scholarly journals A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1596 ◽  
Author(s):  
Shuai Yu ◽  
Sheng Liu
Keyword(s):  
Heart Rate ◽  
Least Squares ◽  
Motion Artifact ◽  
Recursive Least Squares ◽  
Detection Accuracy ◽  
Artifact Removal ◽  
Ecg Signals ◽  
The Right ◽  
Electrocardiogram Ecg ◽  
Recursive Least Squares Filter

This paper presents a novel adaptive recursive least squares filter (ARLSF) for motion artifact removal in the field of seismocardiography (SCG). This algorithm was tested with a consumer-grade accelerometer. This accelerometer was placed on the chest wall of 16 subjects whose ages ranged from 24 to 35 years. We recorded the SCG signal and the standard electrocardiogram (ECG) lead I signal by placing one electrode on the right arm (RA) and another on the left arm (LA) of the subjects. These subjects were asked to perform standing and walking movements on a treadmill. ARLSF was developed in MATLAB to process the collected SCG and ECG signals simultaneously. The SCG peaks and heart rate signals were extracted from the output of ARLSF. The results indicate a heartbeat detection accuracy of up to 98%. The heart rates estimated from SCG and ECG are similar under both standing and walking conditions. This observation shows that the proposed ARLSF could be an effective method to remove motion artifact from recorded SCG signals.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

scholarly journals Novel Stable Capacitive Electrocardiogram Measurement System

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3668
Author(s):  
Chi-Chun Chen ◽  
Shu-Yu Lin ◽  
Wen-Ying Chang
Keyword(s):  
Measurement System ◽  
Input Resistance ◽  
Voltage Divider ◽  
Motion Artifact ◽  
Guard Ring ◽  
Capacitive Sensing ◽  
Ecg Signals ◽  
Optimal Input ◽  
Electrocardiogram Ecg ◽  
Mode Interference

This study presents a noncontact electrocardiogram (ECG) measurement system to replace conventional ECG electrode pads during ECG measurement. The proposed noncontact electrode design comprises a surface guard ring, the optimal input resistance, a ground guard ring, and an optimal voltage divider feedback. The surface and ground guard rings are used to reduce environmental noise. The optimal input resistor mitigates distortion caused by the input bias current, and the optimal voltage divider feedback increases the gain. Simulated gain analysis was subsequently performed to determine the most suitable parameters for the design, and the system was combined with a capacitive driven right leg circuit to reduce common-mode interference. The present study simulated actual environments in which interference is present in capacitive ECG signal measurement. Both in the case of environmental interference and motion artifact interference, relative to capacitive ECG electrodes, the proposed electrodes measured ECG signals with greater stability. In terms of R–R intervals, the measured ECG signals exhibited a 98.6% similarity to ECGs measured using contact ECG systems. The proposed noncontact ECG measurement system based on capacitive sensing is applicable for use in everyday life.

scholarly journals Anticipating Atrial Fibrillation Signal Using Efficient Algorithm

2021 ◽  
Vol 17 (02) ◽  
pp. 106
Author(s):  
Mohand Lokman Ahmad Al-dabag ◽  
Haider Th. Salim ALRikabi ◽  
Raid Rafi Omar Al-Nima
Keyword(s):  
Atrial Fibrillation ◽  
Computational Cost ◽  
Extraction Methods ◽  
Support Vector ◽  
Ecg Signal ◽  
Heart Problem ◽  
Ecg Signals ◽  
The Right ◽  
Electrocardiogram Ecg ◽  
Low Computational Cost

One of the common types of arrhythmia is Atrial Fibrillation (AF), it may cause death to patients. Correct diagnosing of heart problem through examining the Electrocardiogram (ECG) signal will lead to prescribe the right treatment for a patient. This study proposes a system that distinguishes between the normal and AF ECG signals. First, this work provides a novel algorithm for segmenting the ECG signal for extracting a single heartbeat. The algorithm utilizes low computational cost techniques to segment the ECG signal. Then, useful pre-processing and feature extraction methods are suggested. Two classifiers, Support Vector Machine (SVM) and Multilayer Perceptron (MLP), are separately used to evaluate the two proposed algorithms. The performance of the last proposed method with the two classifiers (SVM and MLP) show an improvement of about (19% and 17%, respectively) after using the proposed segmentation method so it became 96.2% and 97.5%, respectively.

scholarly journals TWO-LEAD JOINT DETECTION ALGORITHM OF QRS COMPLEXES IN ECG SIGNAL

2021 ◽  
Author(s):  
WANSONG XU ◽  
TIANWU CHEN ◽  
FANYU DU
Keyword(s):  
Detection Algorithm ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Joint Detection ◽  
Ecg Signals ◽  
Detection Algorithms ◽  
Threshold Adjustment ◽  
Current Algorithm ◽  
Electrocardiogram Ecg

Objective: The detection of QRS complexes is an important part of computer-aided analysis of electrocardiogram (ECG). However, most of the existing detection algorithms are mainly for single-lead ECG signals, which requires high quality of signal. If the signal quality decreases suddenly due to some interference, then the current algorithm is easy to cause misjudgment or missed detection. To improve the detection ability of QRS complexes under sudden interference, we study the QRS complexes information on multiple leads in-depth, and propose a two-lead joint detection algorithm of QRS complexes. Methods: Firstly, the suspected QRS complexes are screened on the main lead. For the suspected QRS complexes with low confidence and the complexes that may be missed, further accurate detection and joint judgment shall be carried out at the corresponding position of the auxiliary lead. At the same time, the adaptive threshold adjustment algorithm and backtracking mechanism are used to modify the detection results. Results: The proposed detection algorithm is validated using 48 ECG records of the MIT-BIH arrhythmia database, and achieves average detection accuracy of 99.71%, sensitivity of 99.88% and positive predictivity of 99.81%. Conclusion: The proposed algorithm has high accuracy, which can effectively deal with the sudden interference of ECG signal. Meanwhile, the algorithm requires small amount of computation, and can be embedded into hardware for real-time detection.

Motion Artifact Removal in Ambulatory ECG Signal for Heart Rate Variability Analysis

2019 ◽  
Vol 19 (24) ◽  
pp. 12432-12442 ◽  
Author(s):  
Deepak Berwal ◽  
Vandana C.R. ◽  
Sourya Dewan ◽  
Jiji C.V. ◽  
Maryam Shojaei Baghini
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Motion Artifact ◽  
Heart Rate Variability Analysis ◽  
Ecg Signal ◽  
Artifact Removal ◽  
Variability Analysis ◽  
Ambulatory Ecg
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