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Earable Multimodal Sensing and Stimulation: A Prospective Towards Unobtrusive Closed-Loop Biofeedback
The human ear has emerged as a bidirectional gateway to the brain's and body's signals.
Recent advances in around-the-ear and in-ear sensors have enabled the assessment of …
Recent advances in around-the-ear and in-ear sensors have enabled the assessment of …
Interpretable Pre-Trained Transformers for Heart Time-Series Data
Decoder-only transformers are the backbone of the popular generative pre-trained
transformer (GPT) series of large language models. In this work, we employ this framework …
transformer (GPT) series of large language models. In this work, we employ this framework …
[HTML][HTML] Design and implementation of an atrial fibrillation detection algorithm on the ARM Cortex-M4 microcontroller
At present, a medium-level microcontroller is capable of performing edge computing and
can handle the computation of neural network kernel functions. This makes it possible to …
can handle the computation of neural network kernel functions. This makes it possible to …
Hearables: feasibility of recording cardiac rhythms from single in-ear locations
The ear is well positioned to accommodate both brain and vital signs monitoring, via so-
called hearable devices. Consequently, ear-based electroencephalography has recently …
called hearable devices. Consequently, ear-based electroencephalography has recently …
Improving diffusion models for ecg imputation with an augmented template prior
Pulsative signals such as the electrocardiogram (ECG) are extensively collected as part of
routine clinical care. However, noisy and poor-quality recordings are a major issue for …
routine clinical care. However, noisy and poor-quality recordings are a major issue for …
Hearables: In-Ear Multimodal Data Fusion for Robust Heart Rate Estimation
Background: Ambulatory heart rate (HR) monitors that acquire electrocardiogram (ECG)
or/and photoplethysmographm (PPG) signals from the torso, wrists, or ears are notably less …
or/and photoplethysmographm (PPG) signals from the torso, wrists, or ears are notably less …
Single-channel electroencephalography decomposition by detector-atom network and its pre-trained model
Signal decomposition techniques utilizing multi-channel spatial features are critical for
analyzing, denoising, and classifying electroencephalography (EEG) signals. To facilitate …
analyzing, denoising, and classifying electroencephalography (EEG) signals. To facilitate …
In-ear ECG Signal Enhancement with Denoising Convolutional Autoencoders
The cardiac dipole has been shown to propagate to the ears, now a common site for
consumer wearable electronics, enabling the recording of electrocardiogram (ECG) signals …
consumer wearable electronics, enabling the recording of electrocardiogram (ECG) signals …
Advancing Ear ECG Analysis during CPR Using Adaptive Filtering
This study explores the feasibility of using ear electrocardiogram (ECG) as a viable
alternative to the traditional chest ECG during cardiopulmonary resuscitation (CPR). To …
alternative to the traditional chest ECG during cardiopulmonary resuscitation (CPR). To …
ECG Signal Data Classification System Based on Hankel Dynamic Mode Decomposition
C Liang, MKM Ali, L Wu, Z Zhang - Malaysian Journal of Fundamental …, 2025 - mjfas.utm.my
The modes in the electrocardiogram (ECG) signal can be divided into stable modes and
unstable modes. The unstable modes are of great significance for signal analysis and …
unstable modes. The unstable modes are of great significance for signal analysis and …