Heart rate tracking in photoplethysmography signals affected by motion artifacts: A review
Non-invasive photoplethysmography (PPG) technology was developed to track heart rate
during motion. Automated analysis of PPG has made it useful in both clinical and non …
during motion. Automated analysis of PPG has made it useful in both clinical and non …
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 …
Emerging energy-efficient biosignal-dedicated circuit techniques: A tutorial brief
High spatiotemporal resolution biosignal that is vital for biomedical applications results in an
information bottleneck that poses challenges for their transferring and processing. The …
information bottleneck that poses challenges for their transferring and processing. The …
Q-ppg: Energy-efficient ppg-based heart rate monitoring on wearable devices
Hearth Rate (HR) monitoring is increasingly performed in wrist-worn devices using low-cost
photoplethysmography (PPG) sensors. However, Motion Artifacts (MAs) caused by …
photoplethysmography (PPG) sensors. However, Motion Artifacts (MAs) caused by …
Finding order in chaos: A novel data augmentation method for time series in contrastive learning
BU Demirel, C Holz - Advances in Neural Information …, 2024 - proceedings.neurips.cc
The success of contrastive learning is well known to be dependent on data augmentation.
Although the degree of data augmentations has been well controlled by utilizing pre-defined …
Although the degree of data augmentations has been well controlled by utilizing pre-defined …
[HTML][HTML] Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing …
Abstract Background and Motivations Physiological signals, such as the
Photoplethysmogram (PPG) collected through wearable devices, consistently encounter …
Photoplethysmogram (PPG) collected through wearable devices, consistently encounter …
Embedding temporal convolutional networks for energy-efficient ppg-based heart rate monitoring
Photoplethysmography (PPG) sensors allow for non-invasive and comfortable heart rate
(HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, motion artifacts …
(HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, motion artifacts …
Heart rate estimation in PPG signals using Convolutional-Recurrent Regressor
Heart rate monitoring using PPG signal has emerged as an attractive as well as an applied
research problem which enjoys a renewed interest in the recent years. Spectral analysis of …
research problem which enjoys a renewed interest in the recent years. Spectral analysis of …
RISC-V CNN coprocessor for real-time epilepsy detection in wearable application
SY Lee, YW Hung, YT Chang, CC Lin… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Epilepsy is a common clinical disease. Severe epilepsy can be life-threatening in certain
unexpected conditions, so it is important to detect seizures instantly with a wearable device …
unexpected conditions, so it is important to detect seizures instantly with a wearable device …
An energy efficient ECG ventricular ectopic beat classifier using binarized CNN for edge AI devices
Wearable Artificial Intelligence-of-Things (AIoT) requires edge devices to be resource and
energy-efficient. In this paper, we design and implement an efficient binary convolutional …
energy-efficient. In this paper, we design and implement an efficient binary convolutional …