{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:00:22Z","timestamp":1762866022179,"version":"build-2065373602"},"reference-count":16,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2012,7,31]],"date-time":"2012-07-31T00:00:00Z","timestamp":1343692800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Background: Human life can be further improved if diseases and disorders can be predicted before they become dangerous, by correctly recognizing signals from the human body, so in order to make disease detection more precise, various body-signals need to be measured simultaneously in a synchronized manner. Object: This research aims at developing an integrated system for measuring four signals (EEG, ECG, respiration, and PPG) and simultaneously producing synchronous signals on a Wireless Body Sensor Network. Design: We designed and implemented a platform for multiple bio-signals using Bluetooth communication. Results: First, we developed a prototype board and verified the signals from the sensor platform using frequency responses and quantities. Next, we designed and implemented a lightweight, ultra-compact, low cost, low power-consumption Printed Circuit Board. Conclusion: A synchronous multi-body sensor platform is expected to be very useful in telemedicine and emergency rescue scenarios. Furthermore, this system is expected to be able to analyze the mutual effects among body signals.<\/jats:p>","DOI":"10.3390\/s120810381","type":"journal-article","created":{"date-parts":[[2012,7,31]],"date-time":"2012-07-31T10:44:19Z","timestamp":1343731459000},"page":"10381-10394","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A Synchronous Multi-Body Sensor Platform in a Wireless Body Sensor Network: Design and Implementation"],"prefix":"10.3390","volume":"12","author":[{"given":"Yeongjoon","family":"Gil","sequence":"first","affiliation":[{"name":"Graduate School of Computer Science and Engineering, Pusan National University, Pusan 609-735, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanqing","family":"Wu","sequence":"additional","affiliation":[{"name":"Graduate School of Computer Science and Engineering, Pusan National University, Pusan 609-735, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jungtae","family":"Lee","sequence":"additional","affiliation":[{"name":"Graduate School of Computer Science and Engineering, Pusan National University, Pusan 609-735, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"R27","DOI":"10.1088\/0967-3334\/29\/11\/R01","article-title":"Wireless body sensor networks for health-monitoring applications","volume":"29","author":"Hao","year":"2008","journal-title":"Physiol. Meas."},{"key":"ref_2","first-page":"307","article-title":"System architecture of a wireless body area sensor network for ubiquitous health monitoring","volume":"1","author":"Otto","year":"2006","journal-title":"J. Mobile Multimed."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1007\/s10916-009-9304-7","article-title":"ECG\/PPG integer signal processing for a ubiquitous health monitoring system","volume":"34","author":"Shin","year":"2009","journal-title":"J. Med. Syst."},{"key":"ref_4","unstructured":"Li, Y., Li, X., Ratcliffe, M., Liu, L., Qi, Y., and Liu, Q. A Real-Time EEG-Based BCI System for Attention Recognition in Ubiquitous Environment."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Wu, W., Lee, J., and Chen, H. (2009, January 3\u20136). Estimation of Heart Rate Variability Changes during Different Visual Stimulations Using Non-invasive Continuous ECG Monitoring System. 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