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1.
Article in English | MEDLINE | ID: mdl-26736228

ABSTRACT

This study proposes a unifying framework for m-Health video communication systems that provides for the joint optimization of video quality, bitrate demands, and encoding time. The framework is video modality and infrastructure independent and facilitates adaptation to the best available encoding mode that satisfies underlying technology and application imposed constraints. The scalability of the proposed algorithm is demonstrated using different HEVC encoding configurations and realistic modelling of 802.11× wireless infrastructure for emergency scenery and response videos. Extensive experimentation shows that a jointly optimal solution in the encoding time, bitrate, and video quality space is feasible.


Subject(s)
Disasters , Emergency Medicine/methods , Video Recording/methods , Wireless Technology , Algorithms , Computer Communication Networks , Decision Support Techniques , Humans , Telemedicine/instrumentation , Wireless Technology/instrumentation
2.
Article in English | MEDLINE | ID: mdl-26736267

ABSTRACT

Non-invasive ultrasound imaging of carotid plaques can provide information on the characteristics of the arterial wall including the size, morphology and texture of the atherosclerotic plaques. Several studies were carried out that demonstrated the usefulness of these feature sets for differentiating between asymptomatic and symptomatic plaques and their corresponding cerebrovascular risk stratification. The aim of this study was to develop predictive modelling for estimating the time period of a stroke event by determining the risk for short term (less or equal to three years) or long term (more than three years) events. Data from 108 patients that had a stroke event have been used. The information collected included clinical and ultrasound imaging data. The prediction was performed at base line where patients were still asymptomatic. Several image texture analysis and clinical features were used in order to create a classification model. The different features were statistically analyzed and we conclude that image texture analysis features extracted using Spatial Gray Level Dependencies method had the best statistical significance. Several predictive models were derived based on Binary Logistic Regression (BLR) and Support Vector Machines (SVM) modelling. The best results were obtained with the SVM modelling models with an average correct classifications score of 77±7% for differentiating between stroke event occurrences within 3 years versus more than 3 years. Further work is needed in investigating additional multiscale texture analysis features as well as more modelling techniques on more subjects.


Subject(s)
Carotid Arteries/diagnostic imaging , Plaque, Atherosclerotic/diagnostic imaging , Stroke/diagnosis , Ultrasonography/methods , Carotid Arteries/pathology , Humans , Ischemia/diagnosis , Ischemia/diagnostic imaging , Logistic Models , Plaque, Atherosclerotic/complications , Risk Factors , Sensitivity and Specificity , Stroke/etiology , Support Vector Machine , Time Factors
3.
Article in English | MEDLINE | ID: mdl-24111419

ABSTRACT

The emergence of the new, High Efficiency Video Coding (HEVC) standard, combined with wide deployment of 4G wireless networks, will provide significant support toward the adoption of mobile-health (m-health) medical video communication systems in standard clinical practice. For the first time since the emergence of m-health systems and services, medical video communication systems can be deployed that can rival the standards of in-hospital examinations. In this paper, we provide a thorough overview of today's advancements in the field, discuss existing approaches, and highlight the future trends and objectives.


Subject(s)
Computer Communication Networks , Telemedicine/instrumentation , Algorithms , Communication , Diagnosis, Computer-Assisted , Equipment Design , Humans , Signal Processing, Computer-Assisted , Telemedicine/methods , Video Recording , Wireless Technology
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