Recent advances in contactless sensing technologies for mental health monitoring
The process of monitoring mental health has relied on methods, such as invasive sensing
and self-reporting. The use of these methods has been limited because of the invasiveness …
and self-reporting. The use of these methods has been limited because of the invasiveness …
Attention-based convolutional neural network and long short-term memory for short-term detection of mood disorders based on elicited speech responses
Mood disorders, including unipolar depression (UD) and bipolar disorder (BD), have
become some of the commonest mental health disorders. The absence of diagnostic …
become some of the commonest mental health disorders. The absence of diagnostic …
Cell-Coupled Long Short-Term Memory With -Skip Fusion Mechanism for Mood Disorder Detection Through Elicited Audiovisual Features
In early stages, patients with bipolar disorder are often diagnosed as having unipolar
depression in mood disorder diagnosis. Because the long-term monitoring is limited by the …
depression in mood disorder diagnosis. Because the long-term monitoring is limited by the …
Development of Sorrow Analysis Dataset for Speech Depression Prediction
MF Alghifari, TS Gunawan… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Computers can get insight into the user's mental state, including depression prediction, by
analyzing speech signals. Numerous uses exist, ranging from customer service to …
analyzing speech signals. Numerous uses exist, ranging from customer service to …
A framework for monitoring of depression patient using WBAN
Wireless Body Area Networks consist of low power lightweight wearable and/or implantable
sensor nodes that are often placed remotely for applications like ubiquitous health care …
sensor nodes that are often placed remotely for applications like ubiquitous health care …
On the optimum speech segment length for depression detection
MF Alghifari, TS Gunawan, MAW Nordin… - … conference on smart …, 2019 - ieeexplore.ieee.org
Depression is a worldwide problem, which according to the World Health Organization, is
the largest contributor to global disability. According to a study, around 18336 Malaysians …
the largest contributor to global disability. According to a study, around 18336 Malaysians …
A Survey: Feature Extraction Techniques and machine learning models for Depression Analysis
The most common psychiatric disorder is Clinical Depression. More than fifteen percent of
people undergo an incident of major depression sometime during their life. There is an …
people undergo an incident of major depression sometime during their life. There is an …
[HTML][HTML] Who's in Charge? Information Technology and Disability Justice in the United States
A Gibson, R Williams - 2022 - just-tech.ssrc.org
Disabled people in the United States are surrounded, defined, and, to some degree,
controlled by data, technology, and information—from medical technology and therapies to …
controlled by data, technology, and information—from medical technology and therapies to …
[PDF][PDF] Smart model for Depression detection Using Deep Learning
P Kapse, VK Gargline - kalaharijournals.com
In this research paper to classifying Depression detection People datasets using a deep
neural network model, namely, Smart model for Depression detection (SMDD) is proposed …
neural network model, namely, Smart model for Depression detection (SMDD) is proposed …
[PDF][PDF] ARTIFICIAL INTELLIGENCE BASED DEPRESSION RECOGNITION SYSTEM
L Joy, N Alex, S Thomas, T Sunny, A George - 2020 - academia.edu
Prediction of depression manually is a time consuming process. Apps and chat boxes with
cognitive capabilities can recognize the mental state of a person. This project proposes a …
cognitive capabilities can recognize the mental state of a person. This project proposes a …