Principles of electrostimulation of the face and neck muscles - a medical and biocybernetic approach

Autor

  • Mikołajewska Emilia Collegium Medicum im. Ludwika Rydygiera w Bydgoszczy Uniwersytet Mikołaja Kopernika w Toruniu
  • Mikołajewski Dariusz Uniwersytet Kazimierza Wielkiego w Bydgoszczy

DOI:

https://doi.org/10.34767/SIMIS.2023.01.03

Słowa kluczowe:

model obliczeniowy, elektrostymulacja, ruchy twarzy, gałęzie nerwu twarzowego, mięśnie mimiczne, monitorowanie, przebieg nerwu, unerwienie nerwu

Abstrakt

Nerw twarzowy ma kręty i złożony przebieg od połączenia ślinianki przyusznej i móżdżku do różnych miejsc docelowych, z indywidualnie zróżnicowanymi i złożonymi wzorcami rozgałęzień i połączeniami z kilkoma innymi nerwami czaszkowymi. Sprawia to, że modele obliczeniowe oparte na badaniach są kluczowym elementem nowoczesnej diagnostyki i terapii, a także monitorowania pacjentów i projektowania urządzeń wspierających wyżej wymienione procesy. Do tej pory nie zaproponowano dobrego modelu obliczeniowego w tym obszarze, a przedstawione koncepcje znajdują się we wstępnej fazie badań. Celem niniejszego badania jest opracowanie wytycznych dla modelu obliczeniowego elektrostymulacji mięśni twarzy i szyi w celu poprawy diagnostyki i terapii, ale także dla przyszłego rozwoju wirtualnego bliźniaka dla eZdrowia

Bibliografia

Sommerauer L, Engelmann S, Ruewe M, Anker A, Prantl L, Kehrer A. Effects of electrostimulation therapy in facial nerve palsy. Arch Plast Surg. 2021; 48(3):278-281.

Pinheiro DLDSA, Alves GÂDS, Fausto FMM, Pessoa LSF,Silva LAD, Pereira SMF, Almeida LNA. Effects of electrostimulation associated with masticatory training in individuals with down syndrome. Codas.2018;30(3):e20170074.

Kurz A, Volk GF, Arnold D, Schneider-Stickler B, Mayr W,Guntinas-Lichius O. Selective Electrical Surface Stimulation to Support Functional Recovery in the Early Phase After Unilateral Acute Facial Nerve or Vocal Fold Paralysis. Front Neurol. 2022 Apr 4;13:869900.

Arnold D, Thielker J, Klingner CM, Puls WC, Misikire W, Guntinas-Lichius O, Volk GF. Selective Surface Electrostimulation of the Denervated Zygomaticus Muscle.Diagnostics 2021; 11(2):188.

Prado DGA, Berretin-Felix G, Migliorucci RR, Bueno MDRS, Rosa RR, Polizel M, Teixeira IF, Gavião MBD. Effects of orofacial myofunctional therapy on masticatory function in individuals submitted to orthognathic surgery: a randomized trial. J Appl Oral Sci. 2018; 26:e20170164.

Santos JK, Silvério KC, Diniz Oliveira NF, Gama AC.Evaluation of Electrostimulation Effect in Women With Vocal Nodules. J Voice. 2016; 30(6):769.e1-769.e7.

Thuler ER, Rabelo FAW, Santos Junior V, Kayamori F,Bianchini EMG. Hypoglossal nerve trunk stimulation:electromyography findings during drug-induced sleep endoscopy: a case report. J Med Case Rep. 2023; 17(1):187.

Guntinas-Lichius O, Volk GF, Olsen KD, Mäkitie AA, Silver CE, Zafereo ME, Rinaldo A, Randolph GW, Simo R, Shaha AR, Vander Poorten V, Ferlito A. Facial nerve electrodiagnostics for patients with facial palsy:a clinical practice guideline.Eur Arch Otorhinolaryngol. 2020;277(7):1855-1874.

De Bonnecaze G, Vergez S, Chaput B, Vairel B, Serrano E, Chantalat E, Chaynes P. Variability in facial-muscle innervation: A comparative study based on electrostimulation and anatomical dissection. Clin Anat. 2019 Mar;32(2):169-175. doi: 10.1002/ca.23081.

Diamant A., Reilly J.P. Electrostimulation: Theory, Applications, and Computational Model. Artech House 2011.

Tarnaud T., Tanghe E., Martens L., Joseph W. Effect of myelin parameters and membrane channel dynamics in the SENN model. Brain Stimulation 2017; 10(2):P384-386.

Neufeld E, Cassará AM, Montanaro H, Kuster N, Kainz W. Functionalized anatomical models for EM-neuron Interaction modeling. Phys Med Biol. 2016; 61(12):4390-401.

Frijns J.H.M.. ten Kate J.H. A model of myelinated nerve fibr es for electric al prosthesis design. Medical & Biological Engineering & Computing 1994; 6:391-398.

Reilly J.P. Electrical models for neural excitation studies. ohns Hopkin s APL Technical Digest, 1988; 9(1):44-59.

Raslan A, Volk GF, Möller M, Stark V, Eckhardt N, Guntinas-Lichius O. High variability of facial muscle innervation by facial nerve branches: A prospective electrostimulation study. Laryngoscope. 2017; 127(6):1288-1295. doi: 10.1002/lary.26349.

Mitsukawa N, Moriyama H, Shiozawa K, Satoh K. Study on distribution of terminal branches of the facial nerve in mimetic muscles (orbicularis oculi muscle and orbicularis oris muscle). Ann Plast Surg. 2014; 72(1):71-4. doi: 10.1097/SAP.0b013e318284eca0.

Ouattara D, Vacher C, de Vasconcellos JJ, Kassanyou S, Gnanazan G, N'Guessan B. Anatomical study of the variations in innervation of the orbicularis oculi by the facial nerve. Surg Radiol Anat. 2004; 26(1):51-3. doi:10.1007/s00276-003-0168-0.

Diamond M, Wartmann CT, Tubbs RS, Shoja MM, CohenGadol AA, Loukas M. Peripheral facial nerve communications and their clinical implications. Clin Anat.2011; 24(1):10-8. doi: 10.1002/ca.21072.

Martínez Pascual P, Maranillo E, Vázquez T, Simon de Blas C, Lasso JM, Sañudo JR. Extracranial Course of the Facial Nerve Revisited. Anat Rec (Hoboken). 2019; 302(4):599-608. doi: 10.1002/ar.23825.

Kehrer A, Ruewe M, Platz Batista da Silva N, Lonic D, Heidekrueger PI, Knoedler S, Jung EM, Prantl L, Knoedler L. Using High-Resolution Ultrasound to Assess Post-Facial Paralysis Synkinesis-Machine Settings and Technical Aspects for Facial Surgeons. Diagnostics (Basel). 2022;12(7):1650. doi: 10.3390/diagnostics12071650.

Golpayegani M, Habibi Z, Rabbani Anari M, Nejat F.Peripheral facial nerve palsy following ventriculoperitoneal shunting in an infant. Childs Nerv Syst. 2020 Jan;36(1):209-212. doi: 10.1007/s00381-019-04295-w.

Raslan A, Guntinas-Lichius O, Volk GF. Altered facial muscle innervation pattern in patients with postparetic facial synkinesis. Laryngoscope. 2020 May;130(5):E320-E326. doi: 10.1002/lary.28149.

Hwang K. Surgical anatomy of the facial nerve relating to facial rejuvenation surgery. J Craniofac Surg. 2014 Jul;25(4):1476-81. doi: 10.1097/SCS.0000000000000577.

Eisele DW, Wang SJ, Orloff LA. Electrophysiologic facial nerve monitoring during parotidectomy. Head Neck. 2010 Mar;32(3):399-405. doi: 10.1002/hed.21190.

Kaufmann E, Bartkiewicz J, Fearns N, Ernst K, Vollmar C,Noachtar S. Unilateral Blinking: Insights from Stereo-EEG and Tractography. Brain Topogr. 2021 Sep;34(5):698-707.doi: 10.1007/s10548-021-00865-x.

García-García S, González-Sánchez JJ, Kakaizada S, Lawton MT, Benet A. Facial Nerve Preservation for Supraorbital Approaches: Anatomical Mapping Based on Consistent Landmarks. Oper Neurosurg (Hagerstown). 2020 Jan 1;18(1):52-59. doi: 10.1093/ons/opz084.

Beutner D, Grosheva M. Reconstruction of complex defects of the extracranial facial nerve: technique of "the trifurcation approach". Eur Arch Otorhinolaryngol. 2019 Jun;276(6):1793-1798. doi: 10.1007/s00405-019-05418-4.

Thielker J, Grosheva M, Ihrler S, Wittig A, Guntinas-Lichius O. Contemporary Management of Benign and Malignant Parotid Tumors. Front Surg. 2018 May 11;5:39. doi:10.3389/fsurg.2018.00039.

Rojek I., Macko M., Mikołajewski D., Sága M., Burczyński T. Modern methods in the field of machine modelling and simulation as a research and practical issue related to Industry 4.0. Bulletin of the Polish Academy of Sciences. Technical Sciences 2021; 69(2): e136717.

Rojek I. Hybrid neural networks as prediction models. Artifical Intelligence and Soft Computing: 10th International Conference, ICAISC 2010, Zakopane, Poland, June 13-17, 2010, Part II 10, 88-95.

Rojek I. Classifier models in intelligent CAPP systems.Man-machine interactions. Springer Berlin Heidelberg 2009, 311-319.

Duch W., Nowak W., Meller J., Osiński G., Dobosz K., Mikołajewski D., Wójcik G.M. Consciousness and attention in autism spectrum disorders. Proceedings of Cracow Grid Workshop 2010, 202-211.

Mikołajewska E., Mikołajewski D. Zastosowania automatyki i robotyki w wózkach dla niepełnosprawnych i egzoszkieletach medycznych. Pomiary Automatyka Robotyka 2011; 15(5):58-63.

Mikołajewska E., Mikołajewski D. Roboty rehabilitacyjne. Rehabil. Prakt 2010; 4:49-53.

Mikolajczyk T., Mikołajewska E., Al-Shuka H.F.N. Malinowski T., Kłodowski A., Pimenov D.Y.,Paczkowski T.,Hu F.,Giasin K.,Mikołajewski D. et al. Recent Advances in Bipedal Walking Robots: Review of Gait, Drive, Sensors and Control Systems. Sensors 2022; 22,4440. https://doi.org/10.3390/s22124440.

Macko M., Szczepański Z., Mikołajewski D., Mikołajewska E., Listopadzki S. The method of artificial organs fabrication based on reverse engineering in medicine. Proceedings of the 13th International Scientific Conference: Computer Aided Engineering 2017, 353-365.

Mikołajewska E., Mikołajewski D. Informatyka afektywna w zastosowaniach cywilnych i wojskowych. Zeszyty Naukowe/Wyższa Szkoła Oficerska Wojsk Lądowych im. gen. T. Kościuszki 2013; 2:171-184.

Mikołajewska E., Prokopowicz P., Mikołajewski D. Computational gait analysis using fuzzy logic for everyday clinical purposes preliminary findings. Bio-Algorithms and Med-Systems 2017; 13(1):37-42.

Prokopowicz P., Mikołajewski D., Mikołajewska E., Kotlarz P. Fuzzy System as an Assessment Tool for Analysis of the Health-Related Quality of Life for the People After Stroke. In: Rutkowski L., Korytkowski M., Scherer R., Tadeusiewicz R., Zadeh L., Zurada J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_64.

Ważny M., Wojcik G.M. Shifting spatial attention—numerical model of Posner experiment. Neurocomputing 2010; 135:139-144.

Wojcik G.M., Garcia-Lazaro J.A. Analysis of the neural hypercolumn in parallel pcsim simulations. Procedia Computer Science 2010; 1(1):845-854.

Kahankova R., Jezewski J., Nedoma J., Jezewski M., Fajkus M., Kawala-Janik A., Wen H., Martinek R. Influence of gestation age on the performance of adaptive systems for fetal ECG extraction. Advances in Electrical and Electronic Engineering 2014; 15(3):491-501.

Kawala-Janik A., Podpora M., Baranowski J., Bauer W., Pelc M. Innovative approach in analysis of EEG and EMG signals Comparision of the two novel methods. 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR), IEEE 2014, 804-807.

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Opublikowane

2023-09-20