Research On Wearable ECG Monitoring System Based On Mobile MIOT And Its Application In The Auxiliary Osis Of Cardiovascular Disease

Non-communicable chronic diseases(NCD)has now becoming an leading disease and is showing a younger trend.Most cardiovascular diseases are chronic diseases,and cardiovascular death account for more than 40%of urban and rural residents' disease death.Compared with traditional clinical monitoring,wearable ECG monitoring system based on mobile medical Internet of Things can monitor long-term changes of the overall state of the human body,achieve daily monitoring of the modern population without significant organic heart disease,provide more intelligent auxiliary treatment methods for professionals.This paper mainly do the following research:1.Research on the wearable ECG monitoring system based on mobile medical Internet of Things,including hardware construction and software design,realizing real-time communication among signal acquisition front-end,mobile relay and cloud platform.The signal acquisition front end realizes the synchronous collection of 12-lead human ECG signals and six-axis acceleration signals.The data is packaged and transmitted to the mobile relay in the form of MODBUS communication protocol.The mobile relay is a one-to-many extensible intermediate platform and supports multiple communication modes,which is responsible for transmitting data to cloud platform according to the MQTT protocol.The system realizes real-time communication between the sensor and the mobile relay,the mobile relay and the cloud platform.2.Double density wavelet algorithm is used for signal denoising and make use of multilevel attitude recognition classification method to flag the status of ECG signal under different motion state for preventing misjudgment,assists distinguishing motion artifacts from ectopic heartbeatsBy threshold adjustment and comparision,obtain double density wavelet denoising algorithm more suitable for this system A gesture recognition classification model combining threshold method and morphological features differentiates body posture quickly.The result is calibrated by using insertion null judgment strategy and used to mark wearable 12-lead ECG signal to prevent misjudging,which assists the professional to distinguish motion artifacts from ectopic heartbeats.3.Apply the wearable ECG monitoring system in P wave recognition,provide reference for the diagnosis of cardiovascular disease caused by atrial lesions.A P-wave detection method based on double-density wavelet transform is proposed.Calculate the P-wave time limit and P-wave dispersion degree of best 3-lead and wearable 12-lead ECG signals in the motion and static state,the result indicates that compared with the best 3-lead,12-lead system can accurately reflect the P wave state,provide reference for the diagnosis of for the diagnosis of cardiovascular disease caused by atrial lesions.This system has certain application value in the monitoring of cardiovascular health status in the daily life of the general population.