[HTML][HTML] Wearable artificial intelligence for anxiety and depression: scoping review
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 …
Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence …
Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression
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 …
the technologies that have been exploited to detect or predict depression. The current …
Exploration of EEG-based depression biomarkers identification techniques and their applications: a systematic review
Depression is the most common mental illness, which has become the major cause of fear
and suicidal mortality or tendencies. Currently, about 10% of the world population has been …
and suicidal mortality or tendencies. Currently, about 10% of the world population has been …
An insight into diagnosis of depression using machine learning techniques: a systematic review
Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …
from which millions of individuals are affected today. The symptoms of depression are …
Depress-DCNF: A deep convolutional neuro-fuzzy model for detection of depression episodes using IoMT
Discernible patterns of a person's daily activities can be utilized to detect behavioral
symptomatology of mental illness at early stages. Wearable Internet of Medical Things …
symptomatology of mental illness at early stages. Wearable Internet of Medical Things …
Unipolar and bipolar depression detection and classification based on actigraphic registration of motor activity using machine learning and uniform manifold …
M Zakariah, YA Alotaibi - Diagnostics, 2023 - mdpi.com
Modern technology frequently uses wearable sensors to monitor many aspects of human
behavior. Since continuous records of heart rate and activity levels are typically gathered …
behavior. Since continuous records of heart rate and activity levels are typically gathered …
Identifying digital biomarkers in actigraph based sequential motor activity data for assessment of depression: a model evaluating SVM in LSTM extracted feature space
This research puts forward a methodology for depression assessment using actigraph
recordings of motor activity. High level features of motor activity are extracted using Long …
recordings of motor activity. High level features of motor activity are extracted using Long …
Predicting depressive symptoms in middle-aged and elderly adults using sleep data and clinical health markers: A machine learning approach
SRBS Gomes, M von Schantz, M Leocadio-Miguel - Sleep Medicine, 2023 - Elsevier
Objectives Comorbid depression is a highly prevalent and debilitating condition in middle-
aged and elderly adults, particularly when associated with obesity, diabetes, and sleep …
aged and elderly adults, particularly when associated with obesity, diabetes, and sleep …
Psykose: A motor activity database of patients with schizophrenia
P Jakobsen, E Garcia-Ceja, LA Stabell… - 2020 IEEE 33rd …, 2020 - ieeexplore.ieee.org
Using sensor data from devices such as smart-watches or mobile phones is very popular in
both computer science and medical research. Such movement data can predict certain …
both computer science and medical research. Such movement data can predict certain …
Two-dimensional convolutional neural network for depression episodes detection in real time using motor activity time series of depresjon dataset
Depression is a common illness worldwide, affecting an estimated 3.8% of the population,
including 5% of all adults, in particular, 5.7% of adults over 60 years of age. Unfortunately, at …
including 5% of all adults, in particular, 5.7% of adults over 60 years of age. Unfortunately, at …