Assessment of Pain Expression in Infant Cry Signals Using Empirical Mode Decomposition

Summary

Background:The presence of decoupling, i.e. the absence of coupling between fundamental frequency variation and intensity contour during phonetic crying, and its extent, reflects the degree of maturation of the central nervous system.

Objectives: The aim of this work was to evaluate whether Empirical Mode Decomposition (EMD) is a suitable technique for analyzing infant cries. We hereby wanted to assess the existence and extent of decoupling in term neonates and whether an association between decoupling (derived from EMD) and clinical pain expression could be unveiled.

Methods: To assess decoupling in healthy term neonates during procedural pain, 24 newborns were videotaped and crying was recorded during venous blood sampling. Besides acoustic analysis, pain expression was quantified based on the Modified Behavioral Pain Scale (MBPS). Fundamental frequency and the intensity contour of the cry signals were extracted by applying the EMD to the data, and the correlation between the two was studied.

Results: Based on data collected in healthy term neonates, correlation coefficients varied between 0.39 and 0.83. The degree of decoupling displayed extended variability between the neonates and also in different cry bouts in a crying sequence within an individual neonate.

Conclusion: When considering the individual ratio between the mean correlation of cry bouts during a crying sequence and their standard deviation, there seems to be a positive trend with increasing MBPS value. This might indicate that higher stressed subjects have less consistency in the investigated acoustic cry features, concluding that EMD has potential in the assessment of infant cry analysis.

Keywords

Empirical mode decomposition - phonetic crying - pain expression - neonates

• References

• 1 Bellieni CV, Sisto R, Codelli BM, Buonocore G. Cry features reflect pain intensity in term newborns: an alarm threshold. Pediatric Research 2004; 55 (01) 142-146.
• 2 Facchini A, Bellieni CV, Marchettini N, Pulselli FM, Tiezzi EB. Relating pain intensity of newborns to onset of non-linear phenomena in cry recordings. Phys Lett 2005; 338: 332-337.
• 3 Moller S, Schonweiler R. Analysis of infant cries for the early detection of hearing impairment. Speech Com 1999; 28: 175-193.
• 4 Wolf P. The natural history of crying and other vocalization in early infancy. Determinants of infant behavior. 1969 pp 81-109.
• 5 Barr RG, Hopkins B, Green JA. Crying as a sign, a symptom and a signal. Mac Keith Press; 2000. pp 143-146.
• 6 Huang NE, Shen Z, Long HR, Wu MC, Shih HH, Zheng Q. et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc London 1998; 454: 903-995.
• 7 LaGasse L, Neal A, Lester B. Assessment of infant cry: acoustic cry analysis and parental perception. Ment Retard Dev Disabil Res Rev 2005; 11 (01) 83-93.
• 8 Zhaohua W, Huang NE. Ensemble empirical mode decomposition: A noise assisted data analysis method. Centre for Ocean-Land-Atmosphere Studies, Tech Rep 193. Available from: http://perso.ens-lyon.fr/patrick.flandrin/EEMD.pdf.
• 9 Rilling G, Flandrin P, Goncalves P. On Empirical Mode Decomposition and its algorithms. IEEEEURASIP Workshop on Nonlinear Signal and Image Processing NSIP03 (internet). 2003 Available from http://perso.ens-lyon.fr/patrick.flandrin/NSIP03.pdf.
• 10 Auger F, Flandrin P. The why and how of time-frequency reassignment. Proc on IEEE International Symposium on Time-Frequency and Time-Scale Analysis; Oct 1994 pp 197-200. doi: 10. 1109/TFSA.1994.467259. ISSBN: 0-7803-2127-8.
• 11 Silva M, Mijović B, Van Den Bergh BRH, Allegaert K, Aerts JM, Van Huffel S, Berckmans D. Decoupling between fundamental frequency and energy envelope of neonate cries. Early Hum Dev 2010; 86 (01) 35-40.