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Heart Rate

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STConvSleepNet: A Spatiotemporal Convolutional Network for Sleep Posture Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sleep posture, intricately connected to sleep health, has emerged as a crucial focus in sleep medicine. Studies have associated the supine posture with increased frequency and severity of obstructive sleep apnea (OSA), while lateral postures may miti...

Physical, Social and Cognitive Stressor Identification using Electrocardiography-derived Features and Machine Learning from a Wearable Device.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Anxiety is a prevalent and detrimental mental health condition affecting young adults, particularly in college students who face a range of stressors including academic pressures, interpersonal relationships, and financial concerns. The ability to pr...

Heart Rate Estimation from Neck Photoplethysmography using FFT-Based Scoring and a Shallow Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Heart rate (HR) is one of the most important vital signs to monitor. Constantly monitoring HR makes it important to have an easy-to-use system that is able to achieve clinically acceptable measurement accuracy. Depending on the monitoring device's ul...

PhysioSens1D-NET: A 1D Convolution Network for Extracting Heart Rate from Facial Videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Non-contact heart rate (HR) monitoring from video streams is the most established approach to unobtrusive vitals monitoring. A multitude of classical signal processing algorithms and cutting-edge deep learning models have been developed for non-conta...

EmoNet: Deep Learning-based Emotion Climate Recognition Using Peers' Conversational Speech, Affect Dynamics, and Physiological Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Understanding the emotional dynamics within social interactions is crucial for meaningful interpretation. Despite progress in emotion recognition systems, recognizing the collective emotional climate among peers has been understudied. Addressing this...

[A review of deep learning methods for non-contact heart rate measurement based on facial videos].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Heart rate is a crucial indicator of human health with significant physiological importance. Traditional contact methods for measuring heart rate, such as electrocardiograph or wristbands, may not always meet the need for convenient health monitoring...

Classifying metro drivers' cognitive distractions during manual operations using machine learning and random forest-recursive feature elimination.

Scientific reports
Metro drivers are more likely to trigger accidents if they suffer from cognitive distractions during manual driving. However, identifying metro drivers' cognitive distractions faces challenges as generally no obvious behavior can be found during the ...

Assessment of PTSD in military personnel via machine learning based on physiological habituation in a virtual immersive environment.

Scientific reports
Posttraumatic stress disorder (PTSD) is a complex mental health condition triggered by exposure to traumatic events that leads to physical health problems and socioeconomic impairments. Although the complex symptomatology of PTSD makes diagnosis diff...

Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BMC medical informatics and decision making
BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The...

Reconstruction of ECG from ballistocardiogram using generative adversarial networks with attention.

Biomedical physics & engineering express
Electrocardiogram (ECG) is widely used to provide early warning signals for cardiovascular diseases. However, traditional twelve-lead ECG monitoring methods and smartwatch-based home solutions are unable to achieve daily long-term monitoring. Therefo...