BeWell: A Smartphone Application to Monitor, Model and Promote Wellbeing
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A key challenge for mobile health is to develop new technology that can assist individuals in maintaining a healthy lifestyle by keeping track of their everyday behaviors. Smartphones embedded with a wide variety of sensors are enabling a new generation of personal health applications that can activ
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The NeuroSence application detects sleep and speech/conversation data using pre-trained classifiers on accelerometer and audio data.
“Furthermore, our application detects sleep [17] and speech/conversation data [54, 76] by incorporating pre-trained classifiers using accelerometer and audio data from a microphone, respectively.”
From Predicting Brain Functional Connectivity Using Mobile Sensing (2020) · cites this paper as [54]
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Self-citation
- Authors
- Lane, N., Mohammod, M., Lin, M., Yang, X., Lu, H., Ali, S., Doryab, A., Berke, E., Choudhury, T., & Campbell, A.
- Affiliations
- Dartmouth College (US)
- Cornell University (US)
- Corresponding author
- Lane, Nicholas
- ORCID
- Venue
- Proceedings of the 5th International ICST Conference on Pervasive Computing Technologies for Healthcare
- Publisher
- IEEE
- Published
- 2011
- ISSN
- 2153-1633 (ISSN-L)
- OpenAlex
- W2056591916
- Cited by
- 409
- References
- 24
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 8 · 2023: 11 · 2022: 18 · 2021: 21 · 2020: 32 · 2019: 26 · 2018: 36 · 2017: 39 · 2016: 42 · 2015: 66 · 2014: 45 · 2013: 36 · 2012: 17
- FWCI
- 171.62
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Pervasive Computing Technologies for Healthcare (publishedVersion)
- IT University Of Copenhagen (IT University of Copenhagen) (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- mobile application, well-being, mobile health, behavioral tracking, healthy lifestyle, health promotion, behavioral modeling
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