G. Arrobo, Calvin A. Perumalla, Stanley B. Hanke, T. Ketterl, P. Fabri, R. Gitlin
{"title":"An innovative wireless Cardiac Rhythm Management (iCRM) system","authors":"G. Arrobo, Calvin A. Perumalla, Stanley B. Hanke, T. Ketterl, P. Fabri, R. Gitlin","doi":"10.1109/WTS.2014.6835035","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a wireless Communicator to manage and enhance a Cardiac Rhythm Management System. The system includes: (1) an on-body wireless Electrocardiogram (ECG), (2) an Intracardiac Electrogram (EGM) embedded inside an Implantable Cardioverter/Defibrillator, and (3) a Communicator (with a resident Learning System). The first two devices are existing technology available in the market and are emulated using data from the Physionet database, while the Communicator was designed and implemented by our research team. The value of the information obtained by combining the information supplied by (1) and (2), presented to the Communicator, improves decision making regarding use of the actuator or other actions. Preliminary results show a high level of confidence in the decisions made by the Communicator. For example, excellent accuracy is achieved in predicting atrial arrhythmia in 8 patients using only external ECG when we used a neural network.","PeriodicalId":199195,"journal":{"name":"2014 Wireless Telecommunications Symposium","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Wireless Telecommunications Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WTS.2014.6835035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we propose a wireless Communicator to manage and enhance a Cardiac Rhythm Management System. The system includes: (1) an on-body wireless Electrocardiogram (ECG), (2) an Intracardiac Electrogram (EGM) embedded inside an Implantable Cardioverter/Defibrillator, and (3) a Communicator (with a resident Learning System). The first two devices are existing technology available in the market and are emulated using data from the Physionet database, while the Communicator was designed and implemented by our research team. The value of the information obtained by combining the information supplied by (1) and (2), presented to the Communicator, improves decision making regarding use of the actuator or other actions. Preliminary results show a high level of confidence in the decisions made by the Communicator. For example, excellent accuracy is achieved in predicting atrial arrhythmia in 8 patients using only external ECG when we used a neural network.