scholarly journals Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5548
Author(s):  
Hesam Halvaei ◽  
Leif Sörnmo ◽  
Martin Stridh
Keyword(s):  
Ambulatory Monitoring ◽  
Motion Artifact ◽  
Detection Performance ◽  
Motion Artifacts ◽  
Signal Quality ◽  
The Novel ◽  
Quality Indices ◽  
Qrs Detection ◽  
Time Frequency ◽  
The Cost

Background: The presence of noise is problematic in the analysis and interpretation of the ECG, especially in ambulatory monitoring. Restricting the analysis to high-quality signal segments only comes with the risk of excluding significant arrhythmia episodes. Therefore, the development of novel electrode technology, robust to noise, continues to be warranted. Methods: The signal quality of a novel wet ECG electrode (Piotrode) is assessed and compared to a commercially available, commonly used electrode (Ambu). The assessment involves indices of QRS detection and atrial fibrillation detection performance, as well as signal quality indices (ensemble standard deviation and time–frequency repeatability), computed from ECGs recorded simultaneously from 20 healthy subjects performing everyday activities. Results: The QRS detection performance using the Piotrode was considerably better than when using the Ambu, especially for running but also for lighter activities. The two signal quality indices demonstrated similar trends: the gap in quality became increasingly larger as the subjects became increasingly more active. Conclusions: The novel wet ECG electrode produces signals with less motion artifacts, thereby offering the potential to reduce the review burden, and accordingly the cost, associated with ambulatory monitoring.

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 An Efficient Motion and Noise Artifacts Removal Method using GAIT and Machine Learning Model

2019 ◽  
Vol 9 (2) ◽  
pp. 285-292
Keyword(s):  
Oxygen Saturation ◽  
Real Time ◽  
Threshold Model ◽  
Arterial Oxygen Saturation ◽  
Ambulatory Monitoring ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Arterial Oxygen ◽  
Support Vector ◽  
Machine Model

obtaining an exact measurement of oxygen saturation (SpO2) using a finger-probe based pulse oximeter is dependent on both artifact-free infrared (IR) and red (R) Photoplethysmographic signals. However, in actual real-time environment condition, these Photoplethysmographic signals are corrupted due to presence of motion artifact (MA) signal that is produced due to the movement/motion from either hand or finger. To address this motion artifacts interference, the cause of the contamination of Photoplethysmographic signals by the motion artifacts signal is observed using GAIT. Motion and noise artifacts enforce constraints on the usability of the Photoplethysmographic, predominantly in the setting of sleep disorder detection and ambulatory monitoring. Motion and noise artifacts can alter Photoplethysmographic, resulting wrong approximation of physiological factors such as arterial oxygen saturation and heart rate. For overcoming issues and problems, this manuscript presented a new approach for detection of artifacts. First, present an adaptive filter and adaptive threshold model to detect artifact and obtain derivative of correlation coefficient (CC) for labelling artifacts, respectively. Lastly, Improved Support Vector Machine Model is presented to perform classification. Experiment are conducted on real-time dataset. Our approach attain significant performance in term of accuracy, sensitivity, specificity and positive prediction.

scholarly journals Peak Space Motion Artifact Cancellation Applied to Textile Electrode Waist Electrocardiograms Recording During Outdoors Walking and Jogging

2022 ◽  
Author(s):  
Bruce R Hopenfeld
Keyword(s):  
Real World ◽  
Single Channel ◽  
Ground Truth ◽  
Motion Artifact ◽  
Heart Beat ◽  
Pattern Search ◽  
Motion Artifacts ◽  
Qrs Detection ◽  
Detection Scheme ◽  
Textile Electrode

Background: Obtaining reliable rate heart estimates from waist based electrocardiograms (ECGs) poses a very challenging problem due to the presence of extreme motion artifacts. The literature reveals few, if any, attempts to apply motion artifact cancellation methods to waist based ECGs. This paper describes a new methodology for ameliorating the effects of motion artifacts in ECGs by specifically targeting ECG peaks for elimination that are determined to be correlated with accelerometer peaks. This peak space cancellation was applied to real world waist based ECGs. Algorithm Summary: The methodology includes successive applications of a previously described pattern-based heart beat detection scheme (Temporal Pattern Search, or TEPS) that can also detect patterns in other types of peak sequences. In the first application, TEPS is applied to accelerometer signals recorded contemporaneously with ECG signals to identify high-quality accelerometer peak sequences (SA) indicative of quasi-periodic motion likely to impair identification of peaks in a corresponding ECG signal. The process then performs ECG peak detection and locates the closest in time ECG peak to each peak in an SA. The differences in time between ECG and SA peaks are clustered. If the number of elements in a cluster of peaks in an SA exceeds a threshold, the ECG peaks in that cluster are removed from further processing. After this peak removal process, further QRS detection proceeds according to TEPS. Experiment: The above procedure was applied to data from real world experiments involving four sessions of walking and jogging on a dirt road for approximately 20-25 minutes. A compression shirt with textile electrodes served as the ground truth recording. A textile electrode based chest strap was worn around the waist to generate a single channel signal upon which to test peak space cancellation/TEPS. Results: Both walking and jogging heart rates were generally well tracked. In the four recordings, the percentage of 5 second segments within 10 beats/minute of reference was 96%, 99%, 92% and 96%. The percentage of segments within 5 beats/minute of reference was 86%, 90%, 82% and 78%. There was very good agreement between the RR intervals associated with the reference and waist recordings. For acceptable quality segments, the root mean square sum of successive RR interval differences (RMSSD) was calculated for both the reference and waist recordings. Next, the difference between waist and reference RMSSDs was calculated (∆RMSSD). The mean ∆RMSSD (over acceptable segments) was 4.6 m, 5.2 ms, 5.2 ms and 6.6 ms for the four recordings. Conclusion: Given that only one waist ECG channel was available, and that the strap used for the waist recording was not tailored for that purpose, the proposed methodology shows promise for waist based sinus rhythm QRS detection.

Insights into Transdermal Drug Delivery: Approaches for Redressal of a Burgeoning Issue of Osteoporosis

2020 ◽  
Vol 20 (10) ◽  
pp. 1682-1695
Author(s):  
Foziyah Zakir ◽  
Kanchan Kohli ◽  
Farhan J. Ahmad ◽  
Zeenat Iqbal ◽  
Adil Ahmad
Keyword(s):  
Drug Delivery ◽  
Transdermal Delivery ◽  
Oral Delivery ◽  
Calcium Absorption ◽  
Early Stage ◽  
Osteoporotic Fractures ◽  
The Novel ◽  
Systemic Delivery ◽  
Primary Focus ◽  
The Cost

Osteoporosis is a progressive bone disease that remains unnoticed until a fracture occurs. It is more predominant in the older age population, particularly in females due to reduced estrogen levels and ultimately limited calcium absorption. The cost burden of treating osteoporotic fractures is too high, therefore, primary focus should be treatment at an early stage. Most of the marketed drugs are available as oral delivery dosage forms. The complications, as well as patient non-compliance, limit the use of oral therapy for prolonged drug delivery. Transdermal delivery systems seem to be a promising approach for the delivery of anti-osteoporotic active moieties. One of the confronting barriers is the passage of drugs through the SC layers followed by penetration to deeper dermal layers. The review focuses on how anti-osteoporotic drugs can be molded through different approaches so that they can be exploited for the skin to systemic delivery. Insights into the various challenges in transdermal delivery and how the novel delivery system can be used to overcome these have also been detailed.

scholarly journals Detection of Ventricular Fibrillation Based on Ballistocardiography by Constructing an Effective Feature Set

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3524
Author(s):  
Rongru Wan ◽  
Yanqi Huang ◽  
Xiaomei Wu
Keyword(s):  
Ventricular Fibrillation ◽  
Cross Validation ◽  
Rhythmic Activity ◽  
Detection Algorithm ◽  
Motion Artifacts ◽  
Cardiac Monitoring ◽  
Mechanical Activity ◽  
Time Frequency ◽  
S Transform ◽  
Fatal Arrhythmia

Ventricular fibrillation (VF) is a type of fatal arrhythmia that can cause sudden death within minutes. The study of a VF detection algorithm has important clinical significance. This study aimed to develop an algorithm for the automatic detection of VF based on the acquisition of cardiac mechanical activity-related signals, namely ballistocardiography (BCG), by non-contact sensors. BCG signals, including VF, sinus rhythm, and motion artifacts, were collected through electric defibrillation experiments in pigs. Through autocorrelation and S transform, the time-frequency graph with obvious information of cardiac rhythmic activity was obtained, and a feature set of 13 elements was constructed for each 7 s segment after statistical analysis and hierarchical clustering. Then, the random forest classifier was used to classify VF and non-VF, and two paradigms of intra-patient and inter-patient were used to evaluate the performance. The results showed that the sensitivity and specificity were 0.965 and 0.958 under 10-fold cross-validation, and they were 0.947 and 0.946 under leave-one-subject-out cross-validation. In conclusion, the proposed algorithm combining feature extraction and machine learning can effectively detect VF in BCG, laying a foundation for the development of long-term self-cardiac monitoring at home and a VF real-time detection and alarm system.

scholarly journals Quality Classification of Injection-Molded Components by Using Quality Indices, Grading, and Machine Learning

Polymers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 353
Author(s):  
Kun-Cheng Ke ◽  
Ming-Shyan Huang
Keyword(s):  
Machine Learning ◽  
Integrated Circuit ◽  
Quality Indices ◽  
Statistical Process ◽  
Suitable Alternative ◽  
Quality Grading ◽  
Quality Of Products ◽  
The Cost ◽  
Mlp Model

Conventional methods for assessing the quality of components mass produced using injection molding are expensive and time-consuming or involve imprecise statistical process control parameters. A suitable alternative would be to employ machine learning to classify the quality of parts by using quality indices and quality grading. In this study, we used a multilayer perceptron (MLP) neural network along with a few quality indices to accurately predict the quality of “qualified” and “unqualified” geometric shapes of a finished product. These quality indices, which exhibited a strong correlation with part quality, were extracted from pressure curves and input into the MLP model for learning and prediction. By filtering outliers from the input data and converting the measured quality into quality grades used as output data, we increased the prediction accuracy of the MLP model and classified the quality of finished parts into various quality levels. The MLP model may misjudge datapoints in the “to-be-confirmed” area, which is located between the “qualified” and “unqualified” areas. We classified the “to-be-confirmed” area, and only the quality of products in this area were evaluated further, which reduced the cost of quality control considerably. An integrated circuit tray was manufactured to experimentally demonstrate the feasibility of the proposed method.

scholarly journals Assessing ECG signal quality indices to discriminate ECGs with artefacts from pathologically different arrhythmic ECGs

2016 ◽  
Vol 37 (8) ◽  
pp. 1370-1382 ◽  
Author(s):  
C Daluwatte ◽  
L Johannesen ◽  
L Galeotti ◽  
J Vicente ◽  
D G Strauss ◽  
...  
Keyword(s):  
Signal Quality ◽  
Ecg Signal ◽  
Quality Indices

scholarly journals Novel dry electrode EEG headbands for home use: Comparing performance and comfort

2020 ◽  
Vol 6 (3) ◽  
pp. 139-142
Author(s):  
Jens Haueisen ◽  
Patrique Fiedler ◽  
Anna Bernhardt ◽  
Ricardo Gonçalves ◽  
Carlos Fonseca
Keyword(s):  
Brain Activity ◽  
Skin Impedance ◽  
Signal Quality ◽  
The Novel ◽  
Application Time ◽  
Dry Electrodes ◽  
Power Spectral ◽  
Dry Electrode ◽  
Increasing Trend ◽  
Eeg Recordings

AbstractMonitoring brain activity at home using electroencephalography (EEG) is an increasing trend for both medical and non-medical applications. Gel-based electrodes are not suitable due to the gel application requiring extensive preparation and cleaning support for the patient or user. Dry electrodes can be applied without prior preparation by the patient or user. We investigate and compare two dry electrode headbands for EEG acquisition: a novel hybrid dual-textile headband comprising multipin and multiwave electrodes and a neoprene-based headband comprising hydrogel and spidershaped electrodes. We compare the headbands and electrodes in terms of electrode-skin impedance, comfort, electrode offset potential and EEG signal quality. We did not observe considerable differences in the power spectral density of EEG recordings. However, the hydrogel electrodes showed considerably increased impedances and offset potentials, limiting their compatibility with many EEG amplifiers. The hydrogel and spider-shaped electrodes required increased adduction, resulting in a lower wearing comfort throughout the application time compared to the novel headband comprising multipin and multiwave electrodes.

scholarly journals Computer Modeling of Barrel-Vaulted Sanctuary Exhibiting Flutter Echo with Comparison to Measurements

Acoustics ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 87-109
Author(s):  
Heather Lai ◽  
Brian Hamilton
Keyword(s):  
Computer Modeling ◽  
Architectural Design ◽  
Impulse Responses ◽  
Time Frequency ◽  
Geometrical Acoustics ◽  
Decay Times ◽  
Before And After ◽  
Show Evidence ◽  
Architectural Planning ◽  
The Cost

Computer modeling in acoustics allows for the prediction of acoustical defects and the evaluation of potential remediations. In this article, computer modeling is applied to the case of a barrel-vaulted sanctuary whose architectural design and construction led to severe flutter echoes along the main aisle, which was later mitigated through acoustical remediations. State-of-the-art geometrical acoustics and wave-based simulations are carried out to analyze the acoustics of this space, with a particular focus on the flutter echoes along the main aisle, before and after remediations. Multi-resolution wavelet and spectrogram analyses are carried out to isolate and characterize flutter echoes within measurements and computer-simulated room impulse responses. Comparisons of simulated responses to measurements are also made in terms of decay times and curves. Simulated room impulse responses from both geometrical acoustics and wave-based methods show evidence of flutter echoes matching measurements, to varying degrees. Time-frequency analyses isolating flutter echoes demonstrate better matches to measurements from wave-based simulated responses, at the cost of longer simulation times than geometrical acoustics simulations. This case study highlights the importance of computer modeling of acoustics in early design phases of architectural planning of worship spaces.

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