Hardware implementation of deep network accelerators towards healthcare and biomedical applications
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors
has brought on new opportunities for applying both Deep and Spiking Neural Network …
has brought on new opportunities for applying both Deep and Spiking Neural Network …
A review on wearable and contactless sensing for COVID-19 with policy challenges
S Suresh Kumar, K Dashtipour, QH Abbasi… - Frontiers in …, 2021 - frontiersin.org
The COVID-19 pandemic has affected more than 100 million people worldwide, with around
500,000 cases reported daily. This has led to the overwhelming of healthcare systems even …
500,000 cases reported daily. This has led to the overwhelming of healthcare systems even …
Robust R-peak detection in low-quality holter ECGs using 1D convolutional neural network
Objective: Noise and low quality of ECG signals acquired from Holter or wearable devices
deteriorate the accuracy and robustness of R-peak detection algorithms. This paper …
deteriorate the accuracy and robustness of R-peak detection algorithms. This paper …
Robust peak detection for holter ECGs by self-organized operational neural networks
Although numerous R-peak detectors have been proposed in the literature, their robustness
and performance levels may significantly deteriorate in low-quality and noisy signals …
and performance levels may significantly deteriorate in low-quality and noisy signals …
The application of deep learning algorithms for ppg signal processing and classification
F Esgalhado, B Fernandes, V Vassilenko, A Batista… - Computers, 2021 - mdpi.com
Photoplethysmography (PPG) is widely used in wearable devices due to its conveniency
and cost-effective nature. From this signal, several biomarkers can be collected, such as …
and cost-effective nature. From this signal, several biomarkers can be collected, such as …
[HTML][HTML] Pain recognition with electrocardiographic features in postoperative patients: method validation study
E Kasaeyan Naeini, A Subramanian… - Journal of Medical …, 2021 - jmir.org
Background There is a strong demand for an accurate and objective means of assessing
acute pain among hospitalized patients to help clinicians provide pain medications at a …
acute pain among hospitalized patients to help clinicians provide pain medications at a …
Motion artifacts correction from EEG and fNIRS signals using novel multiresolution analysis
MS Hossain, MBI Reaz, MEH Chowdhury… - IEEE …, 2022 - ieeexplore.ieee.org
Physiological signal measurement and processing are increasingly becoming popular in the
ambulatory setting as the hospital-centric treatment is moving towards wearable and …
ambulatory setting as the hospital-centric treatment is moving towards wearable and …
A deep learning–based ppg quality assessment approach for heart rate and heart rate variability
Photoplethysmography (PPG) is a non-invasive optical method to acquire various vital signs,
including heart rate (HR) and heart rate variability (HRV). The PPG method is highly …
including heart rate (HR) and heart rate variability (HRV). The PPG method is highly …
Robust ppg peak detection using dilated convolutional neural networks
Accurate peak determination from noise-corrupted photoplethysmogram (PPG) signal is the
basis for further analysis of physiological quantities such as heart rate. Conventional …
basis for further analysis of physiological quantities such as heart rate. Conventional …
[HTML][HTML] Wearable edge machine learning with synthetic photoplethysmograms
Strict privacy regulations pose challenges to the development of machine learning (ML) in
the field of health technology where data is particularly sensitive. Gathering and using …
the field of health technology where data is particularly sensitive. Gathering and using …