16 research outputs found
Autonomous path following by fuzzy adaptive curvature-based point selection algorithm for four-wheel-steering car-like mobile robot
No full textDetection and classification of cardiovascular abnormalities using FFT based multi-objective genetic algorithm
No full textStable control of a heterogeneous platoon of vehicles with switched interaction topology, time-varying communication delay and lag of actuator
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An Adaptive Automatic EEG Signal Segmentation Method Based on Generalized Likelihood Ratio
No full textExtraction of ECG Significant Features for Remote CVD Monitoring
No full textRemote healthcare monitoring for Cardiovascular Diseases (CVD) in the present lifestyle is of the utmost importance throughout the world because of high mortality rate, around 30% of deaths all over the world are due to the CVD as per the World Health Organization (WHO) statistics. With the advancement of medical industry and huge growth in IoT technology is gradually making the remote CVD monitoring a reality. During the real-time Electrocardiography (ECG) acquisition, proper detection of individual ECG beats, and the extraction of essential features from each ECG beat is crucial to automate the diagnosis process of CVD remotely. Therefore, it is necessary to explore various techniques for the detection of CVD and the complexity involved in it. This chapter does the review and covers various methods to process the ECG signal and focuses on the low complexity algorithms to extract the significant clinical features of ECG
Neighborhood rough set based ECG signal classification for diagnosis of cardiac diseases
No full textA low-complexity data-adaptive approach for premature ventricular contraction recognition
No full textA Generalized Recursive Identification Algorithm Compensated by Orthogonal Weighted Kernel for Tracking Time-Variant Systems
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