Abstract
Soleus muscle flap as coverage tissue is a possible surgical solution adopted to cover the wounds due to open fractures. Despite this procedure presents many clinical advantages, relatively poor information is available about the loss of functionality of triceps surae of the treated leg. In this study, a group of patients who underwent a soleus muscle flap surgical procedure has been analyzed through the heel rise test (HRT), in order to explore the triceps surae residual functionalities. A frequency band analysis was performed in order to assess whether the residual heads of triceps surae exhibit different characteristics with respect to both the non-treated lower limb and an age-matched control group. Then, an in-depth analysis based on a machine learning approach was proposed for discriminating between groups by generalizing across new unseen subjects. Experimental results showed the reliability of the proposed analyses for discriminating between-group at a specific time epoch and the high interpretability of the proposed machine learning algorithm allowed the temporal localization of the most discriminative frequency bands. Findings of this study highlighted that significant differences can be recognized in the myoelectric spectral characteristics between the treated and contralateral leg in patients who underwent soleus flap surgery. These experimental results may support the clinical decision-making for assessing triceps surae performance and for supporting the choice of treatment in plastic and reconstructive surgery.
Similar content being viewed by others
References
Beck J B, Stile F, Lineaweaver W (2003) Reconsidering the soleus muscle flap for coverage of wounds of the distal third of the leg. Ann Plast Surg 50(6):631–635
Bernardini M, Morettini M, Romeo L, Frontoni E, Burattini L (2019) Tyg-er: an ensemble regression forest approach for identification of clinical factors related to insulin resistance condition using electronic health records. Comput Biol Med 112:103358. https://doi.org/10.1016/j.compbiomed.2019.103358. http://www.sciencedirect.com/science/article/pii/S0010482519302355
Bernardini M, Romeo L, Misericordia P, Frontoni E (2019) Discovering the type 2 diabetes in electronic health records using the sparse balanced support vector machine. IEEE Journal of Biomedical and Health Informatics 1–1. https://doi.org/10.1109/JBHI.2019.2899218
Cardozo A C, Gonċalves M, Dolan P (2011) Back extensor muscle fatigue at submaximal workloads assessed using frequency banding of the electromyographic signal. Clin Biomech 26(10):971–976
Cawley G C, Talbot N L (2010) On over-fitting in model selection and subsequent selection bias in performance evaluation. J Mach Learn Res 11:2079–2107
Chawla N V, Bowyer K W, Hall L O, Kegelmeyer W P (2002) SMOTE: synthetic minority over-sampling technique. J Artif Intell Res 16:321–357
Daigeler A, Drücke D, Tatar K, Homann H H, Goertz O, Tilkorn D, Lehnhardt M, Steinau H U (2009) The pedicled gastrocnemius muscle flap: a review of 218 cases. Plast Reconstr Surg 123 (1):250–257
De Felício CM, Mapelli A, Sidequersky FV, Tartaglia GM, Sforza C (2013) Mandibular kinematics and masticatory muscles emg in patients with short lasting tmd of mild-moderate severity. J Electromyogr Kinesiol 23(3):627–633
Farina D, Mesin L, Martina S, Merletti R (2004) A surface emg generation model with multilayer cylindrical description of the volume conductor. IEEE Trans Biomed Eng 51(3):415–426
Farina D, Cescon C, Negro F, Enoka R M (2008) Amplitude cancellation of motor-unit action potentials in the surface electromyogram can be estimated with spike-triggered averaging. J Neurophys 100(1):431–440
Ferrari D, Kuriki H U, Silva C R, Alves N, de Azevedo F M (2014) Diagnostic accuracy of the electromyography parameters associated with anterior knee pain in the diagnosis of patellofemoral pain syndrome. Arch Phys Med Rehabil 95(8):1521–1526
Ganganwar V (2012) An overview of classification algorithms for imbalanced datasets. International Journal of Emerging Technology and Advanced Engineering 2:42–47
Grävare Silbernagel K, Thomee R, Thomee P, Karlsson J (2001) Eccentric overload training for patients with chronic achilles tendon pain–a randomised controlled study with reliability testing of the evaluation methods. Scand J Med Sci Sports 11(4):197–206
Hastie T, Tibshirani R, Wainwright M (2015) Statistical learning with sparsity: the lasso and generalizations. CRC Press, Boca Raton
Hébert-Losier K, Newsham-West RJ, Schneiders AG, Sullivan SJ (2009) Raising the standards of the calf-raise test: a systematic review. J Sci Med Sport 12(6):594–602
Hébert-Losier K, Schneiders AG, Newsham-West RJ, Sullivan SJ (2009) Scientific bases and clinical utilisation of the calf-raise test. Phys Ther Sport 10(4):142–149
Hermens H J, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, Disselhorst-Klug C, Hägg G (1999) European recommendations for surface electromyography. Roessingh Research and Development 8(2):13–54
Hurley N, Rickard S (2009) Comparing measures of sparsity. IEEE Trans Inf Theory 55 (10):4723–4741
Kaikkonen A, Kannus P, Järvinen M (1994) A performance test protocol and scoring scale for the evaluation of ankle injuries. Am J Sports Med 22(4):462–469
Knopp W, Buchholz J, Muhr G, Steinau H (1993) Negative effects of local tibial muscle flap repair on foot function. Der Unfallchirurg 96(5):229–234
Komi P V, Tesch P (1979) Emg frequency spectrum, muscle structure, and fatigue during dynamic contractions in man. Eur J Appl Physiol Occup Physiol 42(1):41–50
Kwon M, Baweja H S, Christou E A (2012) Ankle variability is amplified in older adults due to lower emg power from 30–60 hz. Hum Mov Sci 31(6):1366–1378
Larsson B, Kadi F, Lindvall B, Gerdle B (2006) Surface electromyography and peak torque of repetitive maximum isokinetic plantar flexions in relation to aspects of muscle morphology. J Electromyogr Kinesiol 16(3):281–290
Lasserre G, Cornu J, Vidal C, Laveaux C, Lepage D, Obert L, Pauchot J, Tropet Y (2011) Baropodometric analysis of the functional donor-site morbidity after gastrocnemius or soleus muscle-flap procedure. In: Annales de chirurgie plastique et esthetique, vol 56, p 180
Lunsford B R, Perry J (1995) The standing heel-rise test for ankle plantar flexion: criterion for normal. Phys Ther 75(8):694–698
Madeley L T, Munteanu S E, Bonanno D R (2007) Endurance of the ankle joint plantar flexor muscles in athletes with medial tibial stress syndrome: a case-control study. J Sci Med Sport 10(6):356–362
Merletti R, Farina D (2016) Surface electromyography: physiology, engineering, and applications. Wiley, New York
Murray M, Guten G, Sepic S, Gardner G, Baldwin J (1978) Function of the triceps surae during gait. compensatory mechanisms for unilateral loss. J Bone Joint Surg Am 60(4):473–476
Nilsson G, Nyberg P, Ekdahl C, Eneroth M (2003) Performance after surgical treatment of patients with ankle fractures—14-month follow-up. Physiother Res Int 8(2):69–82
Norte G E, Knaus K R, Kuenze C, Handsfield G G, Meyer C H, Blemker S S, Hart J M (2018) Mri-based assessment of lower-extremity muscle volumes in patients before and after acl reconstruction. J Sport Rehabil 27(3):201–212
Olsson N, Karlsson J, Eriksson B, Brorsson A, Lundberg M, Silbernagel K (2014) A bility to perform a single heel-rise is significantly related to patient-reported outcome after a chilles tendon rupture. Scand J Med Sci Sports 24(1):152–158
Österberg U, Svantesson U, Takahashi H, Grimby G (1998) Torque, work and emg development in a heel-rise test. Clin Biomech 13(4-5):344–350
Pereira F, Mitchell T, Botvinick M (2009) Machine learning classifiers and fmri: a tutorial overview. NeuroImage 45(1, Supplement 1):S199–S209. https://doi.org/10.1016/j.neuroimage.2008.11.007. http://www.sciencedirect.com/science/article/pii/S1053811908012263. Mathematics in Brain Imaging
Politti F, Casellato C, Kalytczak M M, Garcia M B S, Biasotto-Gonzalez D A (2016) Characteristics of emg frequency bands in temporomandibullar disorders patients. J Electromyogr Kinesiol 31:119–125
Kramers-de Quervain I A, Lüuffer J M, Küch K, Trentz O, Stüssi E (2001) Functional donor-site morbidity during level and uphill gait after a gastrocnemius or soleus muscle-flap procedure. JBJS 83 (2):239
Riccio M, Zingaretti N, Verdini F, Marchesini A, De Francesco F, Parodi P C (2019) Functional donor-site morbidity after soleus muscle-flap procedure in the treatment of lower limb severe injuries. Handchir Mikrochir Plast Chir 51(06):453–463
Roman-Liu D, Konarska M (2009) Characteristics of power spectrum density function of emg during muscle contraction below 30 % mvc. J Electromyogr Kinesiol 19(5):864–874
Solomonow M, Baten C, Smit J, Baratta R, Hermens H, D’Ambrosia R, Shoji H (1990) Electromyogram power spectra frequencies associated with motor unit recruitment strategies. J Appl Physiol 68(3):1177–1185
Suda A J, Cieslik A, Grützner P A, Münzberg M, Heppert V (2014) Flaps for closure of soft tissue defects in infected revision knee arthroplasty. Int Orthop 38(7):1387–1392
Svantesson U, Osterberg U, Thomeé R, Grimby G (1998) Muscle fatigue in a standing heel-rise test. Scand J Rehabil Med 30(2):67–72
Tengman T, Coleman S, Grävare Silbernagel K, Karlsson J, Riad J (2015) Muscle fatigue after achilles tendon rupture: a limited heel-rise test with electromyography reveals decreased endurance. Eur J Physiother 17(4):200–207
Tibshirani R (1996) Regression shrinkage and selection via the lasso. J R Stat Soc Ser B Methodol 267–288
Unluer Z, Al-Ajam Y, Al-Benna S (2018) Functional outcome after reconstruction of traumatic soft tissue defects in the lower half of the leg with distally based medial hemisoleus muscle flaps: a case series and literature review. Ann Plast Surg 81(4):468–471
Wakeling J M, Rozitis A I (2004) Spectral properties of myoelectric signals from different motor units in the leg extensor muscles. J Exp Biol 207(14):2519–2528
Walton Z, Armstrong M, Traven S, Leddy L (2017) Pedicled rotational medial and lateral gastrocnemius flaps: surgical technique. JAAOS-J Am Acad Orthop Surg 25(11):744–751
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ferracuti, F., Fioretti, S., Frontoni, E. et al. Functional evaluation of triceps surae during heel rise test: from EMG frequency analysis to machine learning approach. Med Biol Eng Comput 59, 41–56 (2021). https://doi.org/10.1007/s11517-020-02286-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-020-02286-7