Jointly utilizing different sensor streams from your smartphone, smartwatch, and smart home environment devices can create some pretty amazing personal health informatics.
Status of this project: on the back burner, but collaborators welcome
Publications:
- Wu, C., Fisher, A., & Schnyer, D. (2022). Gaussian Latent Dirichlet Allocation for Discrete Human State Discovery. arXiv preprint arXiv:2206.14233. To be submitted to ACM Transactions on Computing for Healthcare.
- Fritz, H., Kinney, K. A., Wu, C., Schnyer, D. M., & Nagy, Z. (2022). Data fusion of mobile and environmental sensing devices to understand the effect of the indoor environment on measured and self-reported sleep quality. Building and Environment, 214, 108835.
- Wu, C., Fritz, H., Bastami, S., Maestre, J. P., Thomaz, E., Julien, C., … & Nagy, Z. (2021). Multi-modal data collection for measuring health, behavior, and living environment of large-scale participant cohorts. GigaScience, 10(6), giab044.
- Wu, C., McMahon, M., Fritz, H., & Schnyer, D. M. (2022). circadian rhythms are not captured equal: Exploring Circadian metrics extracted by different computational methods from smartphone accelerometer and GPS sensors in daily life tracking. Digital Health, 8, 20552076221114201.
- Wu, C., Fritz, H., Craddock, C., Kinney, K. A., Castelli, D. M., & Schnyer, D. M. (2021). Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: a GPS-focused Smartphone Sensing Study. Frontiers in Digital Health, 169.
- Boukhechba, M., Cai, L., Wu, C., & Barnes, L. E. (2019). ActiPPG: using deep neural networks for activity recognition from wrist-worn photoplethysmography (PPG) sensors. Smart Health, 14, 100082.
- Cai, L., Boukhechba, M., Wu, C., Chow, P. I., Teachman, B. A., Barnes, L. E., & Gerber, M. S. (2018, September). State affect recognition using smartphone sensing data. In Proceedings of the 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (pp. 120-125).