Publications

@inproceedings{Meher2024PDME,

title = {Acquisition and Synchronisation of Cardiography Signals from a Clinical Patient Monitor with Facial Video Recordings},

author = {Jagmohan Meher and Chien-Chih Wang and Torbjörn E. M. Nordling},

editor = {Esteban Pino and Ratko Magjarević and Paulo Carvalho},

url = {https://doi.org/10.1007/978-3-031-59216-4_28},

isbn = {978-3-031-59216-4},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-01},

booktitle = {International Conference on Biomedical and Health Informatics 2022},

pages = {254–261},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {A far too frequent practical challenge in clinical informatics research and method development for acquiring vital signs is the extraction and synchronisation of signals from proprietary devices for the clinical monitoring of patients. In an ongoing study evaluating methods for video-based remote photoplethysmography (rPPG), we needed to extract ground truth values of electrocardiogram (ECG) and pulse oximetry (SpO2) signals from the Philips vitals monitor while recording the facial video of the subject, simultaneously. This ground truth data will be used to train the model that will perform rPPG. Various software can extract data from the Philips vitals monitor with features like data acquisition, parsing, and visualisation, but they lack synchronisation with the facial video. Therefore, we developed the Patient Monitor Data Extractor (PMDE), which collects data from the Philips IntelliVue monitors following the Data export interface programming guide provided by Philips. We set up a DHCP server on a Windows 7 computer with a webcam and interfaced with the monitor through LAN with UDP/IP. We used C++ and Windows Sockets API to develop our software and communicate over UDP. For synchronisation with the video cameras, we turned off the light in the room and used this sudden brightness drop as a trigger. The timestamp of the monitor was recorded when the webcam detected the trigger. The PMDE software records ECG at 500 Hz and SpO2 at 125 Hz with a synchronisation error of less than two sampling periods, which is about 40 ms for a 50 fps video. We conclude that PMDE is uniquely suited for recording data for rPPG evaluation because of its synchronisation feature. We have used PMDE to collect a dataset of facial videos with ground truth ECG and SpO2 signals. We intend to make PMDE available as open source to save other researchers time.},

keywords = {Clinical informatics, data extraction, patient monitor, Philips IntelliVue, remote photoplethysmography (rPPG), Software, vital signs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Meher2022Sync,

title = {Acquisition and synchronisation of cardiography signals from a clinical patient monitor with facial video recordings},

author = {Torbjörn Nordling Jagmohan Meher Chien-Chih Wang},

editor = {Ratko Magjarevic},

year  = {2022},

date = {2022-11-01},

booktitle = {Proceedings of the International Conference on Health and Bioinformatics 2022 (ICBHI2022)},

publisher = {University of Concepcion},

address = {Concepcion, Chile},

series = {IFMBE Proceedings},

abstract = {A far too frequent practical challenge in clinical informatics research and method development for acquiring vital signs is the extraction and synchronisation of signals from proprietary devices for the clinical monitoring of patients. In an ongoing study evaluating methods for video-based remote photoplethysmography (rPPG), we needed to extract ground truth values of electrocardiogram (ECG) and pulse oximetry (SpO2) signals from the Philips vitals monitor while recording the facial video of the subject, simultaneously. This ground truth data will be used to train the model that will perform rPPG. Various software can extract data from the Philips vitals monitor with features like data acquisition, parsing, and visualisation, but they lack synchronisation with the facial video. Therefore, we developed the Patient Monitor Data Extractor (PMDE), which collects data from the Philips IntelliVue monitors following the Data export interface programming guide provided by Philips. We set up a DHCP server on a Windows 7 computer with a webcam and interfaced with the monitor through LAN with UDP/IP. We used C++ and Windows Sockets API to develop our software and communicate over UDP. For synchronisation with the video cameras, we turned off the light in the room and used this sudden brightness drop as a trigger.The timestamp of the monitor was recorded when the webcam detected the trigger. The PMDE software records ECG at 500 Hz and SpO2 at 125 Hz with a synchronisation error of less than two sampling periods, which is about 40 ms for a 50 fps video. We conclude that PMDE is uniquely suited for recording data for rPPG evaluation because of its synchronisation feature. We have used PMDE to collect a dataset of facial videos with ground truth ECG and SpO2 signals. We intend to make PMDE available as open source to save other researchers time.},

howpublished = {The International Conference on Health and Bioinformatics 2022 (ICBHI2022) at University of Concepcion, Concepcion, Chile 24-26 Nov. 2022},

keywords = {Clinical informatics, data extraction, patient monitor, Philips IntelliVue, remote photoplethysmography (rPPG), Software, vital signs},

pubstate = {published},

tppubtype = {inproceedings}

}