Skip to main content
Top
Published in: BMC Geriatrics 1/2020

Open Access 01-12-2020 | Fatigue | Research article

Hand grip strength variability during serial testing as an entropic biomarker of aging: a Poincaré plot analysis

Authors: Elena Ioana Iconaru, Constantin Ciucurel

Published in: BMC Geriatrics | Issue 1/2020

Login to get access

Abstract

Background

The Poincaré plot method can be used for both qualitative and quantitative assessment of self-similarity in usually periodic functions, hence the idea of applying it to the study of homeostasis of living organisms. From the analysis of numerous scientific data, it can be concluded that hand functionality can be correlated with the state of the human body as a biological system exposed to various forms of ontogenetic stress.

Methods

We used the Poincaré plot method to analyze the variability of hand grip strength (HGS), as an entropic biomarker of aging, during 60 repetitive tests of the dominant and nondominant hand, in young and older healthy subjects. An observational cross-sectional study was performed on 80 young adults (18–22 years old, mean age 20.01 years) and 80 older people (65–69 years old, mean age 67.13 years), with a sex ratio of 1:1 for both groups. For statistical analysis, we applied univariate descriptive statistics and inferential statistics (Shapiro–Wilk test, Mann–Whitney U-test for independent large samples, with the determination of the effect size coefficient r, and simple linear regression. We calculated the effect of fatigue and the Poincaré indices SD1, SD2, SD1/SD2 and the area of the fitting ellipse (AFE) for the test values of each subject.

Results

The analysis of the differences between groups revealed statistically significant results for most HGS-derived indices (p ≤ 0.05), and the magnitude of the differences indicated, in most situations, a large effect size (r > 0.5). Our results demonstrate that the proposed repetitive HGS testing indicates relevant differences between young and older healthy subjects. Through the mathematical modeling of data and the application of the concept of entropy, we provide arguments supporting this new design of HGS testing.

Conclusions

Our results indicate that the variability of HGS during serial testing, which reflects complex repetitive biomechanical functions, represents an efficient indicator for differentiation between young and older hand function patterns from an entropic perspective. In practical terms, the variability of HGS, evaluated by the new serial testing design, can be considered an attractive and relatively simple biomarker to use for gerontological studies.
Literature
2.
go back to reference Pincus SM, Goldberger AL. Physiological time-series analysis: what does regularity quantify? Am J Phys. 1994;266(4 Pt 2):H1643–56. Pincus SM, Goldberger AL. Physiological time-series analysis: what does regularity quantify? Am J Phys. 1994;266(4 Pt 2):H1643–56.
3.
go back to reference Khandoker AH, Karmakar C, Brennan M, Voss A, Palaniswami M. Quantitative Poincaré Plot. In: Poincaré plot methods for heart rate variability analysis. Boston: Springer; 2013. p. 13–23.CrossRef Khandoker AH, Karmakar C, Brennan M, Voss A, Palaniswami M. Quantitative Poincaré Plot. In: Poincaré plot methods for heart rate variability analysis. Boston: Springer; 2013. p. 13–23.CrossRef
7.
go back to reference Crenier L. Poincaré plot quantification for assessing glucose variability from continuous glucose monitoring systems and a new risk marker for hypoglycemia: application to type 1 diabetes patients switching to continuous subcutaneous insulin infusion. Diabetes Technol Ther. 2014;16(4):247–54. https://doi.org/10.1089/dia.2013.0241.CrossRefPubMed Crenier L. Poincaré plot quantification for assessing glucose variability from continuous glucose monitoring systems and a new risk marker for hypoglycemia: application to type 1 diabetes patients switching to continuous subcutaneous insulin infusion. Diabetes Technol Ther. 2014;16(4):247–54. https://​doi.​org/​10.​1089/​dia.​2013.​0241.CrossRefPubMed
8.
go back to reference Guzik P, Piskorski J, Krauze T, Schneider R, Wesseling KH, Wykretowicz A, Wysock H. Correlations between Poincaré plot and conventional heart rate variability parameters assessed during paced breathing. J Physiol Sci. 2007;57:63–71.CrossRefPubMed Guzik P, Piskorski J, Krauze T, Schneider R, Wesseling KH, Wykretowicz A, Wysock H. Correlations between Poincaré plot and conventional heart rate variability parameters assessed during paced breathing. J Physiol Sci. 2007;57:63–71.CrossRefPubMed
10.
go back to reference Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278(6):H2039–49.CrossRefPubMed Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278(6):H2039–49.CrossRefPubMed
11.
go back to reference Huo C, Huang X, Zhuang J, Hou F, Ni H, Ning X. Quadrantal multi-scale distribution entropy analysis of heartbeat interval series based on a modified Poincaré plot. Physica A. 2013;392(17):3601–9.CrossRef Huo C, Huang X, Zhuang J, Hou F, Ni H, Ning X. Quadrantal multi-scale distribution entropy analysis of heartbeat interval series based on a modified Poincaré plot. Physica A. 2013;392(17):3601–9.CrossRef
12.
go back to reference Javorka M. Analysis of variability of physiologic parameters using the Poincare plot. Cesk Fysiol. 2002;51(2):75–81.PubMed Javorka M. Analysis of variability of physiologic parameters using the Poincare plot. Cesk Fysiol. 2002;51(2):75–81.PubMed
13.
go back to reference Voss C, Fischer R, Schroeder A. Coupling of heart rate and systolic blood pressure in hypertensive pregnancy. Methods Inf Med. 2014;53(4):286–0.CrossRefPubMed Voss C, Fischer R, Schroeder A. Coupling of heart rate and systolic blood pressure in hypertensive pregnancy. Methods Inf Med. 2014;53(4):286–0.CrossRefPubMed
15.
go back to reference Bien MY, Shui Lin Y, Shih CH, Yang YL, Lin HW, Bai KJ, Wang JH, Ru KY. Comparisons of predictive performance of breathing pattern variability measured during T-piece, automatic tube compensation, and pressure support ventilation for weaning intensive care unit patients from mechanical ventilation. Crit Care Med. 2011;39(10):2253–62. https://doi.org/10.1097/CCM.0b013e31822279ed.CrossRefPubMed Bien MY, Shui Lin Y, Shih CH, Yang YL, Lin HW, Bai KJ, Wang JH, Ru KY. Comparisons of predictive performance of breathing pattern variability measured during T-piece, automatic tube compensation, and pressure support ventilation for weaning intensive care unit patients from mechanical ventilation. Crit Care Med. 2011;39(10):2253–62. https://​doi.​org/​10.​1097/​CCM.​0b013e31822279ed​.CrossRefPubMed
17.
go back to reference Henriques T, Munshi MN, Segal AR, Costa MD, Goldberger AL. “Glucose-at-a-glance”: new method to visualize the dynamics of continuous glucose monitoring data. J Diabetes Sci Technol. 2014;8(2):299–306.CrossRefPubMedPubMedCentral Henriques T, Munshi MN, Segal AR, Costa MD, Goldberger AL. “Glucose-at-a-glance”: new method to visualize the dynamics of continuous glucose monitoring data. J Diabetes Sci Technol. 2014;8(2):299–306.CrossRefPubMedPubMedCentral
20.
go back to reference Luginbühl M, Rüfenacht M, Korhonen I, Gils M, Jakob S, Petersen-Felix S. Stimulation induced variability of pulse plethysmography does not discriminate responsiveness to intubation. Br J Anaesth. 2006;96(3):323–9.CrossRefPubMed Luginbühl M, Rüfenacht M, Korhonen I, Gils M, Jakob S, Petersen-Felix S. Stimulation induced variability of pulse plethysmography does not discriminate responsiveness to intubation. Br J Anaesth. 2006;96(3):323–9.CrossRefPubMed
24.
go back to reference Ball K, Best R, Dowlan S. Non-linear analysis of centre of pressure patterns in the golf swing – Poincare plots, XXV ISBS Symposium 2007. Ouro Preto: Open Journal Systems; 2007. p. 180–3. Ball K, Best R, Dowlan S. Non-linear analysis of centre of pressure patterns in the golf swing – Poincare plots, XXV ISBS Symposium 2007. Ouro Preto: Open Journal Systems; 2007. p. 180–3.
32.
go back to reference Alkurdi ZD, Dweiri M. A biomechanical assessment of isometric handgrip force and fatigue at different anatomical positions. J Appl Biomech. 2010;26(2):123–33.CrossRefPubMed Alkurdi ZD, Dweiri M. A biomechanical assessment of isometric handgrip force and fatigue at different anatomical positions. J Appl Biomech. 2010;26(2):123–33.CrossRefPubMed
33.
go back to reference Tredgett MW, Davis TR. Rapid repeat testing of grip strength for detection of faked hand weakness. J Hand Surg (Br). 2000;25(4):372–5.CrossRef Tredgett MW, Davis TR. Rapid repeat testing of grip strength for detection of faked hand weakness. J Hand Surg (Br). 2000;25(4):372–5.CrossRef
37.
go back to reference Gąsior JS, Pawłowski M, Williams CA, Dąbrowski MJ, Rameckers EA. Assessment of Maximal Isometric Hand Grip Strength in School-aged Children. Open Med (Wars). 2018;13:22–8.CrossRef Gąsior JS, Pawłowski M, Williams CA, Dąbrowski MJ, Rameckers EA. Assessment of Maximal Isometric Hand Grip Strength in School-aged Children. Open Med (Wars). 2018;13:22–8.CrossRef
38.
go back to reference Wallström A, Nordenskiöld U. Assessing hand grip endurance with repetitive maximal isometric contractions. J Hand Ther. 2001;14(4):279–85.CrossRefPubMed Wallström A, Nordenskiöld U. Assessing hand grip endurance with repetitive maximal isometric contractions. J Hand Ther. 2001;14(4):279–85.CrossRefPubMed
41.
go back to reference Coolican H. Research methods and statistics in psychology. London: Hodder Education; 2009. p. 395. Coolican H. Research methods and statistics in psychology. London: Hodder Education; 2009. p. 395.
47.
go back to reference Reddon JR, Stefanyk WO, Gill DM, Renney C. Hand dynamometer: effects of trials and sessions. Percept Mot Skills. 1985;61:1195–8.CrossRefPubMed Reddon JR, Stefanyk WO, Gill DM, Renney C. Hand dynamometer: effects of trials and sessions. Percept Mot Skills. 1985;61:1195–8.CrossRefPubMed
50.
go back to reference Patterson RP, Baxter T. A multiple muscle strength testing protocol. Arch Phys Med Rehabil. 1988;69:366–8.PubMed Patterson RP, Baxter T. A multiple muscle strength testing protocol. Arch Phys Med Rehabil. 1988;69:366–8.PubMed
51.
52.
go back to reference Mathiowetz V. Effect of three trials on grip and pinch strength measurement. J Hand Ther. 1990;3:195–8.CrossRef Mathiowetz V. Effect of three trials on grip and pinch strength measurement. J Hand Ther. 1990;3:195–8.CrossRef
53.
go back to reference Sung PS, Zurcher U, Kaufman M. Gender differences in spectral and entropic measures of erector spinae muscle fatigue. J Rehabil Res Dev. 2008;45(9):1431–9.CrossRefPubMed Sung PS, Zurcher U, Kaufman M. Gender differences in spectral and entropic measures of erector spinae muscle fatigue. J Rehabil Res Dev. 2008;45(9):1431–9.CrossRefPubMed
58.
go back to reference Watanabe T, Owashi K, Kanauchi Y, Mura N, Takahara M, Ogino T. The short-term reliability of grip strength measurement and the effects of posture and grip span. J Hand Surg Am. 2005;30(3):603–9.CrossRefPubMed Watanabe T, Owashi K, Kanauchi Y, Mura N, Takahara M, Ogino T. The short-term reliability of grip strength measurement and the effects of posture and grip span. J Hand Surg Am. 2005;30(3):603–9.CrossRefPubMed
Metadata
Title
Hand grip strength variability during serial testing as an entropic biomarker of aging: a Poincaré plot analysis
Authors
Elena Ioana Iconaru
Constantin Ciucurel
Publication date
01-12-2020
Publisher
BioMed Central
Published in
BMC Geriatrics / Issue 1/2020
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/s12877-020-1419-1

Other articles of this Issue 1/2020

BMC Geriatrics 1/2020 Go to the issue