AIMC Topic: Monitoring, Ambulatory

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Unsupervised Machine Learning for Developing Personalised Behaviour Models Using Activity Data.

Sensors (Basel, Switzerland) May 4, 2017
The goal of this study is to address two major issues that undermine the large scale deployment of smart home sensing solutions in people's homes. These include the costs associated with having to install and maintain a large number of sensors, and t...
Activities of Daily Living Monitoring, Ambulatory Housing Cluster Analysis Unsupervised Machine Learning
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In-lab versus at-home activity recognition in ambulatory subjects with incomplete spinal cord injury.

Journal of neuroengineering and rehabilitation Feb 6, 2017
BACKGROUND: Although commercially available activity trackers can aid in tracking therapy and recovery of patients, most devices perform poorly for patients with irregular movement patterns. Standard machine learning techniques can be applied on reco...
Humans Monitoring, Ambulatory Accelerometry Machine Learning Spinal Cord Injuries Female Posture Adult Walking Male Movement
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Deep Learning for Health Informatics.

IEEE journal of biomedical and health informatics Dec 29, 2016
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learn...
Medical Informatics Monitoring, Ambulatory Humans Machine Learning Public Health Computational Biology
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An Indoor Positioning System Based on Wearables for Ambient-Assisted Living.

Sensors (Basel, Switzerland) Dec 25, 2016
The urban population is growing at such a rate that by 2050 it is estimated that 84% of the world's population will live in cities, with flats being the most common living place. Moreover, WiFi technology is present in most developed country urban ar...
Internet Monitoring, Ambulatory Assisted Living Facilities Wireless Technology Humans Machine Learning Algorithms
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A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

IEEE journal of biomedical and health informatics Dec 23, 2016
The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires ...
Signal Processing, Computer-Assisted Monitoring, Ambulatory Human Activities Neural Networks, Computer Machine Learning Humans
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COMPOSE: Using temporal patterns for interpreting wearable sensor data with computer interpretable guidelines.

Computers in biology and medicine Dec 5, 2016
This paper describes a novel temporal logic-based framework for reasoning with continuous data collected from wearable sensors. The work is motivated by the Metabolic Syndrome, a cluster of conditions which are linked to obesity and unhealthy lifesty...
Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Humans Machine Learning Algorithms Metabolic Syndrome Practice Guidelines as Topic Europe Monitoring, Ambulatory Pattern Recognition, Automated
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Energy Efficient Monitoring of Metered Dose Inhaler Usage.

Journal of medical systems Oct 29, 2016
Life-long chronic inflammatory diseases of the airways, such as asthma and Chronic Obstructive Pulmonary Disease, are very common worldwide, affecting people of all ages, race and gender. One of the most important aspects for the effective management...
Support Vector Machine Monitoring, Ambulatory Administration, Inhalation Humans Medication Adherence Metered Dose Inhalers Bronchodilator Agents Data Compression Wireless Technology
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Accelerometer and Camera-Based Strategy for Improved Human Fall Detection.

Journal of medical systems Oct 29, 2016
In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving a...
Pattern Recognition, Automated Accelerometry Humans Support Vector Machine Algorithms Bayes Theorem Machine Learning Accidental Falls Monitoring, Ambulatory
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Activity Recognition for Diabetic Patients Using a Smartphone.

Journal of medical systems Oct 8, 2016
Diabetes is a disease that has to be managed through appropriate lifestyle. Technology can help with this, particularly when it is designed so that it does not impose an additional burden on the patient. This paper presents an approach that combines ...
Humans Machine Learning Algorithms Accelerometry Motor Activity Electrocardiography Diabetes Mellitus Geographic Information Systems Monitoring, Ambulatory Smartphone
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Prediction of Ventricular Tachycardia One Hour before Occurrence Using Artificial Neural Networks.

Scientific reports Aug 26, 2016
Ventricular tachycardia (VT) is a potentially fatal tachyarrhythmia, which causes a rapid heartbeat as a result of improper electrical activity of the heart. This is a potentially life-threatening arrhythmia because it can cause low blood pressure an...
Prognosis Monitoring, Ambulatory Heart Rate Humans Reproducibility of Results Tachycardia, Ventricular Neural Networks, Computer Early Diagnosis Sensitivity and Specificity Respiratory Rate
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