Article In: cienciavitae

Impact of sampling rate and interpolation on photoplethysmography and electrodermal activity signals' waveform morphology and feature extraction

Neural Computing and Applications

Silva, Rafael; Salvador, Gonçalo; Plácido da Silva, Hugo — 2022 — Neural Computing and Applications

Key information

Authors:

Silva, Rafael (Rafael Luís Soares da Costa e Silva); Salvador, Gonçalo (Gonçalo Filipe Duarte Salvador); Bota, Patrícia (Patrícia Justo Bota); Fred, Ana (Ana Luísa Nobre Fred); Plácido da Silva, Hugo (Hugo Humberto Plácido da Silva)

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

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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