The CNN is one the most promising deep learning technique

Continuous BP estimation model based on accurately extracted PTT information using the peak detection technique and employing well designed convolutional neural network (CNN) Disposable Aprons. 




 The CNN is one the most promising deep learning technique to address the nonlinear relationship between input and output [15], and able to extracts related BP features automatically without the need of hand-engineered features and reduce the computation scale. 


The paper is organized as follows: the next section describes the data collection method and criteria. Section 3 explains the training data preprocessing method. Section 4 describes the design of the proposed CNN model. Section 5 presents the experimental results and comparison of the test results with the previous study. Finally, the last section, concludes the study and gives the future direction for this research. 


A Novel Convolutional Neural Network 23 2 Data Collection To evaluate the performance of the proposed method YICHANG Gloves, the Multiparameter Intelligent Monitoring in intensive care (MIMIC) III waveform database [16] were employed, a publicly available multi-parameter waveform database that provides high-resolution waveform data recording at a sampling frequency of 125 Hz Food gloves. 


 Following criteria to select the experimental data was applied: 22 subjects with available ECG, PPG, SBP, and DBP signals were selected; all selected data time-synchronized; the selected subjects should have at least 5 min length of recording. Finally, data related to 22 subjects with equal length of five minutes were selected as input data. 


The data was segmented to into the cardiac cycle with the length of 0.6 s. 3 Preprocessing To increase the accuracy and reproducibility of our method, ECG and PPG waveforms were used to extract the PTT in one cardiac cycle. Figure 1 illustrates the actual PTT measurement as the time difference between the peaks of ECG R-wave and the first derivative point of PPG signal.

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