Accurate detection of characteristic electrocardiogram (ECG) waves is necessary for ECG analysis and interpretation. In this paper, we distinguish four processing steps of detectionalgorithms: noise and artifacts red...
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Accurate detection of characteristic electrocardiogram (ECG) waves is necessary for ECG analysis and interpretation. In this paper, we distinguish four processing steps of detectionalgorithms: noise and artifacts reduction, transformations, fiducial marks selection of wave candidates, and decision rule. Processing steps combinations from several detectionalgorithms are used to find QRS, P, and T wave peaks. In addition, we consider the search window parameter modification based on waveform templates extracted by heart cycles clustering. The methods are extensively evaluated on two public ECG databases containing QRS, P, and T wave peaks annotations. We found that the combination of morphological mathematical filtering with Elgendi's algorithm works best for QRS detection on MIT-BIH Arrhythmia Database (detection error rate (DER = 0.48%, Lead I). The combination of modified Martinez's PT and wavelet transform (WT) methods gave the best results for P wave peaks detection on both databases, when both leads are considered (MIT-BIH arrhythmia database: DER = 32.13%, Lead I, DER = 42.52%, Lead II;QT Database: DER = 21.23%, Lead I, DER = 26.80%, Lead II). Waveform templates in combination with Martinez's WT obtained the best results for T wave peaks detection on QT database (DER = 25.15%, Lead II). This paper demonstrates that combining some of the best proposed methods in literature leads to improvements over the original methods for ECG waves detection while maintaining satisfactory computation times.
Determining marine mammal densities is a complex problem that has been ongoing for many decades. Modern approaches use a combination of sophisticated acoustic monitoring and highly trained visual observers from both s...
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ISBN:
(纸本)9781424443338
Determining marine mammal densities is a complex problem that has been ongoing for many decades. Modern approaches use a combination of sophisticated acoustic monitoring and highly trained visual observers from both ships and aircraft. New camera systems with automatic detection algorithms offer the option to do quantitative airborne surveys safely and quickly. This paper presents a discussion on the various methods of calculating marine mammal densities and demonstrates how all these methods can work together to present quantitative density measurements.
Medical imaging is capturing pictures of bodily components for diagnostic or research reasons. Because of advancements in image-handling techniques, which include picture recognition, examination, and upgrading, clini...
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Narcolepsy type 1 (NT1) is a neurological disorder caused by disruption of hypocretin (HCRT;or orexin) neurotransmission leading to fragmented sleep/wake states, excessive daytime sleepiness, and cataplexy (abrupt mus...
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Narcolepsy type 1 (NT1) is a neurological disorder caused by disruption of hypocretin (HCRT;or orexin) neurotransmission leading to fragmented sleep/wake states, excessive daytime sleepiness, and cataplexy (abrupt muscle atonia during wakefulness). Electroencephalography and electromyography (EEG/EMG) monitoring is the gold standard to assess NT1 phenotypical features in both humans and mice. Here, we evaluated the digital ventilated home-cage (DVC (R)) activity system as an alternative to detect NT1 features in two NT1 mouse models: the genetic HCRT-knockout (-KO) model, and the inducible HCRT neuron-ablation hcrt-tTA;TetO-DTA (DTA) model, including both sexes. NT1 mice exhibited an altered dark phase activity profile and increased state transitions, compared to the wild-type (WT) phenotype. An inability to sustain activity periods >40 min represented a robust activity-based NT1 biomarker. These features were observable within the first weeks of HCRT neuron degeneration in DTA mice. We also created a nest-identification algorithm to differentiate between inactivity and activity, inside and outside the nest as a sleep and wake proxy, respectively, showing significant correlations with EEG/EMG-assessed sleep/wake behavior. Lastly, we tested the sensitivity of the activity system to detect behavioral changes in response to interventions such as repeated saline injection and chocolate. Surprisingly, daily consecutive saline injections significantly reduced activity and increased nest time of HCRT-WT mice. Chocolate increased total activity in all mice, and increased the frequency of short out-of-nest inactivity episodes in HCRT-KO mice. We conclude that the DVC (R) system provides a useful tool for non-invasive monitoring of NT1 phenotypical features, and has the potential to monitor drug effects in NT1 mice.
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