Back to Search
Start Over
Cloud-Based Smart Health Monitoring System for Automatic Cardiovascular and Fall Risk Assessment in Hypertensive Patients.
- Source :
-
Journal of Medical Systems . Oct2015, Vol. 39 Issue 10, p1-7. 7p. - Publication Year :
- 2015
-
Abstract
- The aim of this paper is to describe the design and the preliminary validation of a platform developed to collect and automatically analyze biomedical signals for risk assessment of vascular events and falls in hypertensive patients. This m-health platform, based on cloud computing, was designed to be flexible, extensible, and transparent, and to provide proactive remote monitoring via data-mining functionalities. A retrospective study was conducted to train and test the platform. The developed system was able to predict a future vascular event within the next 12 months with an accuracy rate of 84 % and to identify fallers with an accuracy rate of 72 %. In an ongoing prospective trial, almost all the recruited patients accepted favorably the system with a limited rate of inadherences causing data losses (<20 %). The developed platform supported clinical decision by processing tele-monitored data and providing quick and accurate risk assessment of vascular events and falls. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ACTIGRAPHY
*AUTOMATION
*CARDIOVASCULAR diseases risk factors
*CHI-squared test
*CONFIDENCE intervals
*DECISION support systems
*ELECTROCARDIOGRAPHY
*ACCIDENTAL falls
*HYPERTENSION
*INFORMATION storage & retrieval systems
*MEDICAL databases
*LONGITUDINAL method
*MEDICAL ethics
*PATIENT monitoring
*PRIVACY
*RESEARCH funding
*RISK assessment
*SYSTEMS design
*TELEMEDICINE
*DATA mining
*WEARABLE technology
*REMOTE access networks
*DATA security
*CONTENT mining
*CLOUD computing
*RETROSPECTIVE studies
*RECEIVER operating characteristic curves
*MOBILE apps
*DESCRIPTIVE statistics
RESEARCH evaluation
Subjects
Details
- Language :
- English
- ISSN :
- 01485598
- Volume :
- 39
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Journal of Medical Systems
- Publication Type :
- Academic Journal
- Accession number :
- 115925186
- Full Text :
- https://doi.org/10.1007/s10916-015-0294-3