Name
Abstract | ||
|---|---|---|
BSTRACTThe Augmented reality/Virtual reality (AR/VR) industry has ushered in a period of rapid development. The next decade leaves a massive imagination for AR/VR in terms of end product form, software, content, applications, and user increment. The AR & VR technology offers a gazillion of possibilities for smart healthcare. In this poster, we develop an innovative continuous blood pressure (CBP) estimation system leveraging the built-in motion sensors of AR/VR headsets for users. We design a deep learning-based PPG construction scheme using the motion sensor-based cardiac signal and estimate the continuous blood pressure using the regression model. Our experimental results show that our system can continuously estimate both systolic blood pressure (SBP) and diastolic blood pressure (DBP) with a mean error of less than 4 mmHg and 0.9 mmHg respectively within a day. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3498361.3538798 | Mobile Systems, Applications, and Services |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianming Zhao | 1 | 0 | 1.35 |
| Zhengkun Ye | 2 | 0 | 0.68 |
| Tianfang Zhang | 3 | 1 | 2.12 |
| Cong Shi | 4 | 0 | 1.69 |
| Ahmed Tanvir Mahdad | 5 | 0 | 0.68 |
| Yan Wang | 6 | 811 | 40.19 |
| Yingying Chen | 7 | 2495 | 193.14 |
| Nitesh Saxena | 8 | 1204 | 82.45 |