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2020 | OriginalPaper | Buchkapitel

Mechanical Pain Assessment Through Parameters Derived from Photoplethysmographic (PPG) Signals: A Pilot Study

verfasst von : Andrés David Ramírez Mena, Leonardo Antonio Bermeo Varón, Rodolfo Molano Valencia, Erick Javier Argüello Prada

Erschienen in: Applied Technologies

Verlag: Springer International Publishing

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Abstract

Based on the fact that pain modulates the contour of the photoplethysmographic (PPG) signal, several authors have used PPG-derived parameters, like the amplitude of the PPG signal (PPGA) and the variations of the inter-pulse intervals (i.e., the pulse rate variability – PRV), for pain measurement. However, all those studies were limited to use PPG-derived parameters to assess only thermally evoked pain and no recent studies seem to be available to examine whether it is possible to measure the intensity of the pain evoked by mechanical stimulation. The present study aims to analyze whether it is possible to assess the intensity of mechanically induced pain by using PPG-derived parameters. PPG signals were recorded from fifteen healthy subjects during 6 min, and three force stimuli (3, 6 and 9 N) were applied in ascendant order at 90 s intervals to induce three different levels of pain: low, medium and high. The PPGA, the heart rate (HR), and the high-frequency band (0.15 to 0.4 Hz) power of the pulse rate variability (PRV-HF) were computed before and after the initiation of mechanical stimulation and the percentage of change was calculated for each stimulus intensity. Results show that, even though all of the parameters varied considerably in response to painful stimuli, none of them were able to differentiate between three aforementioned levels of mechanical pain. Only HR was capable of differentiating between low and medium pain, as well as between low and high pain.

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Metadaten
Titel
Mechanical Pain Assessment Through Parameters Derived from Photoplethysmographic (PPG) Signals: A Pilot Study
verfasst von
Andrés David Ramírez Mena
Leonardo Antonio Bermeo Varón
Rodolfo Molano Valencia
Erick Javier Argüello Prada
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-42517-3_13