In recent years, hypertension has become a leading cause of diseases worldwide. Despite the recommendation from medical experts to measure blood pressure on a daily basis, only a small few do so. The main reason for this is that the typical measurement method using a cuff is physiologically stressful for many, especially for physically handicapped people, and the elderly. In order to eliminate the burden during measurement, a non-contact method for monitoring blood pressure is necessary. This paper proposes a non-contact method to detect the human pulse and in turn, estimate blood pressure. In the experiment, 2.4GHz microwave signals were transmitted against, and reflected from the body, upon which the time-varying reflection intensity was acquired. Pulse rates are first estimated via post-processing of acquired raw data. Blood pressure is then estimated via Machine Learning (ML) methods with parameter values derived from the detected pulse waveform. Experiments indicate that our proposed method is practical and has great potential for future smart health solutions.
|ジャーナル||Proceedings - IEEE Consumer Communications and Networking Conference, CCNC|
|出版ステータス||Published - 2022|
|イベント||19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022 - Virtual, Online, United States|
継続期間: 2022 1月 8 → 2022 1月 11
ASJC Scopus subject areas
- コンピュータ ネットワークおよび通信
- コンピュータ ビジョンおよびパターン認識