paradigm to …