Non-contact Blood Pressure Estimation By Microwave Reflection Employing Machine Learning

研究成果: Conference article査読

抄録

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.

本文言語English
ページ(範囲)889-892
ページ数4
ジャーナルProceedings - IEEE Consumer Communications and Networking Conference, CCNC
DOI
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 82022 1月 11

ASJC Scopus subject areas

  • 人工知能
  • 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
  • 電子工学および電気工学

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