{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T15:07:56Z","timestamp":1793718476656,"version":"4.6.1"},"reference-count":38,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Foundation Engineering Research Center (NSF\u2014ERC) Precise Advanced Technologies and Health Systems for Under-resourced Populations (PATHS-UP)","award":["ERC\u20141648451"],"award-info":[{"award-number":["ERC\u20141648451"]}]},{"name":"National Science Foundation Engineering Research Center (NSF\u2014ERC) Precise Advanced Technologies and Health Systems for Under-resourced Populations (PATHS-UP)","award":["2037383"],"award-info":[{"award-number":["2037383"]}]},{"DOI":"10.13039\/100000001","name":"NSF SenSE: Multimodal sensor systems for precision health enabled by data harnessing, artificial intelligence, and learning","doi-asserted-by":"publisher","award":["ERC\u20141648451"],"award-info":[{"award-number":["ERC\u20141648451"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF SenSE: Multimodal sensor systems for precision health enabled by data harnessing, artificial intelligence, and learning","doi-asserted-by":"publisher","award":["2037383"],"award-info":[{"award-number":["2037383"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biosensors"],"abstract":"<jats:p>Many commercial wearable sensor systems typically rely on a single continuous cardiorespiratory sensing modality, photoplethysmography (PPG), which suffers from inherent biases (i.e., differences in skin tone) and noise (e.g., motion and pressure artifacts). In this research, we present a wearable device that provides robust estimates of cardiorespiratory variables by combining three physiological signals from the upper arm: multiwavelength PPG, single-sided electrocardiography (SS-ECG), and bioimpedance plethysmography (BioZ), along with an inertial measurement unit (IMU) providing 3-axis accelerometry and gyroscope information. We evaluated the multimodal device on 16 subjects by its ability to estimate heart rate (HR) and breathing rate (BR) in the presence of various static and dynamic noise sources (e.g., skin tone and motion). We proposed a hierarchical approach that considers the subject\u2019s skin tone and signal quality to select the optimal sensing modality for estimating HR and BR. Our results indicate that, when estimating HR, there is a trade-off between accuracy and robustness, with SS-ECG providing the highest accuracy (low mean absolute error; MAE) but low reliability (higher rates of sensor failure), and PPG\/BioZ having lower accuracy but higher reliability. When estimating BR, we find that fusing estimates from multiple modalities via ensemble bagged tree regression outperforms single-modality estimates. These results indicate that multimodal approaches to cardiorespiratory monitoring can overcome the accuracy\u2013robustness trade-off that occurs when using single-modality approaches.<\/jats:p>","DOI":"10.3390\/bios15080493","type":"journal-article","created":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T07:49:58Z","timestamp":1754380198000},"page":"493","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Robust Prediction of Cardiorespiratory Signals from a Multimodal Physiological System on the Upper Arm"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6332-4200","authenticated-orcid":false,"given":"Kimberly L.","family":"Branan","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3762-1962","authenticated-orcid":false,"given":"Rachel","family":"Kurian","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7237-6966","authenticated-orcid":false,"given":"Justin P.","family":"McMurray","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0017-5866","authenticated-orcid":false,"given":"Madhav","family":"Erraguntla","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ricardo","family":"Gutierrez-Osuna","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Texas A&M University, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3164-9625","authenticated-orcid":false,"given":"Gerard L.","family":"Cot\u00e9","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA"},{"name":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA"},{"name":"Texas A&M Engineering Experiment Station, Center for Remote Health Technologies and Systems, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fine, J., Branan, K.L., Rodriguez, A.J., Boonya-Ananta, T., Ramella-Roman, J.C., McShane, M.J., and Cot\u00e9, G.L. 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