Simulating Motion Artifact Using an Autoregressive Model for Research in Biomedical Signal Quality Analysis

2020 ◽  
Author(s):  
Emma Farago ◽  
Adrian D. C. Chan
Keyword(s):  
Autoregressive Model ◽  
Motion Artifact ◽  
Quality Analysis ◽  
Signal Quality ◽  
Biomedical Signal

Application of Biomedical Signal Acquisition Equipment in Human Sport Heart Rate Monitoring

2020 ◽  
Vol 10 (4) ◽  
pp. 877-883
Author(s):  
Le He
Keyword(s):  
Heart Rate ◽  
Motion Artifact ◽  
Human Motion ◽  
Signal Quality ◽  
Signal Acquisition ◽  
Heart Rate Monitoring ◽  
Artifact Removal ◽  
Biomedical Signal ◽  
Baseline Drift ◽  
Sensor Signals

Aiming at exploring biomedical signal acquisition equipment used in human motion heart rate monitoring, the research on the related hardware design and signal processing method was carried out. A biomedical signal acquisition device based on photoplethysmography (PPG) is designed, and the equipment was applied to acquire PPG signals and acceleration sensor signals under different motion states. The analysis of the experimental data showed that, the fusion method of the acceleration sensing information in the motion artifact removal method is perfected. The effectiveness of the baseline drift removal algorithm, motion artifact removal algorithm and dynamic heart rate monitoring algorithm was verified by reconstructing the signal quality evaluation index. To sum up, taking MINDRAY VS-800 as a reference device, it is compared with the adaptive filtering technology in terms of signal quality, BPM detection results and algorithm complexity, and better results are finally obtained.

scholarly journals An Effective Method to Denoiseeeg, ECG and PPG Signals based on Meyer Wavelet Transform

2018 ◽  
Vol 7 (3.34) ◽  
pp. 678
Author(s):  
P Thamarai ◽  
Dr K.Adalarasu
Keyword(s):  
Wavelet Transform ◽  
Adaptive Filter ◽  
Wavelet Decomposition ◽  
Motion Artifact ◽  
Signal Quality ◽  
Frequency Noise ◽  
Meyer Wavelet ◽  
Discrete Transform ◽  
Reference Input

In this analysis, the prevailing role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the constant and the discrete transform are considered in turn.A Wavelet denoising is functional on the original signal to eradicate high frequency noise, and then a process based on Meyer wavelet transform combined with adaptive filter is functional to eradicate the motion artifact. This approach uses Meyer Wavelet decomposition to extract the motion artifact, which is subsequently utilized as the reference input of an adaptive filter for noise cancellation. The technique diminishes the overhead of the circuit because it does not need a separate collection of reference input signal which link to noise. Testing results illustrate that this approach can efficiently remove motion artifact and make better the signal quality. 

Accurate Detection of ECG Signals in ECG Monitoring Systems by Eliminating the Motion Artifacts and Improving the Signal Quality Using SSG Filter with DBE

2019 ◽  
Vol 29 (02) ◽  
pp. 2050024
Author(s):  
Mahesh B. Dembrani ◽  
K. B. Khanchandani ◽  
Anita Zurani
Keyword(s):  
Signal Analysis ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Signal Quality ◽  
Ecg Signal ◽  
Qrs Complex ◽  
Ecg Signals ◽  
Cardiac Disorders ◽  
Digital Processor ◽  
Ica Algorithm

The automatic recognition of QRS complexes in an Electrocardiography (ECG) signal is a critical step in any programmed ECG signal investigation, particularly when the ECG signal taken from the pregnant women additionally contains the signal of the fetus and some motion artifact signals. Separation of ECG signals of mother and fetus and investigation of the cardiac disorders of the mother are demanding tasks, since only one single device is utilized and it gets a blend of different heart beats. In order to resolve such problems we propose a design of new reconfigurable Subtractive Savitzky–Golay (SSG) filter with Digital Processor Back-end (DBE) in this paper. The separation of signals is done using Independent Component Analysis (ICA) algorithm and then the motion artifacts are removed from the extracted mother’s signal. The combinational use of SSG filter and DBE enhances the signal quality and helps in detecting the QRS complex from the ECG signal particularly the R peak accurately. The experimental results of ECG signal analysis show the importance of our proposed method.

Research of Mobile Terminal QOS Analysis Model Based on Time and Location

2012 ◽  
Vol 263-266 ◽  
pp. 1008-1011
Author(s):  
Xiao Ming Bai ◽  
Lin Lai
Keyword(s):  
Mobile Terminal ◽  
The Other ◽  
Quality Analysis ◽  
Signal Quality ◽  
Analysis Model ◽  
Communication Industry ◽  
Related Data ◽  
Model Based ◽  
Network Quality

With the communication industry becoming more and more competitive, the communication operators is paying more and more attentions on the network quality. The paper proposed the terminal signal quality analysis model based on the time and location which uses the technology of the terminal routing tracking and the signal data analysising.The model starting with the time and location,combines with the signal data of the station and the terminal,associates to related data of the other systems,come to the signal qality of the terminal during the move.

scholarly journals BeiDou 3 Signal Quality Analysis and its Impact on Users

2019 ◽  
Author(s):  
Steffen Thoelert ◽  
Felix Antreich ◽  
Christoph Enneking ◽  
Michael Meurer
Keyword(s):  
Quality Analysis ◽  
Signal Quality
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