An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring
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 aware...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/8/3890 |
| _version_ | 1797603521313374208 |
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| author | David Arney Yi Zhang Lauren R. Kennedy-Metz Roger D. Dias Julian M. Goldman Marco A. Zenati |
| author_facet | David Arney Yi Zhang Lauren R. Kennedy-Metz Roger D. Dias Julian M. Goldman Marco A. Zenati |
| author_sort | David Arney |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T04:33:18Z |
| format | Article |
| id | doaj.art-af2c1c8ae83640f38abcd59ee40a380e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T04:33:18Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-af2c1c8ae83640f38abcd59ee40a380e2023-11-17T21:16:04ZengMDPI AGSensors1424-82202023-04-01238389010.3390/s23083890An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability MonitoringDavid Arney0Yi Zhang1Lauren R. Kennedy-Metz2Roger D. Dias3Julian M. Goldman4Marco A. Zenati5Medical Device Plug-and-Play Interoperability and Cybersecurity Program, Massachusetts General Hospital, Boston, MA 02115, USAMedical Device Plug-and-Play Interoperability and Cybersecurity Program, Massachusetts General Hospital, Boston, MA 02115, USADepartment of Psychology, Roanoke College, Salem, VA 24153, USASTRATUS Center for Medical Simulation, Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USAMedical Device Plug-and-Play Interoperability and Cybersecurity Program, Massachusetts General Hospital, Boston, MA 02115, USADivision of Cardiac Surgery, Veterans Affairs Boston Healthcare System, Department of Surgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USAClinical 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.https://www.mdpi.com/1424-8220/23/8/3890surgical data scienceinteroperabilitycognitive loadsmart alarmsheart-rate variability |
| spellingShingle | David Arney Yi Zhang Lauren R. Kennedy-Metz Roger D. Dias Julian M. Goldman Marco A. Zenati An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring Sensors surgical data science interoperability cognitive load smart alarms heart-rate variability |
| title | An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring |
| title_full | An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring |
| title_fullStr | An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring |
| title_full_unstemmed | An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring |
| title_short | An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring |
| title_sort | open source interoperable architecture for generating real time surgical team cognitive alerts from heart rate variability monitoring |
| topic | surgical data science interoperability cognitive load smart alarms heart-rate variability |
| url | https://www.mdpi.com/1424-8220/23/8/3890 |
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