(FA8750-18-2-0027)
This study investigates the usage of new wearable sensing devices, which measure pulse wave velocity, respiratory rate, and heart rate before, during, and after cardiac rehabilitation exercises to better quantify recovery in participants diagnosed with heart failure with reduced ejection fraction. The study additionally aims to use this quantification to update estimates of recovery designed from baseline available data.
Huo, Zepeng, Arash PakBin, Xiaohan Chen, Nathan Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, and Bobak Mortazavi. “Uncertainty quantification for deep context-aware mobile activity recognition and unknown context discovery.” In International Conference on Artificial Intelligence and Statistics, pp. 3894-3904. PMLR, 2020. Link to paper
Huo, Zepeng, Lida Zhang, Rohan Khera, Shuai Huang, Xiaoning Qian, Zhangyang Wang, and Bobak J. Mortazavi. “Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data.” In 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), pp. 1-4. IEEE, 2021. Link to paper
STMI Lab @ Texas A&M University