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

  • S.I.: Computational-based Biomarkers for Mental and Emotional Health(CBMEH2021)
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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.

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Notes

  1. https://who.int/news-room/fact-sheets/detail/depression.

  2. https://pulsesensor.com/.

  3. https://github.com/PIA-Group/BioSPPy.

  4. https://pulsesensor.com.

  5. https://bitalino.com/storage/uploads/media/eda-sensor-datasheet-revb.pdf.

  6. https://plux.info/electrodes/60-non-gelled-reusable-agagcl-electrodes-870122114.html.

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Acknowledgements

This work was partially funded by Fundação para a Ciência e Tecnologia (FCT) under the grant 2020.06675.BD and under the project PCIF/SSO/0163/2019 “SafeFire”, by the FCT/Ministério da Ciência, Tecnologia e Ensino Superior (MCTES) through national funds and when applicable co-funded by EU funds under the project UIDB/50008/2020, by the Instituto de Telecomunicações (IT), by the European Regional Development Fund (FEDER) through the Operational Competitiveness and Internationalization Programme (COMPETE 2020), and by National Funds (OE) through the FCT under the LISBOA-01-0247-FEDER-069918 “CardioLeather” and LISBOA-1-0247-FEDER-113480 “EpilFootSense”.

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Authors and Affiliations

  1. Department of Bioengineering (DBE), Instituto Superior Técnico (IST), Av. Rovisco Pais 1, 1049-001, Lisboa, Portugal

    Rafael Silva, Gonçalo Salvador, Patrícia Bota, Ana Fred & Hugo Plácido da Silva

  2. Instituto de Telecomunicações (IT), Av. Rovisco Pais 1, Torre Norte - Piso 10, 1049-001, Lisboa, Portugal

    Rafael Silva, Gonçalo Salvador, Patrícia Bota, Ana Fred & Hugo Plácido da Silva

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Appendices

A PPG signal analysis

See Tables 5.

Table 5 PPG time errors, amplitude errors and Pearson correlation coefficient values between down-sampled and original 1kHz signal for different interpolation methods and sampling frequencies. The number of peak counts in each essay is presented as well as mean, standard deviation (SD), minimum (Min) and maximum (Max) values. The Pearson correlation coefficient values and t of the estimated distribution are also described
Full size table

B EDA signal analysis

See Table 6.

Table 6 EDA time errors, amplitude errors and Pearson correlation coefficient values between down-sampled and original 1kHz signal for different interpolation methods and sampling frequencies. The number of peak counts in each essay is presented as well as mean, standard deviation (SD), minimum (Min) and maximum (Max) values. The Pearson correlation coefficient values and kurtosis of the estimated distribution are also described
Full size table

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Silva, R., Salvador, G., Bota, P. et al. Impact of sampling rate and interpolation on photoplethysmography and electrodermal activity signals’ waveform morphology and feature extraction. Neural Comput & Applic 35, 5661–5677 (2023). https://doi.org/10.1007/s00521-022-07212-6

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