Multirate Processing with Selective Subbands and Machine Learning for Efficient Arrhythmia Classification
The usage of wearable gadgets is growing in the cloud-based health monitoring systems. The signal compression, computational and power efficiencies play an imperative part in this scenario. In this context, we propose an efficient method for the diagnosis of cardiovascular diseases based on electroc...
Main Authors: | Saeed Mian Qaisar, Alaeddine Mihoub, Moez Krichen, Humaira Nisar |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/4/1511 |
Similar Items
-
Arrhythmia classification using multirate processing metaheuristic optimization and variational mode decomposition
by: Saeed Mian Qaisar, et al.
Published: (2023-01-01) -
Arrhythmia Diagnosis by Using Level-Crossing ECG Sampling and Sub-Bands Features Extraction for Mobile Healthcare
by: Saeed Mian Qaisar, et al.
Published: (2020-04-01) -
An ECG Stitching Scheme for Driver Arrhythmia Classification Based on Deep Learning
by: Do Hoon Kim, et al.
Published: (2023-03-01) -
A Multirate Control Strategy to the Slow Sensors Problem: An Interactive Simulation Tool for Controller Assisted Design
by: Julián Salt, et al.
Published: (2014-02-01) -
Subband Adaptive Array for DS-CDMA Mobile Radio
by: Tran Xuan Nam, et al.
Published: (2004-01-01)