A Patient-Adaptive ECG Measurement System for Fault-Tolerant Diagnoses of Heart Abnormalities

The present paper proposes an original smart and patient-adaptive electrocardiogram (ECG) measurement system. The projected instrument is able to configure the embedded diagnosis models according to the available information about patient to be tested. In details, a removable and updatable memory device is used to store the clinical and personal patient data. An additional internal and read-only memory stores information on the metrological status of the measurement system. So, the electrical activity of heart is measured and analyzed in order to characterize possible abnormalities of its regular working. Main feature of the present contribution is to provide a practical solution in the design of smart medical instrumentation for fault-tolerant diagnoses. In fact, the innovative contribution is due to embedded information on the system metrological performances and on patient data. So the implemented system is able to diagnose possible cardiac arrhythmias occurrences reducing the happening of faults. In this way, according to personal data and historical medical information of patient, the measurement system adapts itself by selecting the best fit ECG model as reference, so to configure the computing algorithm. Further information on the measurement uncertainty is used in order to qualify the reliability of the final clinical response.