Design And Implementation Of ECG And EEG Monitoring And Bio-feedback Training System Based On Wireless Transmission

With the progress of society,people's attention to physical and mental health has gradually become higher.Biofeedback has become the focus of physical and mental health program.This technique is widely used to train attention,emotional or relaxation.However,most of the monitoring equipment produced in foreign countries,which is expensive,consuming huge storage space,cumbersome operation,making bio-feedback training is difficult to promote in the general public.Therefore,independent research of biofeedback system has important significance.The main contents and innovations of the paper include the following three aspects:(1)The paper uses heart rate variability,EEG signal as the physiological signal of biofeedback training.The heart and brain signals were pretreated using the corresponding high-pass,low-pass and band-pass filters.The HRV signal was obtained by using the difference threshold method.The HRV frequency domain features were analyzed by Welch method,and the frequency domain characteristics of EEG were analyzed by FFT transform.(2)The paper designs the attention feedback training experiment based on heart rate variability and EEG signal,including the experimental method,process and experimental result and analysis.The experiment was conducted to analyze the mental stress of the subjects under the different parameters of the training process.The validity of the experiment,the correlation between the experimental data and the persistence of the experimental results were analyzed.(3)Design and implement a set of mobile health monitoring system that can collect ECG signals,EEG signals and carry out biofeedback training,dynamic ECG monitoring and motion monitoring,including: collection of physiological signals at the collection end,mobile terminal Data receiving and decoding,uploading and downloading,real-time waveform display and analysis,historical return visit and biofeedback function training,dynamic ECG,motion status detection function,cloud platform side physiological data,test records summary,statistics,display and storage.