Deep neural network: As the novel pipelines in multiple preprocessing for Raman spectroscopy

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2023, Номер 302, С. 123086 - 123086

Опубликована: Июль 1, 2023

Язык: Английский

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Contactless Camera-Based Sleep Staging: The HealthBed Study

Bioengineering, Год журнала: 2023, Номер 10(1), С. 109 - 109

Опубликована: Янв. 12, 2023

Polysomnography (PSG) remains the gold standard for sleep monitoring but is obtrusive in nature. Advances camera sensor technology and data analysis techniques enable contactless of heart rate variability (HRV). In turn, this may allow remote assessment stages, as different HRV metrics indirectly reflect expression stages. We evaluated a camera-based photoplethysmography (PPG) setup to perform automated classification stages near darkness. Based on measurement pulse variability, we use previously developed HRV-based algorithm 3 4-class stage classification. Performance was 46 healthy participants obtained from simultaneous overnight recording PSG PPG. To validate results benchmarking purposes, same used classify based corresponding ECG data. Compared manually scored PSG, PPG-based achieved moderate agreement both class (Wake–N1/N2/N3–REM) 4 (Wake–N1/N2–N3–REM) classification, with average κ 0.58 0.49 accuracy 81% 68%, respectively. This range other performance reported sensing technologies wearable staging, showing potential video-based non-contact staging.

Язык: Английский

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An implantable device for wireless monitoring of diverse physio-behavioral characteristics in freely behaving small animals and interacting groups

Neuron, Год журнала: 2024, Номер 112(11), С. 1764 - 1777.e5

Опубликована: Март 26, 2024

Язык: Английский

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Detection of early fatigue damage during ultrasonic fatigue testing of steel by acoustic emission monitoring

International Journal of Fatigue, Год журнала: 2024, Номер 185, С. 108367 - 108367

Опубликована: Май 3, 2024

Ultrasonic fatigue testing (USFT) is a time-efficient method for evaluation of the limit metallic alloys in high and very cycle range. Propagation final crack at end life can be clearly detected by USFT parameters monitoring techniques. In contrast, initiation damage during remains unclear. Despite its excellent sensitivity, implementation acoustic emission (AE) hindered severe noisiness signals from USFT. addition to resonance-related quasi-stationary noises, pulse-pause mode accompanied non-stationary ones, which makes recognition material-related AE even more difficult. A special processing algorithm was developed overcome this issue get useful insights monitoring. Consistent cropping, Fourier transformation, adaptive filtration thresholding allowed calculate noise-free activity 42CrMo4 steel Remarkably, most located beginning loading. comparison non-failed runout samples, samples with cracks significantly higher, indicating relation damage. The proposed principle helpful other parts, operating resonance conditions.

Язык: Английский

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Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors

JACC Heart Failure, Год журнала: 2024, Номер 12(6), С. 1030 - 1040

Опубликована: Апрель 3, 2024

Язык: Английский

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