| Presentation | 2019-01-29 MUSIC Algorithm-based Heart Rate Estimation with Doppler Sensor Kohei Yamamoto, Kentaroh Toyoda, Tomoaki Ohtsuki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Heartbeat is one of the major signals that provide the crucial information on our health. Specifically, the HR (Heart Rate) is known to be highly related with our stress, which motivates researchers to develop HR estimation technique for the stress estimation. A Doppler sensor could be a device to facilitate the non-contact HR estimation. As one of Doppler sensor-based HR estimation methods, the MUSIC (MUltiple SIgnal Classification)-algorithm based HR estimation method has been proposed. However, the conventional MUSIC algorithm-based HR estimation method not only needs a long time window, but also requires to estimate the number of sinusoidal signals composing the analyzed signals, P, which is challenging. In this paper, we propose a novel MUSIC-based HR estimation method with the DCT (Discrete Cosine Transform)-based parameter P estimation. In the proposed method, the analyzed signal is firstly decomposed by DCT. P is then estimated by extracting components that might be related with heartbeats. The signal reconstruction is performed by the inverse DCT based on only such P components, which not only results in the reconstructed signal consisting of P sinusoidal signals, but also reduces the effect of the noise due to respiration and body movements within a time window so that the HR is estimated accurately even with a short time window. Finally, the HR is estimated by MUSIC with the estimated P. Through the experiments on 10 subjects, we confirmed that our method outperformed the conventional one by the estimation accuracy of the HR and the stress indexes such as CVI (Cardiac Vagal Index) and CSI (Cardiac Sympathetic Index). |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Doppler sensor / Heart rate estimation / Stress estimation / Health care |
| Paper # | ASN2018-89 |
| Date of Issue | 2019-01-21 (ASN) |
| Conference Information | |
| Committee | ASN |
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| Conference Date | 2019/1/28(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyuukamura Ibusuki |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Ambient intelligence, Sensor networks, Poster session, etc. |
| Chair | Hiraku Okada(Nagoya Univ.) |
| Vice Chair | Koji Yamamoto(Kyoto Univ.) / Jin Nakazawa(Keio Univ.) / Kazuya Monden(Hitachi) |
| Secretary | Koji Yamamoto(NICT) / Jin Nakazawa(Sophia Univ.) / Kazuya Monden(Kanagawa Inst. of Tech.) |
| Assistant | Masafumi Hashimoto(Osaka Univ.) / Tomoyuki Ota(Hiroshima City Univ.) / Tatsuya Kikuzuki(Fujitu Lab.) / Ryo Nakano(HITACHI) / Yoshifumi Hotta(Mitsubishi Electric) |
| Paper Information | |
| Registration To | Technical Committee on Ambient intelligence and Sensor Networks |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | MUSIC Algorithm-based Heart Rate Estimation with Doppler Sensor |
| Sub Title (in English) | |
| Keyword(1) | Doppler sensor |
| Keyword(2) | Heart rate estimation |
| Keyword(3) | Stress estimation |
| Keyword(4) | Health care |
| 1st Author's Name | Kohei Yamamoto |
| 1st Author's Affiliation | Keio University(Keio Univ.) |
| 2nd Author's Name | Kentaroh Toyoda |
| 2nd Author's Affiliation | Keio University(Keio Univ.) |
| 3rd Author's Name | Tomoaki Ohtsuki |
| 3rd Author's Affiliation | Keio University(Keio Univ.) |
| Date | 2019-01-29 |
| Paper # | ASN2018-89 |
| Volume (vol) | vol.118 |
| Number (no) | ASN-428 |
| Page | pp.pp.59-64(ASN), |
| #Pages | 6 |
| Date of Issue | 2019-01-21 (ASN) |