AIMC Topic: Heart Rate

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Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by technological advancements and electronics miniaturization, wearable health device (WHD) applications are expected to grow exponentially. This, in tur...

Intelligent infusion controller with a physiological information feedback function.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In hospitals, some problems still exist, such as transfusion reaction that cannot be dealt with in time, medical staff cannot observe the physiological information of the infusion patients in real time, and the infusion speed cannot be co...

[Clinical research of target guided treatment of patients with severe heart failure under the guidance of pulse indicator continuous cardiac output].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To investigate the value of pulse indicator continuous cardiac output (PiCCO) monitoring in the treatment management of patients with severe heart failure.

[Heartbeat-based end-to-end classification of arrhythmias].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the classification performance for supraventricular ectopic beat (SVEB) and ventricular ectopic beat (VEB).

Artificial neural networks-based classification of emotions using wristband heart rate monitor data.

Medicine
Heart rate variability (HRV) is an objective measure of emotional regulation. This study aimed to estimate the accuracy with which an artificial neural network (ANN) algorithm could classify emotions using HRV data that were obtained using wristband ...

EEG-Based Mental Workload Estimation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Knowledge of the level of mental workload induced by any task is essential for optimizing load share among the operators. This helps in assessing their capability; besides, helping in task allocation. Since a persistently high workload experienced by...

RespNet: A deep learning model for extraction of respiration from photoplethysmogram.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Respiratory ailments afflict a wide range of people and manifests itself through conditions like asthma and sleep apnea. Continuous monitoring of chronic respiratory ailments is seldom used outside the intensive care ward due to the large size and co...

Optimizing Probability Threshold of Convolution Neural Network to Improve HRV-based Acute Stress Detection Performance.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
As stress is linked to numerous emotional and physical conditions, its timely detection and proper management is important for our health. Convolution neural network (CNN) has been shown to be promising in stress detection because it could automatica...

Clustering Continuous Wavelet Transform Characteristics of Heart Rate Variability through Unsupervised Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The analysis and interpretation of physiological signals acquired non-invasively are increasingly important in Smart Health, precision medicine, and medical research. However, this analysis is hampered due to the length, complexity, and inter-subject...

Feasibility Study of Deep Neural Network for Heart Rate Estimation from Wearable Photoplethysmography and Acceleration Signals.

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) estimation using wearable reflectance-type photoplethysmographic (PPG) signals is challenging due to low signal-to-noise ratio (SNR). Especially during intensive exercise, motion artifacts (MAs) overwhelm PPG signals in an unpredictab...