Volume 21, Issue 1 (March 2025)                   IJEEE 2025, 21(1): 3277-3277 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Alizadeh Aliabadi M, Karimi M, Karimi Z, soheili Fard M. The Effect of Photoplethysmography Signal Denoising on Compression Quality. IJEEE 2025; 21 (1) :3277-3277
URL: http://ijeee.iust.ac.ir/article-1-3277-en.html
The Effect of Photoplethysmography Signal Denoising on Compression Quality
Mohammadreza Alizadeh Aliabadi , Mohsen Karimi , Zahra Karimi , Mehrdad Soheili Fard
Abstract:   (278 Views)
Photoplethysmography (PPG) signals provide a non-invasive means of monitoring cardiovascular status during physical exercise; however, they are prone to noise, especially motion artifacts (MA). For specific telemedicine applications, compression is necessary for tasks such as PPG signal generation and secure data transmission. In this study, the investigation focused on determining whether it is better to perform compression before or after noise removal by applying a noise removal method and various compression methods. To achieve the aim, the study explored a subspace-based denoising method called "Maximum Uncorrelated PPG Denoising." Additionally, signal compression methods were examined in nine distinct steps. Compression quality is evaluated using various criteria, such as compression rate (CR) and Percentage Root Mean Square Difference (PRD). The results showed that regardless of the type of compression method, it is better not to remove noise before the compression process because doing so reduces CR and increases PRD.
Keywords: Photoplethysmography (PPG), signal denoising, compression ratio (CR), Percentage Root Mean Square Difference (PRD).
Full-Text [PDF 1137 kb]   (124 Downloads)    
Type of Study: Research Paper | Subject: Biomedical Signal Processing
Received: 2024/05/12 | Revised: 2025/02/04 | Accepted: 2024/12/17
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.