AIMC Topic: Monitoring, Physiologic

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Reduction of false arrhythmia alarms using signal selection and machine learning.

Physiological measurement Jul 25, 2016
In this paper, we propose an algorithm that classifies whether a generated cardiac arrhythmia alarm is true or false. The large number of false alarms in intensive care is a severe issue. The noise peaks caused by alarms can be high and in a noisy en...
Humans Critical Care Monitoring, Physiologic Machine Learning False Positive Reactions Signal Processing, Computer-Assisted Electrocardiography Signal-To-Noise Ratio Arrhythmias, Cardiac Clinical Alarms Heart Rate
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Suppression of false arrhythmia alarms in the ICU: a machine learning approach.

Physiological measurement Jul 25, 2016
This paper presents a novel approach for false alarm suppression using machine learning tools. It proposes a multi-modal detection algorithm to find the true beats using the information from all the available waveforms. This method uses a variety of ...
Heart Rate Pattern Recognition, Automated False Positive Reactions Clinical Alarms Humans Monitoring, Physiologic Signal Processing, Computer-Assisted Machine Learning Arrhythmias, Cardiac Intensive Care Units Electrocardiography
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Improved Fuzzy Logic System to Evaluate Milk Electrical Conductivity Signals from On-Line Sensors to Monitor Dairy Goat Mastitis.

Sensors (Basel, Switzerland) Jul 13, 2016
The aim of this study was to develop and test a new fuzzy logic model for monitoring the udder health status (HS) of goats. The model evaluated, as input variables, the milk electrical conductivity (EC) signal, acquired on-line for each gland by a de...
Monitoring, Physiologic Female Goats Animals Milk Mastitis Electric Conductivity Fuzzy Logic
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Machine Learning Techniques in Clinical Vision Sciences.

Current eye research Jun 30, 2016
This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and tr...
Multimodal Imaging Eye Diseases Vision, Ocular Diagnostic Techniques, Ophthalmological Algorithms Sensitivity and Specificity Monitoring, Physiologic Humans Machine Learning
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Real-time multi-channel monitoring of burst-suppression using neural network technology during pediatric status epilepticus treatment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Jun 11, 2016
OBJECTIVE: To develop a real-time monitoring system that has the potential to guide the titration of anesthetic agents in the treatment of pediatric status epilepticus (SE).
Child, Preschool Child Monitoring, Physiologic Electroencephalography Status Epilepticus Female Sensitivity and Specificity Male Adolescent Neural Networks, Computer Brain Intensive Care Units Humans
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Learning temporal rules to forecast instability in continuously monitored patients.

Journal of the American Medical Informatics Association : JAMIA Jun 6, 2016
Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. The appea...
Monitoring, Physiologic Respiratory Insufficiency Cardiovascular System Hospital Units Humans Machine Learning Forecasting Time Factors
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Monitoring of total positive end-expiratory pressure during mechanical ventilation by artificial neural networks.

Journal of clinical monitoring and computing Apr 11, 2016
Ventilation treatment of acute lung injury (ALI) requires the application of positive airway pressure at the end of expiration (PEEP) to avoid lung collapse. However, the total pressure exerted on the alveolar walls (PEEP) is the sum of PEEP and intr...
Treatment Outcome Monitoring, Physiologic Positive-Pressure Respiration Pattern Recognition, Automated Therapy, Computer-Assisted Manometry Neural Networks, Computer Animals Acute Lung Injury Reproducibility of Results Respiration, Artificial Sensitivity and Specificity Swine Diagnosis, Computer-Assisted
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Using a Calculated Pulse Rate with an Artificial Neural Network to Detect Irregular Interbeats.

Journal of medical systems Dec 7, 2015
Heart rate is an important clinical measure that is often used in pathological diagnosis and prognosis. Valid detection of irregular heartbeats is crucial in the clinical practice. We propose an artificial neural network using the calculated pulse ra...
Neural Networks, Computer Monitoring, Physiologic Signal Processing, Computer-Assisted Arrhythmias, Cardiac Heart Rate Infrared Rays Pulse Software Design Humans
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A novel approach for analysis of altered gait variability in amyotrophic lateral sclerosis.

Medical & biological engineering & computing Oct 30, 2015
Gait variability reflects important information for the maintenance of human beings' health. For pathological populations, changes in gait variability signal the presence of abnormal motor control strategies. Quantitative analysis of the altered gait...
Male Middle Aged Case-Control Studies ROC Curve Gait Humans Entropy Female Gait Disorders, Neurologic Aged Support Vector Machine Adult Monitoring, Physiologic Amyotrophic Lateral Sclerosis
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Real alerts and artifact classification in archived multi-signal vital sign monitoring data: implications for mining big data.

Journal of clinical monitoring and computing Oct 5, 2015
Huge hospital information system databases can be mined for knowledge discovery and decision support, but artifact in stored non-invasive vital sign (VS) high-frequency data streams limits its use. We used machine-learning (ML) algorithms trained on ...
Vital Signs Hospital Information Systems Oscillometry Clinical Alarms Female Middle Aged Blood Pressure Humans Aged Decision Support Systems, Clinical Area Under Curve Machine Learning Monitoring, Physiologic Adult Heart Rate Data Interpretation, Statistical Algorithms Male Data Mining Artifacts Risk
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