HeartSaver: A mobile cardiac monitoring system for auto-detection of atrial fibrillation, myocardial infarction, and atrio-ventricular block

被引:46
作者
Sankari, Ziad [1 ,5 ]
Adeli, Hojjat [1 ,2 ,3 ,4 ,5 ,6 ]
机构
[1] Ohio State Univ, Dept Biomed Engn, Columbus, OH 43210 USA
[2] Ohio State Univ, Dept Biomed Informat, Columbus, OH 43210 USA
[3] Ohio State Univ, Dept Civil & Environm Engn, Columbus, OH 43210 USA
[4] Ohio State Univ, Dept Geodet Sci, Columbus, OH 43210 USA
[5] Ohio State Univ, Dept Elect & Comp Engn, Columbus, OH 43210 USA
[6] Ohio State Univ, Dept Neurol Surg & Neurosci, Columbus, OH 43210 USA
关键词
Cardiac monitoring systems; Heart; FUNCTION NEURAL-NETWORK; EEG-BASED DIAGNOSIS; WAVELET-CHAOS METHODOLOGY; ST-SEGMENT ELEVATION; WORK ZONE CAPACITY; INCIDENT-DETECTION; ALZHEIMERS-DISEASE; DYNAMICS MODEL; SEIZURE; OPTIMIZATION;
D O I
10.1016/j.compbiomed.2011.02.002
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A mobile medical device, dubbed HeartSaver, is developed for real-time monitoring of a patient's electrocardiogram (ECG) and automatic detection of several cardiac pathologies, including atrial fibrillation, myocardial infarction and atrio-ventricular block. HeartSaver is based on adroit integration of four different modern technologies: electronics, wireless communication, computer, and information technologies in the service of medicine. The physical device consists of four modules: sensor and ECG processing unit, a microcontroller, a link between the microcontroller and the cell phone, and mobile software associated with the system. HeartSaver includes automated cardiac pathology detection algorithms. These algorithms are simple enough to be implemented on a low-cost, limited-power microcontroller but powerful enough to detect the relevant cardiac pathologies. When an abnormality is detected, the microcontroller sends a signal to a cell phone. This operation triggers an application software on the cell phone that sends a text message transmitting information about patient's physiological condition and location promptly to a physician or a guardian. HeartSaver can be used by millions of cardiac patients with the potential to transform the cardiac diagnosis, care, and treatment and save thousands of lives. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:211 / 220
页数:10
相关论文
共 69 条
[1]   Dynamic fuzzy wavelet neural network model for structural system identification [J].
Adeli, H ;
Jiang, XM .
JOURNAL OF STRUCTURAL ENGINEERING, 2006, 132 (01) :102-111
[2]  
Adeli H, 2005, J ALZHEIMERS DIS, V7, P187
[3]   Alzheimer's disease: Models of computation and analysis of EEGs [J].
Adeli, H ;
Ghosh-Dastidar, S ;
Dadmehr, N .
CLINICAL EEG AND NEUROSCIENCE, 2005, 36 (03) :131-140
[4]   Neuro-fuzzy logic model for freeway work zone capacity estimation [J].
Adeli, H ;
Jiang, XM .
JOURNAL OF TRANSPORTATION ENGINEERING, 2003, 129 (05) :484-493
[5]   Analysis of EEG records in an epileptic patient using wavelet transform [J].
Adeli, H ;
Zhou, Z ;
Dadmehr, N .
JOURNAL OF NEUROSCIENCE METHODS, 2003, 123 (01) :69-87
[6]   A NEURAL DYNAMICS MODEL FOR STRUCTURAL OPTIMIZATION - THEORY [J].
ADELI, H ;
PARK, HS .
COMPUTERS & STRUCTURES, 1995, 57 (03) :383-390
[7]   Neural network model for optimization of cold-formed steel beams [J].
Adeli, H ;
Karim, A .
JOURNAL OF STRUCTURAL ENGINEERING-ASCE, 1997, 123 (11) :1535-1543
[8]   COUNTERPROPAGATION NEURAL NETWORKS IN STRUCTURAL-ENGINEERING [J].
ADELI, H ;
PARK, HS .
JOURNAL OF STRUCTURAL ENGINEERING-ASCE, 1995, 121 (08) :1205-1212
[9]   A spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's disease [J].
Adeli, Hojjat ;
Ghosh-Dastidar, Samanwoy ;
Dadmehr, Nahid .
NEUROSCIENCE LETTERS, 2008, 444 (02) :190-194
[10]   A wavelet-chaos methodology for analysis of EEGs and EEG subbands to detect seizure and epilepsy [J].
Adeli, Hojjat ;
Ghosh-Dastidar, Samanwoy ;
Dadmehr, Nahid .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2007, 54 (02) :205-211