{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T14:19:26Z","timestamp":1779373166407,"version":"3.53.1"},"reference-count":43,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000182","name":"US Army Medical Research and Materiel Command","doi-asserted-by":"publisher","award":["W81XWH-18-C-0111"],"award-info":[{"award-number":["W81XWH-18-C-0111"]}],"id":[{"id":"10.13039\/100000182","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wireless wearable sensor systems for biomedical signal acquisition have developed rapidly in recent years. Multiple sensors are often deployed for monitoring common bioelectric signals, such as EEG (electroencephalogram), ECG (electrocardiogram), and EMG (electromyogram). Compared with ZigBee and low-power Wi-Fi, Bluetooth Low Energy (BLE) can be a more suitable wireless protocol for such systems. However, current time synchronization methods for BLE multi-channel systems, via either BLE beacon transmissions or additional hardware, cannot satisfy the requirements of high throughput with low latency, transferability between commercial devices, and low energy consumption. We developed a time synchronization and simple data alignment (SDA) algorithm, which was implemented in the BLE application layer without the need for additional hardware. We further developed a linear interpolation data alignment (LIDA) algorithm to improve upon SDA. We tested our algorithms using sinusoidal input signals at different frequencies (10 to 210 Hz in increments of 20 Hz\u2014frequencies spanning much of the relevant range of EEG, ECG, and EMG signals) on Texas Instruments (TI) CC26XX family devices, with two peripheral nodes communicating with one central node. The analysis was performed offline. The lowest average (\u00b1standard deviation) absolute time alignment error between the two peripheral nodes achieved by the SDA algorithm was 384.3 \u00b1 386.5 \u03bcs, while that of the LIDA algorithm was 189.9 \u00b1 204.7 \u03bcs. For all sinusoidal frequencies tested, the performance of LIDA was always statistically better than that of SDA. These average alignment errors were quite low\u2014well below one sample period for commonly acquired bioelectric signals.<\/jats:p>","DOI":"10.3390\/s23052465","type":"journal-article","created":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T04:32:33Z","timestamp":1677126753000},"page":"2465","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol"],"prefix":"10.3390","volume":"23","author":[{"given":"He","family":"Wang","sequence":"first","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianan","family":"Li","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8657-4213","authenticated-orcid":false,"given":"Benjamin E.","family":"McDonald","sequence":"additional","affiliation":[{"name":"Liberating Technologies, Inc. (LTI), Holliston, MA 01746, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Todd R.","family":"Farrell","sequence":"additional","affiliation":[{"name":"Liberating Technologies, Inc. (LTI), Holliston, MA 01746, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0584-3448","authenticated-orcid":false,"given":"Xinming","family":"Huang","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0729-2523","authenticated-orcid":false,"given":"Edward A.","family":"Clancy","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TSMCC.2009.2032660","article-title":"A survey on wearable sensor-based systems for health monitoring and prognosis","volume":"40","author":"Pantelopoulos","year":"2009","journal-title":"IEEE Trans. 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