Internet of Things with Maximal Overlap Discrete Wavelet Transform for Remote Health Monitoring of Abnormal ECG Signals

2018 ◽  
Vol 42 (11) ◽  
Author(s):  
Revathi Sundarasekar ◽  
M. Thanjaivadivel ◽  
Gunasekaran Manogaran ◽  
Priyan Malarvizhi Kumar ◽  
R. Varatharajan ◽  
...  
2014 ◽  
Vol 571-572 ◽  
pp. 1176-1179 ◽  
Author(s):  
Xiao Jing Meng ◽  
Huan Qing Cui ◽  
Rong Hua

With the development of economies, health has been paid more and more attention on in life. This paper introduces an Internet-of-Things-based health monitoring and management system, consisting of sensing, transportation, storage and application layers which have different functions. This system implements the health-monitoring and service-provision anywhere and anytime, and community-centered healthcare services.


Author(s):  
CHUANG-CHIEN CHIU ◽  
CHOU-MIN CHUANG ◽  
CHIH-YU HSU

The main purpose of this study is to present a novel personal authentication approach with the electrocardiogram (ECG) signal. The electrocardiogram is a recording of the electrical activity of the heart and the recorded signals can be used for individual verification because ECG signals of one person are never the same as those of others. The discrete wavelet transform was applied for extracting features that are the wavelet coefficients derived from digitized signals sampled from one-lead ECG signal. By the proposed approach applied on 35 normal subjects and 10 arrhythmia patients, the verification rate was 100% for normal subjects and 81% for arrhythmia patients. Furthermore, the performance of the ECG verification system was evaluated by the false acceptance rate (FAR) and false rejection rate (FRR). The FAR was 0.83% and FRR was 0.86% for a database containing only 35 normal subjects. When 10 arrhythmia patients were added into the database, FAR was 12.50% and FRR was 5.11%. The experimental results demonstrated that the proposed approach worked well for normal subjects. For this reason, it can be concluded that ECG used as a biometric measure for personal identity verification is feasible.


2008 ◽  
Vol 08 (03) ◽  
pp. 367-387 ◽  
Author(s):  
B. ZHU ◽  
A. Y. T. LEUNG ◽  
C. K. WONG ◽  
W. Z. LU

Presented herein is an experiment that aims to investigate the applicability of the wavelet transform to damage detection of a beam–spring structure. By burning out the string that is connected to the cantilever beam, high-frequency oscillations are excited in the beam–spring system, and there results an abrupt change or impulse in the discrete-wavelet-transformed signal. In this way, the discrete wavelet transform can be used to recognize the damage at the moment it occurs. In the second stage of damage detection, the shift of frequencies and damping ratios is identified by the continuous wavelet transform so as to ensure that the abrupt change or impulse in the signal from the discrete wavelet transform is a result of the damage and not the noise. For the random forced vibration, the random decrement technique is used on the original signal to obtain the free decaying responses, and then the continuous wavelet transform is applied to identify the system parameters. Some developed p version elements are used for the parametric studies on the first stage of health monitoring and to find the damage location. The results show that the two-stage method is successful in damage detection. Since the method is simple and computationally efficient, it is a good candidate for on-line health monitoring and damage detection of structures.


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