Researches On The Hand-Held Atrial Fibrillation Detection System

As one of the most common cardiac arrhythmias,atrial fibrillation(AF)has become a global epidemic.The current prevalence of AF in adults is between 2% and 4% and is increasing year by year.Regular screening and postoperative monitoring of AF is of great help in improving the diagnosis rate of AF and reducing the further deterioration of the patient’s condition.The handheld AF detection system is designed for daily AF monitoring or early screening of AF in the hospital.Firstly,the background of AF morbidity and mortality is described,and the importance of AF detection is pointed out.However,typical single-lead handheld Electrocardiogram(ECG)devices,ECG electrodes,and AF detection algorithms have shortcomings.Therefore,a singlelead handheld ECG device based on fabric electrodes,and a rule-based multi-feature AF detection algorithm are proposed as two technical solutions of the system.Secondly,the hardware and software design of the single-lead handheld ECG device are introduced.The key technologies include the ECG acquisition module based on ADS1299,the microcontroller based on STM32F103C8,the Bluetooth communication module based on HC05,the data storage module based on TF card,and the power management module based on TP4057 and TPS73233.Combined with 3D printing technology,the design of the handle shell is completed.The part of software mainly realizes the functions of initialization,ECG signal acquisition,and data encapsulation and transmission.Then,the software design of the Android client mainly includes Bluetooth connection,data decoding,filtering,dynamic and real-time display of ECG,and AF detection.The rulebased multi-feature AF detection algorithm has four key technologies.The QRS wave detection algorithm uses the difference method,which has an excellent real-time R wave positioning effect.The feature optimization screens out features with strong anti-interference ability from multiple AF features.The optimal threshold of AF features is found with the help of the receiver operating characteristic curve.The rule-based multi-feature AF classification rules are formulated according to the above results.Finally,the system verification and tests are conducted to prove the system’s reliability.Through 30 sets of comparative data,it is proved that the proposed device is highly consistent with standard ECG devices.Meanwhile,based on MIT-BIH AF database and the clinical wearable AF database,the AF detection algorithm is proved to have good accuracy,lightness and real-time performance,basically meeting the needs of AF monitoring.