Why the study?
Traditional cardiac function monitoring devices are large and cannot provide wireless remote monitoring, limiting real-time cardiac assessment and management.
Wearable ECG, respiration, blood pressure, blood oxygen, body temperature, blood sugar multiparameter monitoring devices with wireless remote monitoring function is of great significance for the assessment of cardiovascular health and detection of acute myocardial ischemia and yocardial infarction,and clinical management of critically ill patients or surgical patients1,2,3,4,5. However, due to the large size of traditional devices, traditional cardiac function monitoring methods cannot provide wireless remote monitoring1,2,3,6,7,8. Here we report a wearable patch-type multi-lead ECG multiparameter monitoring instrument3,4,5 and its new-type wireless remote connected ecosystem9,10,11,12 for wireless remote cardiac function assessment. We describe innovations in the design and material manufacturing of the devices that allow a complete one-time remote real-time examination of the patient's left ventricle and its posterior wall, right ventricle from different angles. We propose an new-type wireless remote connected ecosystem based on the B/S architecture (Browser-Server Mode) of the Wide Area Network covering all clinical application scenarios and medical services items13 of the cardiac cardiovascular system. We developed a complete set of AI detection and diagnosis models that automatically classifies common 28 categories of cardiovascular health and disease. This technology can realize wireless remote cardiac function monitoring and diagnosis, greatly improving the accuracy of ECG multiparameter monitoring diagnosis.
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Zhang et al. (2023) studied Healthy volunteers (n=158). Patch-type Multi-lead Electrocardio Multiparameter Monitoring Diagnostic Instrument vs. Traditional desktop 16-electrode 18-lead ECG machine was evaluated on Accuracy of human motion classification using XGBoost algorithm.
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