Detection and monitoring of viral infections via wearable devices and biometric data
CJ Goergen, MKJ Tweardy, SR Steinhubl… - Annual review of …, 2022 - annualreviews.org
Mounting clinical evidence suggests that viral infections can lead to detectable changes in
an individual's normal physiologic and behavioral metrics, including heart and respiration …
an individual's normal physiologic and behavioral metrics, including heart and respiration …
Uncertainty quantification in DenseNet model using myocardial infarction ECG signals
Background and objective Myocardial infarction (MI) is a life-threatening condition
diagnosed acutely on the electrocardiogram (ECG). Several errors, such as noise, can …
diagnosed acutely on the electrocardiogram (ECG). Several errors, such as noise, can …
Analysis of Pan-Tompkins algorithm performance with noisy ECG signals
MAZ Fariha, R Ikeura, S Hayakawa… - Journal of Physics …, 2020 - iopscience.iop.org
Abstract The Pan-Tompkins Algorithm is the most widely used QRS complex detector for the
monitoring of many cardiac diseases including in arrhythmia detection. This method could …
monitoring of many cardiac diseases including in arrhythmia detection. This method could …
Multiple physiological signals fusion techniques for improving heartbeat detection: A review
This paper presents a review of the techniques found in the literature that aim to achieve a
robust heartbeat detection from fusing multi-modal physiological signals (eg …
robust heartbeat detection from fusing multi-modal physiological signals (eg …
An automatic diagnosis of arrhythmias using a combination of CNN and LSTM technology
Electrocardiogram (ECG) signal evaluation is routinely used in clinics as a significant
diagnostic method for detecting arrhythmia. However, it is very labor intensive to externally …
diagnostic method for detecting arrhythmia. However, it is very labor intensive to externally …
scl-st: Supervised contrastive learning with semantic transformations for multiple lead ecg arrhythmia classification
The automatic classification of electrocardiogram (ECG) signals has played an important
role in cardiovascular diseases diagnosis and prediction. With recent advancements in deep …
role in cardiovascular diseases diagnosis and prediction. With recent advancements in deep …
Classification of Obstructive Sleep Apnoea from single-lead ECG signals using convolutional neural and Long Short Term Memory networks
Abstract Obstructive Sleep Apnoea (OSA) is a breathing disorder that happens during sleep.
Polysomnography (PSG) is typically used as a reference standard for the diagnosis of OSA …
Polysomnography (PSG) is typically used as a reference standard for the diagnosis of OSA …
Wearable iots and geo-fencing based framework for COVID-19 remote patient health monitoring and quarantine management to control the pandemic
The epidemic disease of Severe Acute Respiratory Syndrome (SARS) called COVID-19 has
become a more frequently active disease. Managing and monitoring COVID-19 patients is …
become a more frequently active disease. Managing and monitoring COVID-19 patients is …
A wearable multisensor patch for breathing pattern recognition
In this article, a multisensor patch is presented for the purpose of detecting and recognizing
the signals produced by human breathing in response to a variety of different body …
the signals produced by human breathing in response to a variety of different body …
Efficient R-peak detection in electrocardiogram signal based on features extracted using Hilbert transform and Burg method
Electrocardiogram (ECG) is a non-invasive test which is highly adopted as a primary
diagnostic tool for cardiovascular diseases. ECG recording appears as a non-stationary and …
diagnostic tool for cardiovascular diseases. ECG recording appears as a non-stationary and …