AIMC Topic: Heart Rate

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Machine Learning in Rehabilitation Assessment for Thermal and Heart Rate Data Processing.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 1, 2018
Multimodal signal analysis based on sophisticated noninvasive sensors, efficient communication systems, and machine learning, have a rapidly increasing range of different applications. The present paper is devoted to pattern recognition and the analy...
Machine Learning Algorithms Exercise Heart Rate Humans Neural Networks, Computer Electronic Data Processing Respiratory Rate Bicycling Rehabilitation Physical Fitness Pattern Recognition, Automated Body Temperature Respiration
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An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

Critical care medicine Apr 1, 2018
OBJECTIVES: Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-ti...
Humans Female Aged Male Middle Aged Machine Learning Critical Illness Intensive Care Units Electronic Health Records Organ Dysfunction Scores Vital Signs Socioeconomic Factors Electrocardiography Heart Rate Age Factors Time Factors Sex Factors Comorbidity Blood Pressure Hospital Mortality Severity of Illness Index Academic Medical Centers ROC Curve Sepsis Time-to-Treatment Decision Support Systems, Clinical
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Effects of nefopam on emergence agitation after general anesthesia for nasal surgery: A prospective, randomized, and controlled trial.

Medicine Nov 1, 2017
BACKGROUND: Emergence agitation (EA) occurs frequently after nasal surgery. N-methyl-D-aspartate (NMDA) receptor antagonists and analgesics, such as fentanyl, have been shown to prevent EA. Nefopam inhibits the NMDA receptor and shows a potent analge...
Analgesics, Non-Narcotic Emergence Delirium Nasal Surgical Procedures Time Factors Adult Humans Heart Rate Male Treatment Outcome Prospective Studies Nefopam Middle Aged Anesthesia, General Female Postoperative Period Incidence Double-Blind Method Airway Extubation
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[Noninvasive Continuous Blood Pressure Measurement Method Based on EEMD and ANN].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Jul 30, 2017
Blood pressure is an important index to measure the function of human cardiovascular system. In order to solve the problem of non-invasive continuous measurement of blood pressure in electronic sphygmomanometer, a noninvasive blood pressure measureme...
Cardiovascular System Neural Networks, Computer Blood Pressure Determination Blood Pressure Heart Rate Humans
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Patient-Specific Classification of ICU Sedation Levels From Heart Rate Variability.

Critical care medicine Jul 1, 2017
OBJECTIVE: To develop a personalizable algorithm to discriminate between sedation levels in ICU patients based on heart rate variability.
Heart Rate Anesthesia Boston Respiration, Artificial Pilot Projects Electrocardiography Support Vector Machine Humans Algorithms Intensive Care Units Female Aged Male Middle Aged
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An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

Bio-medical materials and engineering Aug 12, 2016
In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid t...
Heart Rate Death, Sudden, Cardiac Humans Algorithms Databases, Factual Electrocardiography Support Vector Machine Discriminant Analysis Signal Processing, Computer-Assisted
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Detection of mental stress due to oral academic examination via ultra-short-term HRV analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Mental stress may cause cognitive dysfunctions, cardiovascular disorders and depression. Mental stress detection via short-term Heart Rate Variability (HRV) analysis has been widely explored in the last years, while ultra-short term (less than 5 minu...
Algorithms Young Adult Adult Data Mining Sensitivity and Specificity Humans Adolescent Heart Rate Stress, Psychological Rest Electrocardiography Signal Processing, Computer-Assisted
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Monitoring and detecting atrial fibrillation using wearable technology.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Atrial fibrillation (AFib) is diagnosed by analysis of the morphological and rhythmic properties of the electrocardiogram. It was recently shown that accurate detection of AFib is possible using beat-to-beat interval variations. This raises the quest...
Heart Rate Monitoring, Ambulatory Accelerometry Pulse Photoplethysmography Electrocardiography Humans Signal Processing, Computer-Assisted Atrial Fibrillation Algorithms Retrospective Studies Reproducibility of Results
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Sensor data quality processing for vital signs with opportunistic ambient sensing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Opportunistic ambient sensing involves placement of sensors appropriately so that intermittent contact can be made unobtrusively for gathering physiological signals for vital signs. In this paper, we discuss the results of our quality processing syst...
Humans Neural Networks, Computer Support Vector Machine Decision Trees Discriminant Analysis Heart Rate Data Accuracy
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Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat "concept" fo...
Ballistocardiography Machine Learning Heart Rate Uncertainty Transducers Humans
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