{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:53:37Z","timestamp":1773327217188,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T00:00:00Z","timestamp":1681171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01 HL126896"],"award-info":[{"award-number":["1R01 HL126896"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Clinical alarm and decision support systems that lack clinical context may create non-actionable nuisance alarms that are not clinically relevant and can cause distractions during the most difficult moments of a surgery. We present a novel, interoperable, real-time system for adding contextual awareness to clinical systems by monitoring the heart-rate variability (HRV) of clinical team members. We designed an architecture for real-time capture, analysis, and presentation of HRV data from multiple clinicians and implemented this architecture as an application and device interfaces on the open-source OpenICE interoperability platform. In this work, we extend OpenICE with new capabilities to support the needs of the context-aware OR including a modularized data pipeline for simultaneously processing real-time electrocardiographic (ECG) waveforms from multiple clinicians to create estimates of their individual cognitive load. The system is built with standardized interfaces that allow for free interchange of software and hardware components including sensor devices, ECG filtering and beat detection algorithms, HRV metric calculations, and individual and team alerts based on changes in metrics. By integrating contextual cues and team member state into a unified process model, we believe future clinical applications will be able to emulate some of these behaviors to provide context-aware information to improve the safety and quality of surgical interventions.<\/jats:p>","DOI":"10.3390\/s23083890","type":"journal-article","created":{"date-parts":[[2023,4,12]],"date-time":"2023-04-12T02:08:11Z","timestamp":1681265291000},"page":"3890","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring"],"prefix":"10.3390","volume":"23","author":[{"given":"David","family":"Arney","sequence":"first","affiliation":[{"name":"Medical Device Plug-and-Play Interoperability and Cybersecurity Program, Massachusetts General Hospital, Boston, MA 02115, USA"},{"name":"Department of Anaesthesia, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5375-360X","authenticated-orcid":false,"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Medical Device Plug-and-Play Interoperability and Cybersecurity Program, Massachusetts General Hospital, Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2696-3943","authenticated-orcid":false,"given":"Lauren R.","family":"Kennedy-Metz","sequence":"additional","affiliation":[{"name":"Department of Psychology, Roanoke College, Salem, VA 24153, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roger D.","family":"Dias","sequence":"additional","affiliation":[{"name":"STRATUS Center for Medical Simulation, Department of Emergency Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julian M.","family":"Goldman","sequence":"additional","affiliation":[{"name":"Medical Device Plug-and-Play Interoperability and Cybersecurity Program, Massachusetts General Hospital, Boston, MA 02115, USA"},{"name":"Department of Anaesthesia, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco A.","family":"Zenati","sequence":"additional","affiliation":[{"name":"Division of Cardiac Surgery, Veterans Affairs Boston Healthcare System, Department of Surgery, Brigham and Women\u2019s Hospital, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1161\/CIR.0b013e3182a38efa","article-title":"Patient safety in the cardiac operat ing room: Human factors and teamwork","volume":"128","author":"Wahr","year":"2013","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1038\/s41551-017-0132-7","article-title":"Surgical data science for next-generation interventions","volume":"1","author":"Vedula","year":"2017","journal-title":"Nat. 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