https://doi.org/10.4081/ejtm.2024.12701
Longitudinal analysis of lower limb muscle activity and ankle tendon biosignals using structural equation modeling
Submitted: 1 June 2024
Accepted: 1 August 2024
Published: 23 September 2024
Accepted: 1 August 2024
Abstract Views: 922
PDF: 305
HTML: 2
HTML: 2
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
We collected biosignals from 63 participants and extracted the features corresponding to each level of exerted muscle force. Data were classified into typical and atypical patterns. Data analysis was performed using the Linear Latent Curve Model (LCM) and the Conditional Linear LCM. The typical patterns demonstrated a high degree of fit. Factors, such as ankle circumference and muscle mass, influenced the model intercept. A larger ankle circumference indicated attenuation of signal transmission from the tendon to the skin surface, leading to lower biosignal values. These results indicate that biosignals from the tendons near the ankle can be captured using piezoelectric film sensors. There are studies that define biosignals originating from tendons as mechanotendography. It has been demonstrated that the relationship between biosignals originating from tendons and the exerted muscle force can be explained linearly. Insights from this study may facilitate individualized approaches in the fields of motion control and rehabilitation. Physiological studies to elucidate the mechanisms underlying biosignal generation are necessary.
Powell KE, Paluch AE, Blair SN. Physical activity for health: What kind? how much? how intense? on top of what? Ann Rev Public Health 2011;32:349-365.
DOI: https://doi.org/10.1146/annurev-publhealth-031210-101151
Howard RM, Conway R, Harrison AJ. A survey of sensor devices: use in sports biomechanics. Sports Biomechanics 2016;15:450-461.
DOI: https://doi.org/10.1080/14763141.2016.1174289
Walter JP, Kinney AL, Banks SA, et al. Muscle synergies may improve optimization prediction of knee contact forces during walking. J Biomech Engin 2014;136:021031.
DOI: https://doi.org/10.1115/1.4026428
Hansen C, Teulier C, Micallef JP, et al. Lower limb muscle activity during first and second tennis serves: a comparison of three surface electromyography normalisation methods. Sports Biomech 2023;1-12.
DOI: https://doi.org/10.1080/14763141.2023.2278154
Schmitz A, Silder A, Heiderscheit B, et al. Differences in lower-extremity muscular activation during walking between healthy older and young adults. J Electromyography Kinesiol 2009;19:1085-91.
DOI: https://doi.org/10.1016/j.jelekin.2008.10.008
Arendt-Nielsen L, Graven-Nielsen T, Svarrer H, Svensson P. Influence of low back pain on muscle activity and coordination during gait: A clinical and experimental study. Pain 1996;64:231-240.
DOI: https://doi.org/10.1016/0304-3959(95)00115-8
Farthing JP, Chilibeck PD. The effects of eccentric and concentric training at different velocities on muscle hypertrophy. Eur J Appl Physiol 2003;89:578-86.
DOI: https://doi.org/10.1007/s00421-003-0842-2
Ekstrom RA, Donatelli RA, Carp KC. Electromyographic analysis of core trunk, hip, and thigh muscles during rehabilitation exercises. J Orthopaedic Sports Physical Ther 2007;37:754-62.
DOI: https://doi.org/10.2519/jospt.2007.2471
Isezaki T, Kadone H, Niijima A, et al. Sock-type wearable sensor for estimating lower leg muscle activity using distal EMG signals. Sensors 2019;19:1954.
DOI: https://doi.org/10.3390/s19081954
Stokes MJ, Dalton PA. Acoustic myography for investigating human skeletal muscle fatigue. J Appl Physiol 1991;71:1422-6.
DOI: https://doi.org/10.1152/jappl.1991.71.4.1422
Koster B, Lauk M, Timmer J, et al. Central mechanisms in human enhanced physiological tremor. Neuroscience Letters 1998;241:135-8.
DOI: https://doi.org/10.1016/S0304-3940(98)00015-9
Ando M, Kawamura H, Kitada H, et al. Pressure-sensitive touch panel based on piezoelectric poly (l-lactic acid) film. Japanese J Appl Physics 2013;52:09KD17.
DOI: https://doi.org/10.7567/JJAP.52.09KD17
Jomyo S, Furui A, Matsumoto T, et al. A wearable finger-tapping motion recognition system using biodegradable piezoelectric film sensors. In: 2021 43rd Annual International Conference of IEEE Engineering in Medicine Biology Society (EMBC). IEEE, 2021.
DOI: https://doi.org/10.1109/EMBC46164.2021.9630643
Menegaldo LL, de Oliveira LF. Effect of muscle model parameter scaling for isometric plantar flexion torque prediction. J Biomech 2009;42:2597-2601.
DOI: https://doi.org/10.1016/j.jbiomech.2009.06.043
Immovilli F, Bianchini C, Cocconcelli M, et al. Bearing fault model for induction motor with externally induced vibration. IEEE Transactions on Industrial Electronics 2012;60:3408-3418.
DOI: https://doi.org/10.1109/TIE.2012.2213566
Tsypkin M. Induction motor condition monitoring: Vibration analysis technique-a twice line frequency component as a diagnostic tool. In: 2013 International Electric Machines Drives Conference, 2013. p. 117-124.
DOI: https://doi.org/10.1109/IEMDC.2013.6556242
Ester M, Kriegel HP, Sander J, Xu X. A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD, 1996. p. 226-231.
Hox JJ, Bechger TM. An introduction to structural equation modeling. In: Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, 2021. p. 1-29.
DOI: https://doi.org/10.1007/978-3-030-80519-7_1
Hoelter JW. The analysis of covariance structures: Goodness-of-fit indices. Sociological Methods Research 1983;11:325-344.
DOI: https://doi.org/10.1177/0049124183011003003
Cole DA. Utility of confirmatory factor analysis in test validation research. J Consulting Clin Psychol 1987;55:584.
DOI: https://doi.org/10.1037//0022-006X.55.4.584
Steiger JH. Understanding the limitations of global fit assessment in structural equation modeling. Personal Individual Diff 2007;42:893-8.
DOI: https://doi.org/10.1016/j.paid.2006.09.017
Iacobucci D. Structural equations modeling: Fit indices, sample size, and advanced topics. J Consumer Psychol 2010;20:90-8.
DOI: https://doi.org/10.1016/j.jcps.2009.09.003
McArdle JJ, Grimm KJ. Five steps in latent curve and latent change score modeling with longitudinal data. In: Longitudinal Research with Latent Variables, 2010. p. 245-273.
DOI: https://doi.org/10.1007/978-3-642-11760-2_8
Bollen KA, Curran PJ. Latent curve models: a structural equation perspective. Wiley and Sons, 2006.
DOI: https://doi.org/10.1002/0471746096
Lance CE, Vandenberg RJ, Self RM. Latent growth models of individual change: The case of newcomer adjustment. Organizat Behav Human Decision Processes 2000;83:107-40.
DOI: https://doi.org/10.1006/obhd.2000.2904
Kubota K, Yokoyama M, Hanawa MT, et al. Muscle co-activation in the elderly contributes to control of hip and knee joint torque and endpoint force. Sci Rep 2023;13:7139.
DOI: https://doi.org/10.1038/s41598-023-34208-6
Billot M, Simoneau EM, Ballay Y, et al. How the ankle joint angle alters the antagonist and agonist torques during maximal efforts in dorsi-and plantar flexion. Scandinavian J Med Sci Sports 2011;21:e273-81.
DOI: https://doi.org/10.1111/j.1600-0838.2010.01278.x
Schaefer LV, Bittmann FN. Mechanotendography: description and evaluation of a novel method for investigating the physiological mechanical oscillations of tendons using a piezo-based measurement system. Eur J f Translat Myol 2021;31:1.
DOI: https://doi.org/10.4081/ejtm.2021.9553
Schaefer LV, Bittmann FN. Two forms of isometric muscle function: Interpersonal motor task supports a distinction between a holding and a pushing isometric muscle action. BioRxiv 2020;2020:08.
DOI: https://doi.org/10.1101/2020.08.17.253633
How to Cite
Matsumoto, T., & Kano, Y. (2024). Longitudinal analysis of lower limb muscle activity and ankle tendon biosignals using structural equation modeling. European Journal of Translational Myology, 34(4). https://doi.org/10.4081/ejtm.2024.12701
Copyright (c) 2024 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
