Heart rate analysis by sparse representation for acute pain detection

S. Tejman-Yarden; O. Levi; A. Beizerov; Y. Parmet; T. Nguyen; M. Saunders; Z. Rudich; J. C. Perry; D. G. Baker; T. Moeller-Bertram

doi:https://doi.org/10.1007/978-3-319-12967-9_29

Heart rate analysis by sparse representation for acute pain detection

S. Tejman-Yarden, O. Levi, A. Beizerov, Y. Parmet, T. Nguyen, M. Saunders, Z. Rudich, J. C. Perry, D. G. Baker, T. Moeller-Bertram

Ben-Gurion University of the Negev

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Conclusion: HR analysis by both methods has successfully indicated the painful event at its onset, without delay. Statistical analysis proved OMP to be by far more specific. This is an initial study using OMP for pain detection. Further studies need to prove the validity of this system for pain detection in different settings.

Results: Data of 11 subjects was analyzed. Compared to baseline, WT analysis showed a significant wavelet coefficients frequency (WCF) increase during the pain incline period (p<0.01) and the entire CPT (p<0.01), with significantly higher amplitudes. OMP analysis showed a significant WCF increase during pain incline and decline periods (p<0.01, p<0.05) and the entire CPT (p<0.001), with suggestive higher amplitudes. Comparing the methods, during the baseline period there was a significant reduction of WCF using OMP analysis (p<0.001). Analysis by the two way ANOVA with repeated measures showed a significant proportional increase of WCF during the incline period and the entire CPT using OMP (p<0.01).

Objective pain assessment has not yet been achieved. Advanced signal processing methodologies, including the wavelet transform (WT) and the Orthogonal Matching Pursuit algorithm (OMP) were developed in the past two decades. The aim of this study was to apply and compare these time specific methods to heart rate samples of healthy subjects to investigate indicators of acute pain.

Methods: 15 adult volunteers participated in a study conducted in the pain clinic at a single center. Each subject’s heart rate (HR) was sampled for 5 minutes baseline followed by a cold pressor test (CPT). Analysis was done by WT and OMP with a Fourier/Wavelet dictionary separately.

Original language	English
Title of host publication	16th Nordic-Baltic Conference on Biomedical Engineering - 16. NBC and 10. MTD 2014 Joint Conferences
Editors	Mikael Persson, Henrik Mindedal
Pages	105-108
Number of pages	4
ISBN (Electronic)	9783319129662
DOIs	https://doi.org/10.1007/978-3-319-12967-9_29
State	Published - 1 Jan 2015
Event	16th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics and Medicinteknikdagarna Joint Conferences, NBC 2014 and MTD 2014 - Gothenburg, Sweden Duration: 14 Oct 2014 → 16 Oct 2014

Publication series

Name	IFMBE Proceedings
Volume	48

Conference

Conference	16th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics and Medicinteknikdagarna Joint Conferences, NBC 2014 and MTD 2014
Country/Territory	Sweden
City	Gothenburg
Period	14/10/14 → 16/10/14

Keywords

Heart Rate Variability
Orthogonal Matching Pursuit
Pain
Wavelet Transform

All Science Journal Classification (ASJC) codes

Bioengineering
Biomedical Engineering

Access to Document

https://doi.org/10.1007/978-3-319-12967-9_29

Cite this

Tejman-Yarden, S., Levi, O., Beizerov, A., Parmet, Y., Nguyen, T., Saunders, M., Rudich, Z., Perry, J. C., Baker, D. G., & Moeller-Bertram, T. (2015). Heart rate analysis by sparse representation for acute pain detection. In M. Persson, & H. Mindedal (Eds.), 16th Nordic-Baltic Conference on Biomedical Engineering - 16. NBC and 10. MTD 2014 Joint Conferences (pp. 105-108). (IFMBE Proceedings; Vol. 48). https://doi.org/10.1007/978-3-319-12967-9_29

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title = "Heart rate analysis by sparse representation for acute pain detection",

abstract = "Conclusion: HR analysis by both methods has successfully indicated the painful event at its onset, without delay. Statistical analysis proved OMP to be by far more specific. This is an initial study using OMP for pain detection. Further studies need to prove the validity of this system for pain detection in different settings.Results: Data of 11 subjects was analyzed. Compared to baseline, WT analysis showed a significant wavelet coefficients frequency (WCF) increase during the pain incline period (p<0.01) and the entire CPT (p<0.01), with significantly higher amplitudes. OMP analysis showed a significant WCF increase during pain incline and decline periods (p<0.01, p<0.05) and the entire CPT (p<0.001), with suggestive higher amplitudes. Comparing the methods, during the baseline period there was a significant reduction of WCF using OMP analysis (p<0.001). Analysis by the two way ANOVA with repeated measures showed a significant proportional increase of WCF during the incline period and the entire CPT using OMP (p<0.01).Objective pain assessment has not yet been achieved. Advanced signal processing methodologies, including the wavelet transform (WT) and the Orthogonal Matching Pursuit algorithm (OMP) were developed in the past two decades. The aim of this study was to apply and compare these time specific methods to heart rate samples of healthy subjects to investigate indicators of acute pain.Methods: 15 adult volunteers participated in a study conducted in the pain clinic at a single center. Each subject{\textquoteright}s heart rate (HR) was sampled for 5 minutes baseline followed by a cold pressor test (CPT). Analysis was done by WT and OMP with a Fourier/Wavelet dictionary separately.",

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author = "S. Tejman-Yarden and O. Levi and A. Beizerov and Y. Parmet and T. Nguyen and M. Saunders and Z. Rudich and Perry, {J. C.} and Baker, {D. G.} and T. Moeller-Bertram",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 16th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics and Medicinteknikdagarna Joint Conferences, NBC 2014 and MTD 2014 ; Conference date: 14-10-2014 Through 16-10-2014",

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doi = "https://doi.org/10.1007/978-3-319-12967-9_29",

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series = "IFMBE Proceedings",

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Tejman-Yarden, S, Levi, O, Beizerov, A, Parmet, Y, Nguyen, T, Saunders, M, Rudich, Z, Perry, JC, Baker, DG & Moeller-Bertram, T 2015, Heart rate analysis by sparse representation for acute pain detection. in M Persson & H Mindedal (eds), 16th Nordic-Baltic Conference on Biomedical Engineering - 16. NBC and 10. MTD 2014 Joint Conferences. IFMBE Proceedings, vol. 48, pp. 105-108, 16th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics and Medicinteknikdagarna Joint Conferences, NBC 2014 and MTD 2014, Gothenburg, Sweden, 14/10/14. https://doi.org/10.1007/978-3-319-12967-9_29

Heart rate analysis by sparse representation for acute pain detection. / Tejman-Yarden, S.; Levi, O.; Beizerov, A. et al.
16th Nordic-Baltic Conference on Biomedical Engineering - 16. NBC and 10. MTD 2014 Joint Conferences. ed. / Mikael Persson; Henrik Mindedal. 2015. p. 105-108 (IFMBE Proceedings; Vol. 48).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Heart rate analysis by sparse representation for acute pain detection

AU - Tejman-Yarden, S.

AU - Levi, O.

AU - Beizerov, A.

AU - Parmet, Y.

AU - Nguyen, T.

AU - Saunders, M.

AU - Rudich, Z.

AU - Perry, J. C.

AU - Baker, D. G.

AU - Moeller-Bertram, T.

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Conclusion: HR analysis by both methods has successfully indicated the painful event at its onset, without delay. Statistical analysis proved OMP to be by far more specific. This is an initial study using OMP for pain detection. Further studies need to prove the validity of this system for pain detection in different settings.Results: Data of 11 subjects was analyzed. Compared to baseline, WT analysis showed a significant wavelet coefficients frequency (WCF) increase during the pain incline period (p<0.01) and the entire CPT (p<0.01), with significantly higher amplitudes. OMP analysis showed a significant WCF increase during pain incline and decline periods (p<0.01, p<0.05) and the entire CPT (p<0.001), with suggestive higher amplitudes. Comparing the methods, during the baseline period there was a significant reduction of WCF using OMP analysis (p<0.001). Analysis by the two way ANOVA with repeated measures showed a significant proportional increase of WCF during the incline period and the entire CPT using OMP (p<0.01).Objective pain assessment has not yet been achieved. Advanced signal processing methodologies, including the wavelet transform (WT) and the Orthogonal Matching Pursuit algorithm (OMP) were developed in the past two decades. The aim of this study was to apply and compare these time specific methods to heart rate samples of healthy subjects to investigate indicators of acute pain.Methods: 15 adult volunteers participated in a study conducted in the pain clinic at a single center. Each subject’s heart rate (HR) was sampled for 5 minutes baseline followed by a cold pressor test (CPT). Analysis was done by WT and OMP with a Fourier/Wavelet dictionary separately.

AB - Conclusion: HR analysis by both methods has successfully indicated the painful event at its onset, without delay. Statistical analysis proved OMP to be by far more specific. This is an initial study using OMP for pain detection. Further studies need to prove the validity of this system for pain detection in different settings.Results: Data of 11 subjects was analyzed. Compared to baseline, WT analysis showed a significant wavelet coefficients frequency (WCF) increase during the pain incline period (p<0.01) and the entire CPT (p<0.01), with significantly higher amplitudes. OMP analysis showed a significant WCF increase during pain incline and decline periods (p<0.01, p<0.05) and the entire CPT (p<0.001), with suggestive higher amplitudes. Comparing the methods, during the baseline period there was a significant reduction of WCF using OMP analysis (p<0.001). Analysis by the two way ANOVA with repeated measures showed a significant proportional increase of WCF during the incline period and the entire CPT using OMP (p<0.01).Objective pain assessment has not yet been achieved. Advanced signal processing methodologies, including the wavelet transform (WT) and the Orthogonal Matching Pursuit algorithm (OMP) were developed in the past two decades. The aim of this study was to apply and compare these time specific methods to heart rate samples of healthy subjects to investigate indicators of acute pain.Methods: 15 adult volunteers participated in a study conducted in the pain clinic at a single center. Each subject’s heart rate (HR) was sampled for 5 minutes baseline followed by a cold pressor test (CPT). Analysis was done by WT and OMP with a Fourier/Wavelet dictionary separately.

KW - Heart Rate Variability

KW - Orthogonal Matching Pursuit

KW - Pain

KW - Wavelet Transform

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U2 - https://doi.org/10.1007/978-3-319-12967-9_29

DO - https://doi.org/10.1007/978-3-319-12967-9_29

M3 - منشور من مؤتمر

T3 - IFMBE Proceedings

SP - 105

EP - 108

BT - 16th Nordic-Baltic Conference on Biomedical Engineering - 16. NBC and 10. MTD 2014 Joint Conferences

A2 - Persson, Mikael

A2 - Mindedal, Henrik

T2 - 16th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics and Medicinteknikdagarna Joint Conferences, NBC 2014 and MTD 2014

Y2 - 14 October 2014 through 16 October 2014

ER -

Tejman-Yarden S, Levi O, Beizerov A, Parmet Y, Nguyen T, Saunders M et al. Heart rate analysis by sparse representation for acute pain detection. In Persson M, Mindedal H, editors, 16th Nordic-Baltic Conference on Biomedical Engineering - 16. NBC and 10. MTD 2014 Joint Conferences. 2015. p. 105-108. (IFMBE Proceedings). doi: https://doi.org/10.1007/978-3-319-12967-9_29

Heart rate analysis by sparse representation for acute pain detection

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Keywords

All Science Journal Classification (ASJC) codes

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