UbiLife
help a larger scope of people to reduce stress through a closed-loop personalized assistive service
Project Description
The overarching goal is to help a larger scope of people to reduce stress through a closed-loop personalized assistive service integrated with a) continuous behavioral monitoring and symptom detection, b) automation of mental health assessment, and c) just-in-time symptom-aware coaching. Different from UB Mind, we are working on developing a data-driven daily activity summary prototype to sense and process multimodal data (wearable and mobile sensors, device use, self-report and clinical data) and interpret them as meaningful behavioral patterns to automate personal assessment. Such prototype can help to gauge smartphone usage and visualize the behavior patterns for self-awareness. The outcome will be a) changes of psychological instrument scores; b) user lifestyle; c) adherence, usability.
UbiLife User Privacy Policy: detail link
Disclaimer:EarlySee Project was launched since March 2014. The team didn't receive any grant support, and the project is supported by a group of passionate researchers who wants to promote the childhood mental health.
- 2021/01 new updates
- 2021/01 new updates
- 2021/01 new updates
Wenyao Xu (PI) - contact: wenyaoxu@buffalo.edu
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- [3] Tri Vu, Hoan Duc Tran, Kun Woo Cho, Chen Song, Feng Lin, Michelle Hartley-McAndrew, Kathy Doody, Chang Wen Chen, Wenyao Xu, "Efficient and Effective Visual Stimuli Design for Quantitative Autism Screening: An Exploratory Study", IEEE International Conference on Biomedical and Health Informatics (BHI'17), Orlando, Florida, February 2017
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- publication1