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Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Published on: April 5, 2019

Heart rate analysis by sparse representation for acute pain detection.

Shai Tejman-Yarden^1,2,3, Ofer Levi⁴, Alex Beizerov⁵

¹Division of Pediatric Cardiology, Department of Pediatrics, University of California, San Diego, Rady Children's Hospital, San Diego, CA, USA. tegmanya@gmail.com.

Medical & Biological Engineering & Computing

|August 13, 2015

Summary

Objective pain assessment using advanced signal processing shows promise. The orthogonal matching pursuit (OMP) algorithm demonstrated higher specificity than wavelet transform (WT) for detecting acute pain via heart rate analysis.

Keywords:

Heart rate variability Orthogonal matching pursuit algorithm Pain Wavelet transform

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Area of Science:

Biomedical Engineering
Signal Processing
Pain Medicine

Background:

Current pain assessment relies on subjective methods, limiting objective measurement.
Advanced signal processing techniques like Wavelet Transform (WT) and Orthogonal Matching Pursuit (OMP) offer potential for objective pain detection.
These time-specific methods analyze physiological signals, such as heart rate, for pain-related changes.

Purpose of the Study:

To apply and compare WT and OMP algorithms for acute pain detection using heart rate samples.
To evaluate the efficacy of these methods in identifying pain events in healthy volunteers.

Main Methods:

Heart rate was sampled from 15 healthy volunteers during a 5-minute baseline and a cold pressor test (CPT).
Data analysis was performed using WT and OMP algorithms with a Fourier/Wavelet dictionary.
Statistical analysis, including two-way ANOVA, was used to compare the methods' performance.

Main Results:

Both WT and OMP showed significant increases in wavelet coefficient density during pain induction (CPT).
OMP analysis revealed a significant reduction in wavelet coefficient density during baseline compared to WT (p < 0.001).
OMP demonstrated higher specificity, distinguishing between basic signal harmonics and time-specific pain events.

Conclusions:

Both WT and OMP can accurately detect pain events without delay.
The OMP algorithm shows superior specificity for objective pain detection using heart rate variability.
Further research is needed to validate OMP's efficiency in diverse clinical settings.