scholarly journals Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications

2021 ◽  
Author(s):  
Fabian Castaño ◽  
Alher Mauricio Hernández
Keyword(s):  
Vital Signs ◽  
Motion Artifacts ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Signal Distortion ◽  
Ecg Signals ◽  
Vital Signs Monitoring ◽  
Significant Difference ◽  
Monitoring Applications ◽  
Artifacts Reduction

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

scholarly journals Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4822
Author(s):  
Fabian Andres Castaño ◽  
Alher Mauricio Hernández
Keyword(s):  
Signal To Noise Ratio ◽  
Vital Signs ◽  
Motion Artifacts ◽  
World Health ◽  
Signal Acquisition ◽  
Signal Distortion ◽  
Electrocardiographic Signal ◽  
Vital Signs Monitoring ◽  
Significant Difference ◽  
Health Organization

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by World Health Organization. Some wearables devices have been developed to monitor the Electrocardiographic in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an Electrocardiographic signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effects of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain Electrocardiographic signals, the result was compared with a computational model of the heart behavior through the Ensemble Average Electrocardiographic, Dynamic Time Warping and Signal-to-Noise Ratio methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the Electrocardiographic signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6 cm at most from the suggested location by the Einthoven triangle in Mason–Likar’s method.

scholarly journals Capturing Electrocardiogram Signals from Chairs by Multiple Capacitively Coupled Unipolar Electrodes

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2835 ◽  
Author(s):  
Zhongjie Hou ◽  
Jinxi Xiang ◽  
Yonggui Dong ◽  
Xiaohui Xue ◽  
Hao Xiong ◽  
...  
Keyword(s):  
Printed Circuit Board ◽  
Experimental Tests ◽  
Circuit Board ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Capacitively Coupled ◽  
Ecg Signals ◽  
Printed Circuit ◽  
Electrocardiogram Signals ◽  
Electrocardiogram Ecg

A prototype of an electrocardiogram (ECG) signal acquisition system with multiple unipolar capacitively coupled electrodes is designed and experimentally tested. Capacitively coupled electrodes made of a standard printed circuit board (PCB) are used as the sensing electrodes. Different from the conventional measurement schematics, where one single lead ECG signal is acquired from a pair of sensing electrodes, the sensing electrodes in our approaches operate in a unipolar mode, i.e., the biopotential signals picked up by each sensing electrodes are amplified and sampled separately. Four unipolar electrodes are mounted on the backrest of a regular chair and therefore four channel of signals containing ECG information are sampled and processed. It is found that the qualities of ECG signal contained in the four channel are different from each other. In order to pick up the ECG signal, an index for quality evaluation, as well as for aggregation of multiple signals, is proposed based on phase space reconstruction. Experimental tests are carried out while subjects sitting on the chair and clothed. The results indicate that the ECG signals can be reliably obtained in such a unipolar way.

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.

scholarly journals Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5503
Author(s):  
Xinyue Zhang ◽  
Xiuzhu Yang ◽  
Yi Ding ◽  
Yili Wang ◽  
Jialin Zhou ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vital Signs ◽  
Motion Artifacts ◽  
Body Motion ◽  
Ultra Wideband ◽  
Body Movements ◽  
Range Resolution ◽  
Vital Signs Monitoring ◽  
Uwb Radar ◽  
Empirical Wavelet Transform

Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest–abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.

RF and camera-based vital signs monitoring applications

2022 ◽  
pp. 303-326
Author(s):  
Li Zhang ◽  
Changhong Fu ◽  
Changzhi Li ◽  
Hong Hong
Keyword(s):  
Vital Signs ◽  
Vital Signs Monitoring ◽  
Monitoring Applications

scholarly journals Quality Assessment of 12 Lead ECG Signals based on Beat Detection Pattern

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Muhammad Yazid
Keyword(s):  
Data Stream ◽  
Training Dataset ◽  
Signal Quality ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Data Set ◽  
Memory Space ◽  
Ecg Signals ◽  
Large Memory ◽  
Percent Accuracy

Abstract—This paper proposed a new method for assessing signal quality from 12 lead ECG signal. The proposed method can be applied to incoming ECG data stream in one pass, does not involve computatively expensive filtering and does not require large memory space, which makes it especially useful for use in mobile device based ECG signal acquisition. The proposed method is verified on PhysioNet/Computing in Cardiology Chal- lenge 2011 12 lead ECG signals database, achieving a result of 89.98 percent accuracy when tested against the training dataset, and 87.4 percent accuracy when tested against the test data set.

scholarly journals LABVIEW BASED ECG SIGNAL ACQUISITION AND ANALYSIS

2021 ◽  
Vol 5 (9) ◽  
Author(s):  
Shila Dhande
Keyword(s):  
Heart Rate ◽  
Research Work ◽  
Heart Rhythm ◽  
The Body ◽  
P Wave ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Qrs Complex ◽  
Ecg Signals ◽  
Rr Interval

The system “LabVIEW based ECG signal acquisition and analysis” is developed to assist patients and doctors in health care. An arrhythmia is an abnormal heart rhythm. It may be so brief that it doesn’t change the overall heart rate, but it can cause the heart rate to be too slow or too fast. When arrhythmias are severe or last long enough, the heart may not be able to pump enough blood to the body. This can cause the patient to feel tired, lightheaded or may make him pass out. It can also cause death. Before treatment, it’s important for the doctor to know where an arrhythmia starts in the heart and whether it’s abnormal. An electrocardiogram (ECG) is often used to diagnose arrhythmias. “LabVIEW based ECG signal acquisition and analysis” is meant to acquire ECG signals from the patient and analyze it to detect and classify its anomalies and abnormalities. This is achieved by extracting amplitudes and durations of parameters of ECG waveform such as P wave, QRS complex, RR interval, and PR durations. These parameters are compared with the normal values to determine the type of abnormality- Tachycardia or Bradycardia. The database of the patient is maintained for further use by the doctor. The objective of LabVIEW based ECG signal acquisition and analysis aims at acquiring and analyzing temporal parameters of ECG signal such as P wave, QRS complex, RR interval, PR durations and amplitudes of the P wave, ST wave, identification of cardiac arrhythmia using LabVIEW. The research work has helped us to explore various features of LabVIEW like signal processing and automated database generation.

scholarly journals Noisy ECG Signal Analysis for Automatic Peak Detection

Information ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 35 ◽  
Author(s):  
Matteo D’Aloia ◽  
Annalisa Longo ◽  
Maria Rizzi
Keyword(s):  
Signal Processing ◽  
Signal To Noise Ratio ◽  
Stress Test ◽  
Processing Technique ◽  
Motion Artifacts ◽  
Ecg Signal ◽  
Signal Processing Technique ◽  
Ecg Signals ◽  
Point Detection ◽  
Detection And Localization

Cardiac signal processing is usually a computationally demanding task as signals are heavily contaminated by noise and other artifacts. In this paper, an effective approach for peak point detection and localization in noisy electrocardiogram (ECG) signals is presented. Six stages characterize the implemented method, which adopts the Hilbert transform and a thresholding technique for the detection of zones inside the ECG signal which could contain a peak. Subsequently, the identified zones are analyzed using the wavelet transform for R point detection and localization. The conceived signal processing technique has been evaluated, adopting ECG signals belonging to MIT-BIH Noise Stress Test Database, which includes specially selected Holter recordings characterized by baseline wander, muscle artifacts and electrode motion artifacts as noise sources. The experimental results show that the proposed method reaches most satisfactory performance, even when challenging ECG signals are adopted. The results obtained are presented, discussed and compared with some other R wave detection algorithms indicated in literature, which adopt the same database as a test bench. In particular, for a signal to noise ratio (SNR) equal to 6 dB, results with minimal interference from noise and artifacts have been obtained, since Se e +P achieve values of 98.13% and 96.91, respectively.

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