Application of Empirical Mode Decomposition to Mother and Infant Physical Activity

Etsuko Shimizu; Toru Nakamura; Jinhyuk Kim; Kazuhiro Yoshiuchi; Yoshiharu Yamamoto

doi:10.3414/ME18-02-0001

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2018; 57(03): 152-157
DOI: 10.3414/ME18-02-0001

Focus Theme – Original Article

Schattauer GmbH

Application of Empirical Mode Decomposition to Mother and Infant Physical Activity

Synchronization of Circadian Rhythms is Associated with Maternal Mental Health

Authors

Etsuko Shimizu

¹Graduate School of Education, The University of Tokyo, Tokyo, Japan
Toru Nakamura

²Graduate School of Engineering Science, Osaka University, Osaka, Japan
Jinhyuk Kim

³Department of Biobehavioral Health, The Pennsylvania State University, PA, USA
Kazuhiro Yoshiuchi

⁴Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
Yoshiharu Yamamoto

¹Graduate School of Education, The University of Tokyo, Tokyo, Japan

Abstract

Summary

Background: The mutual dependencies between mother and infant circadian rhythms are important for examining disturbances of maternal circadian rhythms, which are considered substantial risk factors for the development of maternal depression during childrearing periods.

Objectives: We characterized the mutual dependencies of maternal–infant circadian rhythms by an index of synchronization properties and then tested the hypothesis that such an index, specifically the instantaneous phase differences between their rhythms, is associated with maternal mental health.

Methods: We performed longitudinal recordings of maternal symptoms of fatigue, stress, and mood states by ecological momentary assessment, together with simultaneous measurements of mother and infant physical activity data in daily life, on 20 mother–infant pairs for a period of >1 week. The circadian components in their physical activity data were extracted by ensembled bivariate empirical mode decomposition, and the corresponding instantaneous phases were then obtained based on the Hilbert transformation. The associations between diurnal maternal symptoms and absolute phase differences between mother and infant circadian rhythms were tested by multilevel models.

Results: Diurnal fatigue and depressive mood scores showed positive and significant correlations (p < 0.05) with the increase in instantaneous mother–infant phase differences, indicating the significant role of synchronization of mother–infant circadian rhythms for maintaining maternal mental health.

Conclusions: These findings suggest that modifications of maternal and/or infant circadian rhythms may lead to the improvement of maternal mental health during child-rearing periods.

Keywords

Circadian rhythm - ecological momentary assessment - maternal mental health - physical activity - empirical mode decomposition

Full Text

References

References
1 Bhati S, Richards K. A systematic review of the relationship between postpartum sleep disturbance and postpartum depression. J Obstet Gynecol Neonatal Nurs 2015; 44 (03) 350-357.
2 Sadeh A, Tikotzky L, Scher A. Parenting and infant sleep. Sleep Med Rev 2010; 14 (02) 89-96.
3 Sharkey KM, Pearlstein TB, Carskadon MA. Circadian phase shifts and mood across the perinatal period in women with a history of major depressive disorder: A preliminary communication. J Affect Disorders 2013; 150 (03) 1103-1108.
4 Dorheim SK, Bondevik GT, Eberhard-Gran M, Bjorvatn B. Sleep and depression in postpartum women: A population-based study. Sleep 2009; 32 (07) 847-855.
5 Goyal D, Gay C, Lee K. Patterns of sleep disruption and depressive symptoms in new mothers. J Perinat Neonatal Nurs 2007; 21 (02) 123-129.
6 Tsai SY, Thomas KA, Lentz MJ, Barnard KE. Light is beneficial for infant circadian entrainment: an actigraphic study. J Adv Nurs 2012; 68 (08) 1738-1747.
7 Gnidovec B, Neubauer D, Zidar J. Actigraphic assessment of sleep-wake rhythm during the first 6 months of life. Clin Neurophysiol 2002; 113 (11) 1815-1821.
8 Huang NE, Shen Z, Long SR, Wu MLC, Shih HH, Zheng QN. et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. P Roy Soc a-Math Phy 1998; 454 (1971): 903-995.
9 Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol 2008; 04: 1-32.
10 Stone AA, Shiffman S. Ecological momentary assessment (EMA) in behavioral medicine. Ann Behav Med 1994; 16: 199-202.
11 Fukui I. The depression and anxiety mood scale (DAMS): scale development and validation. Jpn J Behav Ther 1997; 23: 83-93.
12 Kim J, Nakamura T, Kikuchi H, Sasaki T, Yamamoto Y. Co-variation of depressive mood and locomotor dynamics evaluated by ecological momentary assessment in healthy humans. Plos One 2013; 08 (09) e74979.
13 Kim J, Nakamura T, Kikuchi H, Yoshiuchi K, Sasaki T, Yamamoto Y. Covariation of depressive mood and spontaneous physical activity in major depressive disorder: Toward continuous monitoring of depressive mood. IEEE J Biomed Health 2015; 19 (04) 1347-1355.
14 Ahrabian A, Rehman NU, Mandic D. Bivariate empirical mode decomposition for unbalanced real-world signals. IEEE Signal Proc Let 2013; 20 (03) 245-248.
15 Rilling G, Flandrin P, Goncalves P, Lilly JM. Bivariate empirical mode decomposition. IEEE Signal Proc Let 2007; 14 (12) 936-939.
16 Park C, Looney D, Kidmose P, Ungstrup M, Mandic DP. Time-Frequency Analysis of EEG Asymmetry Using Bivariate Empirical Mode Decomposition. IEEE T Neur Sys Reh 2011; 19 (04) 366-373.
17 Wu Z, Huang NE. Ensemble empirical mode decomposition: A noise-assisted data analysis method. Advances in Adaptive Data Analysis 2009; 01 (01) 1-41.
18 Torres ME, Colominas MA, Schlotthauer G, Flandrin P. editors> A complete ensemble empirical mode decomposition with adaptive noise. In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2011
19 Schwartz JE, Stone AA. Strategies for analyzing ecological momentary assessment data. Health Psychol 1998; 17 (01) 6-16.
20 Bryk AS, Raudenbush SW. Hierarchical linear models: applications and data analysis methods. Newbury Park: Sage Publications; 1992: 265.
21 Singer JD, Willett JB. Applied longitudinal data analysis: modeling change and event occurrence. New York: Oxford University Press; 2003: 644.
22 Chan FHY, Wu BM, Lam FK, Poon PWF, Poon AMS. Multiscale characterization of chronobiological signals based on the discrete wavelet transform. IEEE T Bio-Med Eng 2000; 47 (01) 88-95.
23 Levandovski R, Dantas G, Fernandes LC, Caumo W, Torres I, Roenneberg T. et al. Depression scores associate with chronotype and social jetlag in a rural population. Chronobiol Int 2011; 28 (09) 771-778.
24 Wittmann M, Dinich J, Merrow M, Roenneberg T. Social jetlag: Misalignment of biological and social time. Chronobiol Int 2006; 23 (1–2) 497-509.
25 Basnet S, Merikanto I, Lahti T, Mannisto S, Laatikainen T, Vartiainen E. et al. Associations of common noncommunicable medical conditions and chronic diseases with chronotype in a populationbased health examination study. Chronobiol Int 2017; 34 (04) 462-470.
26 Driesen K, Jansen NWH, Kant I, Mohren DCL, van Amelsvoort LGPM. Depressed Mood in the Working Population: Associations with Work Schedules and Working Hours. Chronobiol Int 2010; 27 (05) 1062-1079.
27 Hiscock H, Cook F, Bayer J, Le HND, Mensah F, Cann W. et al. Preventing Early Infant Sleep and Crying Problems and Postnatal Depression: A Randomized Trial. Pediatrics 2014; 133 (02) 346-354.
28 Mindell JA, Kuhn B, Lewin DS, Meltzer LJ, Sadeh A. Behavioral treatment of bedtime problems and night wakings in infants and young children – An American Academy of Sleep Medicine review. Sleep 2006; 29 (10) 1263-1276.
29 Stremler R, Hodnett E, Kenton L, Lee K, Weiss S, Weston J. et al. Effect of behavioural-educational intervention on sleep for primiparous women and their infants in early postpartum: multisite randomised controlled trial. BMJ 2013; 346: f1164.