AIMC Topic: Heart Rate

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Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network.

Sensors (Basel, Switzerland) Feb 16, 2023
Oxygen uptake (V˙O2) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their ...
Linear Models Exercise Test Heart Rate Neural Networks, Computer Oxygen
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Cross Dataset Analysis for Generalizability of HRV-Based Stress Detection Models.

Sensors (Basel, Switzerland) Feb 6, 2023
Stress is an increasingly prevalent mental health condition across the world. In Europe, for example, stress is considered one of the most common health problems, and over USD 300 billion are spent on stress treatments annually. Therefore, monitoring...
Artificial Intelligence Europe Heart Rate Algorithms Biomedical Research
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An interpretable machine learning approach to multimodal stress detection in a simulated office environment.

Journal of biomedical informatics Jan 30, 2023
BACKGROUND AND OBJECTIVE: Work-related stress affects a large part of today's workforce and is known to have detrimental effects on physical and mental health. Continuous and unobtrusive stress detection may help prevent and reduce stress by providin...
Heart Rate Movement Machine Learning Mental Health Random Forest
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A Tiny Matched Filter-Based CNN for Inter-Patient ECG Classification and Arrhythmia Detection at the Edge.

Sensors (Basel, Switzerland) Jan 26, 2023
Automated electrocardiogram (ECG) classification using machine learning (ML) is extensively utilized for arrhythmia detection. Contemporary ML algorithms are typically deployed on the cloud, which may not always meet the availability and privacy requ...
Humans Heart Rate Neural Networks, Computer Electrocardiography Algorithms Signal Processing, Computer-Assisted Heart Ventricles Arrhythmias, Cardiac
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A concept for emotion recognition systems for children with profound intellectual and multiple disabilities based on artificial intelligence using physiological and motion signals.

Disability and rehabilitation. Assistive technology Jan 25, 2023
PURPOSE: This study proposes a concept for emotion recognition systems for children with profound intellectual and multiple disabilities (PIMD) based on artificial intelligence (AI) using physiological and motion signals.
Artificial Intelligence Female Humans Emotions Heart Rate Male Child Intellectual Disability Children with Disabilities
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X-iPPGNet: A novel one stage deep learning architecture based on depthwise separable convolutions for video-based pulse rate estimation.

Computers in biology and medicine Jan 24, 2023
Pulse rate (PR) is one of the most important markers for assessing a person's health. With the increasing demand for long-term health monitoring, much attention is being paid to contactless PR estimation using imaging photoplethysmography (iPPG). Thi...
Video Recording Deep Learning Photoplethysmography Skin Heart Rate Humans Algorithms
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Two phases based training method for designing codewords for a set of perceptrons with each perceptron having multi-pulse type activation function.

Network (Bristol, England) Jan 10, 2023
This paper proposes a two phases-based training method to design the codewords to map the cluster indices of the input feature vectors to the outputs of the new perceptrons with the multi-pulse type activation functions. Our proposed method is applie...
Computer Simulation Neural Networks, Computer Heart Rate Algorithms
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Diagnosis of arrhythmias with few abnormal ECG samples using metric-based meta learning.

Computers in biology and medicine Dec 28, 2022
A major challenge in artificial intelligence based ECG diagnosis lies that it is difficult to obtain sufficient annotated training samples for each rhythm type, especially for rare diseases, which makes many approaches fail to achieve the desired per...
Algorithms Neural Networks, Computer Electrocardiography Artificial Intelligence Arrhythmias, Cardiac Humans Heart Rate
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A Flexible Deep Learning Architecture for Temporal Sleep Stage Classification Using Accelerometry and Photoplethysmography.

IEEE transactions on bio-medical engineering Dec 26, 2022
Wrist-worn consumer sleep technologies (CST) that contain accelerometers (ACC) and photoplethysmography (PPG) are increasingly common and hold great potential to function as out-of-clinic (OOC) sleep monitoring systems. However, very few validation s...
Sleep Stages Sleep Deep Learning Accelerometry Photoplethysmography Heart Rate
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A Denoising and Fourier Transformation-Based Spectrograms in ECG Classification Using Convolutional Neural Network.

Sensors (Basel, Switzerland) Dec 7, 2022
The non-invasive electrocardiogram (ECG) signals are useful in heart condition assessment and are found helpful in diagnosing cardiac diseases. However, traditional ways, i.e., a medical consultation required effort, knowledge, and time to interpret ...
Algorithms Filtration Electrocardiography Heart Diseases Humans Heart Rate Neural Networks, Computer
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