Document Detail


A system for the model based emergency detection and communication for the telerehabilitation training of cardiopulmonary patients.
MedLine Citation:
PMID:  23365989     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Cardiopulmonary diseases affect millions of people and cause high costs in health care systems worldwide. Patients should perform regular endurance exercises to stabilize their health state and prevent further impairment. However, patients are often uncertain about the level of intensity they should exercise in their current condition. The cost of continuous monitoring for these training sessions in clinics is high and additionally requires the patient to travel to a clinic for each single session. Performing the rehabilitation training at home can raise compliance and reduce costs. To ensure safe telerehabilitation training and to enable patients to control their performance and health state, detection of abnormal events during training is a critical prerequisite. Therefore, we created a model that predicts the heart rate of cardiopulmonary patients and that can be used to detect and avoid abnormal health states. To enable external feedback and an immediate reaction in case of a critical situation, the patient should have the possibility to configure the system to communicate warnings and emergency events to clinical and non-clinical actors. To fulfill this task, we coupled a personal health record (PHR) with a new component that extends the classic home emergency systems. The PHR is also used for a training schedule definition that makes use of the predictive HR model. We used statistical methods to evaluate the prediction model and found that our prediction error of 3.2 heart beats per minute is precise enough to enable a detection of critical states. The concept for the communication of alerts was evaluated through focus group interviews with domain experts who judged that it fulfills the needs of potential users.
Authors:
Axel Helmer; Friedrich Kretschmer; Riana Deparade; Bianying Song; Markus Meis; Andreas Hein; Michael Marschollek; Uwe Tegtbur
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2012     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2012  
Date Detail:
Created Date:  2013-01-31     Completed Date:  2013-09-06     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  702-6     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Emergencies
Exercise Therapy
Health Records, Personal
Health Status
Heart Diseases / physiopathology,  rehabilitation*
Heart Rate
Humans
Linear Models
Models, Cardiovascular
Pulmonary Disease, Chronic Obstructive / physiopathology,  rehabilitation*
Telemedicine / methods*
Telemetry / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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