GLOBEM dataset: multi-year datasets for longitudinal human behavior modeling generalization
Recent research has demonstrated the capability of behavior signals captured by
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment
Mental health disorders—including depression, anxiety, trauma-related, and psychotic
conditions—are pervasive and impairing, representing considerable challenges for both …
conditions—are pervasive and impairing, representing considerable challenges for both …
[HTML][HTML] Digital Phenotyping for Stress, Anxiety, and Mild Depression: Systematic Literature Review
A Choi, A Ooi, D Lottridge - JMIR mHealth and uHealth, 2024 - mhealth.jmir.org
Background: Unaddressed early-stage mental health issues, including stress, anxiety, and
mild depression, can become a burden for individuals in the long term. Digital phenotyping …
mild depression, can become a burden for individuals in the long term. Digital phenotyping …
[HTML][HTML] The Google Health Digital Well-Being Study: Protocol for a Digital Device Use and Well-Being Study
D McDuff, A Barakat, A Winbush… - JMIR Research …, 2024 - researchprotocols.org
Background: The impact of digital device use on health and well-being is a pressing
question. However, the scientific literature on this topic, to date, is marred by small and …
question. However, the scientific literature on this topic, to date, is marred by small and …
Fairness Without Demographics in Human-Centered Federated Learning
Federated learning (FL) enables collaborative model training while preserving data privacy,
making it suitable for decentralized human-centered AI applications. However, a significant …
making it suitable for decentralized human-centered AI applications. However, a significant …
Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data
AI tools intend to transform mental healthcare by providing remote estimates of depression
risk using behavioral data collected by sensors embedded in smartphones. While these …
risk using behavioral data collected by sensors embedded in smartphones. While these …
Illuminating the Unseen: A Framework for Designing and Mitigating Context-induced Harms in Behavioral Sensing
With the advanced ability to capture longitudinal sensed data and model human behavior,
behavioral sensing technologies are progressing toward numerous wellbeing applications …
behavioral sensing technologies are progressing toward numerous wellbeing applications …
Human-Machine Alignment for Context Recognition in the Wild
A Bontempelli - 2024 - iris.unitn.it
The premise for AI systems like personal assistants to provide guidance and suggestions to
an end-user is to understand, at any moment in time, the personal context that the user is in …
an end-user is to understand, at any moment in time, the personal context that the user is in …
PupilSense: Detection of Depressive Episodes Through Pupillary Response in the Wild
Early detection of depressive episodes is crucial in managing mental health disorders such
as Major Depressive Disorder (MDD) and Bipolar Disorder. However, existing methods often …
as Major Depressive Disorder (MDD) and Bipolar Disorder. However, existing methods often …
SeSaMe: A Framework to Simulate Self-Reported Ground Truth for Mental Health Sensing Studies
Advances in mobile and wearable technologies have enabled the potential to passively
monitor a person's mental, behavioral, and affective health. These approaches typically rely …
monitor a person's mental, behavioral, and affective health. These approaches typically rely …