| Presentation | 2020-11-04 Non-contact Blood Pressure Measurement using Doppler Radar based on Waveform Analysis by LSTM Shuzo Ishizaka, Kohei Yamamoto, Tomoaki Ohtsuki, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recently, non-contact blood pressure measurement is receiving a lot of interests because it is suitablefor the blood pressure measurement on a daily basis. A Doppler radar is a key device to enable non-contact blood pressure measurement, and it can observe pulse waves due to aortic vasomotion. Speci cally, PTT (Pulse Transit Time) is known to be correlated with the blood pressure, and the blood pressure can be measured by calculating the PTT from the pulse waves. However, due to respiration and slight body movements, the pulse wave could be distorted, which makes it difficult to calculate PTT. To prevent the distortion of the pulse waves due to slight body movements and breathing, the conventional method requires a subject to lie down on a bed and to stop breathing. In this report, we propose a Doppler radar-based blood pressure measurement method that works against a subject not to move and breathe. To measure the blood pressure even from the distorted plus waves, in the proposed method, by relating features of the distorted pulse wave to those of the clean pulse wave using a deep learning model with LSTM (Long Short-Term Memory), the distorted pulse wave is transformed to a clean pulse wave that provides PTT correlated with the blood pressure strongly. The experimental results showed that the PTT calculated by the proposed method has a strong correlation with the actual blood pressure, and our proposal could estimate the blood pressure accurately, compared with the conventional method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Doppler radar / Non-contact blood pressure measurement / PTT (Pulse Transit Time) / Deep learning / Health care |
| Paper # | MICT2020-15,MI2020-41 |
| Date of Issue | 2020-10-28 (MICT, MI) |
| Conference Information | |
| Committee | MICT / MI |
|---|---|
| Conference Date | 2020/11/4(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Virtual (TBD) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical imaging technology, healthcare and medical information communication technology |
| Chair | Eisuke Hanada(Saga Univ.) / Yoshiki Kawata(Tokushima Univ.) |
| Vice Chair | Hirokazu Tanaka(Hiroshima City Univ.) / Daisuke Anzai(Nagoya Inst. of Tech.) / Takayuki Kitasaka(Aichi Inst. of Tech.) / Hidekata Hontani(Nagoya Inst. of Tech.) |
| Secretary | Hirokazu Tanaka(Kobe Univ.) / Daisuke Anzai(Yokohama National Univ.) / Takayuki Kitasaka(Yamaguchi Univ.) / Hidekata Hontani(Univ. of Hyogo) |
| Assistant | Keita Saku(Kyushu Univ.) / Kai Ishida(KISTEC) / Kento Takabayashi(Okayama Pref. Univ.) / Hotaka Takizawa(Tsukuba Univ.) / Yoshito Otake(NAIST) |
| Paper Information | |
| Registration To | Technical Committee on Healthcare and Medical Information Communication Technology / Technical Committee on Medical Imaging |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Non-contact Blood Pressure Measurement using Doppler Radar based on Waveform Analysis by LSTM |
| Sub Title (in English) | |
| Keyword(1) | Doppler radar |
| Keyword(2) | Non-contact blood pressure measurement |
| Keyword(3) | PTT (Pulse Transit Time) |
| Keyword(4) | Deep learning |
| Keyword(5) | Health care |
| 1st Author's Name | Shuzo Ishizaka |
| 1st Author's Affiliation | Keio University(Keio Univ.) |
| 2nd Author's Name | Kohei Yamamoto |
| 2nd Author's Affiliation | Keio University(Keio Univ.) |
| 3rd Author's Name | Tomoaki Ohtsuki |
| 3rd Author's Affiliation | Keio University(Keio Univ.) |
| Date | 2020-11-04 |
| Paper # | MICT2020-15,MI2020-41 |
| Volume (vol) | vol.120 |
| Number (no) | MICT-219,MI-220 |
| Page | pp.pp.36-41(MICT), pp.36-41(MI), |
| #Pages | 6 |
| Date of Issue | 2020-10-28 (MICT, MI) |