Article In: cienciavitae
Impact of sampling rate and interpolation on photoplethysmography and electrodermal activity signals' waveform morphology and feature extraction
Neural Computing and Applications
— 2022 — Neural Computing and Applications
Key information
Authors:
Published in
April 24, 2022
Abstract
The availability of low-cost biomedical devices has driven a growing interest in the use of physiological signals for mental and emotional health research. Due to their potential for integration in discrete wearable form factors, Photoplethysmography (PPG) and Electrodermal Activity (EDA) are particularly popular, especially in out-of-the-lab experiments. Although high-resolution data acquisition should be a priority, the sampling rate can greatly affect the power consumption and memory storage of the devices in long-term recordings. Moreover, systems with shared computational resources that simultaneously monitor different signals, can also have communication channel bandwidth constraints that limit the sampling rate. This work seeks to evaluate how the sampling rate and interpolation affect the signal quality of PPG and EDA signals, in terms of waveform morphology and feature extraction capabilities. We study the minimum sampling rate requirements for each signal, as well as the impact of interpolation methods on signal waveform reconstruction. Using a previously recorded dataset with signals originally recorded at 1 kHz, we simulate multiple lower sampling rates. Results show that for PPG a 50 Hz sampling rate with quadratic or cubic interpolation can achieve a temporal resolution identical to that of a 1 kHz acquisition, while for EDA the same can be said but with a 10 Hz sampling rate. Other recommendations are also proposed depending on the signal application.
Publication details
Authors in the community:
Rafael Luís Soares da Costa e Silva
ist186741
Gonçalo Filipe Duarte Salvador
ist186770
Patrícia Justo Bota
ist194679
Ana Luísa Nobre Fred
ist12170
Hugo Humberto Plácido da Silva
ist46129
Publication version
AO - Author's Original
Publisher
Neural Computing and Applications
Link to the publisher's version
https://link.springer.com/article/10.1007/s00521-022-07212-6
Title of the publication container
Neural Computing and Applications
Issue
CBMEH2021
ISSN
1433-3058
Fields of Science and Technology (FOS)
medical-engineering - Medical engineering
Keywords
- Affective computing
- Reflective photoplethysmography
- Electrodermal activity
- Sampling rate
- Interpolation
- Feature extraction
Publication language (ISO code)
eng - English
Alternative identifier (URI)
http://dx.doi.org/10.1007/s00521-022-07212-6
Rights type:
Only metadata available
Financing entity
Fundação para a Ciência e Tecnologia
Title of the project, award or grant: SafeFire
Number for the project, award or grant: 2020.06675.BD
Financing entity
European Regional Development Fund
Title of the project, award or grant: CardioLeather
Funding Stream: Operational Competitiveness and Internationalization Programme (COMPETE 2020)
Number for the project, award or grant: LISBOA-01-0247-FEDER-069918