AIMC Topic: Monitoring, Physiologic

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Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

Journal of clinical monitoring and computing Sep 27, 2018
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiolog...
Sensitivity and Specificity Infant Child, Preschool Child Critical Illness Infant, Newborn Reproducibility of Results Signal Processing, Computer-Assisted Heart Rate Critical Care Systole Intensive Care Units, Pediatric Monitoring, Physiologic Blood Pressure Oxygen Humans Machine Learning Software Respiratory Rate Heart Arrest
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Estrous detection by continuous measurements of vaginal temperature and conductivity with supervised machine learning in cattle.

Theriogenology Sep 27, 2018
This study aimed to evaluate the effectiveness of estrous detection technique based on continuous measurements of vaginal temperature (VT) and conductivity (VC) with supervised machine learning in cattle. The VT and VC of 17 cows in tie-stalls were m...
Supervised Machine Learning Body Temperature Sexual Behavior, Animal Estrus Animals Cattle Longitudinal Studies Monitoring, Physiologic Female Reproducibility of Results
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Digital diabetes: Perspectives for diabetes prevention, management and research.

Diabetes & metabolism Sep 19, 2018
Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden remote monitoring of patients' symptoms, physiological data, behaviours, and social and environmental ...
Monitoring, Physiologic Data Interpretation, Statistical Internet Telemedicine Inventions Artificial Intelligence Biomedical Research Big Data Humans Diabetes Mellitus
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A Wearable Multi-Modal Bio-Sensing System Towards Real-World Applications.

IEEE transactions on bio-medical engineering Sep 4, 2018
Multi-modal bio-sensing has recently been used as effective research tools in affective computing, autism, clinical disorders, and virtual reality among other areas. However, none of the existing bio-sensing systems support multi-modality in a wearab...
Monitoring, Physiologic Electroencephalography Equipment Design Brain-Computer Interfaces Wearable Electronic Devices Photoplethysmography Electrocardiography Humans Evoked Potentials, Visual Machine Learning Video Games Algorithms Head Movements
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A Time-Distributed Spatiotemporal Feature Learning Method for Machine Health Monitoring with Multi-Sensor Time Series.

Sensors (Basel, Switzerland) Sep 3, 2018
Data-driven methods with multi-sensor time series data are the most promising approaches for monitoring machine health. Extracting fault-sensitive features from multi-sensor time series is a daunting task for both traditional data-driven methods and ...
Deep Learning Time Factors Monitoring, Physiologic Humans Health
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Sensor, Signal, and Imaging Informatics in 2017.

Yearbook of medical informatics Aug 29, 2018
OBJECTIVE:  To summarize significant contributions to sensor, signal, and imaging informatics literature published in 2017.
Humans Machine Learning Electrocardiography Signal Processing, Computer-Assisted Monitoring, Physiologic Radiography Diagnostic Imaging
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Automatic Classification of Gait Impairments Using a Markerless 2D Video-Based System.

Sensors (Basel, Switzerland) Aug 21, 2018
Systemic disorders affecting an individual can cause gait impairments. Successful acquisition and evaluation of features representing such impairments make it possible to estimate the severity of those disorders, which is important information for mo...
Fiducial Markers Biomechanical Phenomena Male Support Vector Machine Monitoring, Physiologic Humans Gait Female Video Recording Sensitivity and Specificity Automation Foot
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Detection of Talking in Respiratory Signals: A Feasibility Study Using Machine Learning and Wearable Textile-Based Sensors.

Sensors (Basel, Switzerland) Jul 31, 2018
Social isolation and loneliness are major health concerns in young and older people. Traditional approaches to monitor the level of social interaction rely on self-reports. The goal of this study was to investigate if wearable textile-based sensors c...
Wearable Electronic Devices Canada Monitoring, Physiologic Young Adult Feasibility Studies Humans Adult Social Isolation Machine Learning Male Respiration Female Speech Textiles
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Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch.

Physiological measurement Jul 23, 2018
OBJECTIVE: Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupe...
Healthy Volunteers Shoulder Physical Therapy Modalities Machine Learning Computers, Handheld Female Young Adult Monitoring, Physiologic Adult Signal Processing, Computer-Assisted Patient Compliance Humans Male Exercise Therapy Neural Networks, Computer Middle Aged Support Vector Machine
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Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor.

IEEE journal of biomedical and health informatics Jul 20, 2018
OBJECTIVE: Utilizing passive radio frequency identification (RFID) tags embedded in knitted smart-garment devices, we wirelessly detect the respiratory state of a subject using an ensemble-based learning approach over an augmented Kalman-filtered tim...
Infant Wearable Electronic Devices Monitoring, Physiologic Signal Processing, Computer-Assisted Humans Respiratory Rate Machine Learning Radio Frequency Identification Device Algorithms
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