The opportunity for cardiac patients to have constantly monitored their health state at home is now possible by means of telemedicine applications. In fact, today, portable and simple-to-use devices allow one to get preliminary domestic diagnoses of the heart status. In this paper, the authors present an original ECG measurement system based on web-service-oriented architecture to monitor the heart health of cardiac patients. The projected device is a smart patient-adaptive system able to provide personalized diagnoses by using personal data and clinical history of the monitored patient. In the presence of a pathology occurrence, the system is able to call the emergency service for assistance. An ECG sensor has the task to acquire, condition, and sample the heart electrical impulses, whereas a personal digital assistant (PDA) performs the diagnosis according to the measurement uncertainty and, in case of a critical situation, calls the medical staff. The system has two removable and updatable memory devices: the first memory device stores the clinical and personal data of the patient, and the second memory device stores information on the metrological status of the measurement system. This way, according to the personal data and historical information of the patient, the measurement system adapts itself by selecting the best fitted ECG model as a reference to configure the computing algorithm. Further information on the measurement uncertainty is used to qualify the reliability of the final clinical response to reduce the occurrence of a faulty diagnosis. Through the PDA graphic interface, the user can display his personal data, observe the graph of his ECG signal, and read diagnosis information with the relative reliability level. Moreover, the patient can choose to print his ECG graph through a Bluetooth printer or to send it to a specialist by a General Packet Radio Service (GPRS) modem.

A Smart ECG Measurement System Based on Web-Service-Oriented Architecture for Telemedicine Applications

DE CAPUA C.;MORELLO R.
2010-01-01

Abstract

The opportunity for cardiac patients to have constantly monitored their health state at home is now possible by means of telemedicine applications. In fact, today, portable and simple-to-use devices allow one to get preliminary domestic diagnoses of the heart status. In this paper, the authors present an original ECG measurement system based on web-service-oriented architecture to monitor the heart health of cardiac patients. The projected device is a smart patient-adaptive system able to provide personalized diagnoses by using personal data and clinical history of the monitored patient. In the presence of a pathology occurrence, the system is able to call the emergency service for assistance. An ECG sensor has the task to acquire, condition, and sample the heart electrical impulses, whereas a personal digital assistant (PDA) performs the diagnosis according to the measurement uncertainty and, in case of a critical situation, calls the medical staff. The system has two removable and updatable memory devices: the first memory device stores the clinical and personal data of the patient, and the second memory device stores information on the metrological status of the measurement system. This way, according to the personal data and historical information of the patient, the measurement system adapts itself by selecting the best fitted ECG model as a reference to configure the computing algorithm. Further information on the measurement uncertainty is used to qualify the reliability of the final clinical response to reduce the occurrence of a faulty diagnosis. Through the PDA graphic interface, the user can display his personal data, observe the graph of his ECG signal, and read diagnosis information with the relative reliability level. Moreover, the patient can choose to print his ECG graph through a Bluetooth printer or to send it to a specialist by a General Packet Radio Service (GPRS) modem.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/3737
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 123
  • ???jsp.display-item.citation.isi??? 94
social impact