{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:04:25Z","timestamp":1775066665990,"version":"3.50.1"},"reference-count":35,"publisher":"Wiley","license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Aichi Science & Technology Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>Measuring blood pressure continuously helps monitor health and also prevent lifestyle related diseases to extend the expectancy of healthy life. Blood pressure, which is nowadays used for monitoring patient, is one of the most useful indexes for prevention of lifestyle related diseases such as hypertension. However, continuously monitoring the blood pressure is unrealistic because of discomfort caused by the tightening of a cuff belt. We have earlier researched the data-oriented blood pressure estimation without using a cuff. Remarkably, our blood pressure estimation method only uses a photoplethysmograph sensor. Therefore, the application is flexible for sensor locations and measuring situations. In this paper, we describe the implementation of our estimation method, the launch of a cloud system which can collect and manage blood pressure data measured by a wristwatch-type photoplethysmograph sensor, and the construction of our applications to visualize life-log data including the time-series data of blood pressure.<\/jats:p>","DOI":"10.1155\/2017\/1803485","type":"journal-article","created":{"date-parts":[[2017,4,24]],"date-time":"2017-04-24T17:01:13Z","timestamp":1493053273000},"page":"1-10","source":"Crossref","is-referenced-by-count":32,"title":["Cuffless Blood Pressure Estimation Based on Data-Oriented Continuous Health Monitoring System"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5278-0238","authenticated-orcid":true,"given":"Kengo","family":"Atomi","sequence":"first","affiliation":[{"name":"Graduate School of Information Science and Technology, Aichi Prefectural University, Aichi, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haruki","family":"Kawanaka","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Technology, Aichi Prefectural University, Aichi, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8983-0876","authenticated-orcid":true,"given":"Md. 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