Advertisement

Validation of a Digital Interface for Assessment of Motor Function Based on MFM

  • Adriana Gomes L. de Souza
  • Dominique Vincent-Genod
  • Carole Vuillerot
  • Michel Dubois
  • Guillaume Thomann
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 876)

Abstract

Patients with neuromuscular diseases undergo frequent motor assessments. The MFM scale (Motor Function Measure) is a validated scale for all neuromuscular diseases. Tasks 18, 19, and 22 have the potential to have a digitized version on a Tablet. This article proposes to digitalize a first version of items 18, 19 and 22 based on MFM. The results show that the scores were similar for the Tablet version and the paper version.

Keywords

Digital tablet Neuromuscular disease MFM scale 

Notes

Acknowledgments

Eloïse GRONLIER, Eloïse LIOGIER, Ambre MIRC end Alison RODRIGUES LOUZANO.

References

  1. 1.
    Urtizberea, J.-A., Boucharef, W., Frischmann, M.: Maladies neuromusculaires: évolution des concepts médicos cientifiques et des pratiques de soins. Neuropsychiatrie de l’enfance et de l’adolescence 56(2), 51–57 (2008)CrossRefGoogle Scholar
  2. 2.
    Mary, P., Servais, L., Vialle, R.: Neuromuscular diseases: diagnosis and management. Orthop. Traumatol. Surg. Res. (2018)Google Scholar
  3. 3.
    Vuillerot, C., et al.: Monitoring changes and predicting loss of ambulation in Duchenne muscular dystrophy with the Motor Function Measure. Dev. Med. Child Neurol. 52(1), 60–65 (2010)CrossRefGoogle Scholar
  4. 4.
    Benaïm, C., et al.: Analyse de validité de la «Mesure de la fonction motrice» (MFM) en pratique de consultation adulte d’un centre de référence pour maladies neuromusculaires. Revue neurologique 166(1), 49–53 (2010)CrossRefGoogle Scholar
  5. 5.
    Montes, J., et al.: Clinical outcome measures in spinal muscular atrophy. J. Child Neurol. 24(8), 968–978 (2009)CrossRefGoogle Scholar
  6. 6.
    Rodriguez-Blazquez, C., Forjaz, M.J., Martinez-Martin, P.: Rating scales in movement disorders. In: Movement Disorders Curricula, pp. 65–75. Springer, Vienna (2017)CrossRefGoogle Scholar
  7. 7.
    Dingenen, B., et al.: The assessment of movement health in clinical practice: a multidimensional perspective. Phys. Ther. Sport. (2018)Google Scholar
  8. 8.
    Fang, B., et al.: 3D human gesture capturing and recognition by the IMMU-based data glove. Neurocomputing 277, 198–207 (2018)CrossRefGoogle Scholar
  9. 9.
    Foxlin, E., et al.: Motion tracking requirements and technologies. In: Handbook of Virtual Environment Technology, vol. 8, pp. 163–210 (2002)Google Scholar
  10. 10.
    Placidi, G., et al.: Overall design and implementation of the virtual glove. Comput. Biol. Med. 43(11), 1927–1940 (2013)CrossRefGoogle Scholar
  11. 11.
    Shukor, A.Z., et al.: A new data glove approach for Malaysian sign language detection. Procedia Comput. Sci. 76, 60–67 (2015)CrossRefGoogle Scholar
  12. 12.
    Coton, J., et al.: Etude de faisabilité de l’analyse de mouvement de doigts par le capteur LeapMotion. In: Conférence Handicap, 9ème édition (2016)Google Scholar
  13. 13.
    Carabeo, C.G.G., et al.: Stroke patient rehabilitation: a pilot study of an android-based game. Simul. Gaming 45(2), 151–166 (2014)CrossRefGoogle Scholar
  14. 14.
    Susini, J., Pons, O., Thevenot, C.: Danse-doigts, jeu de motricité fine. Handicap 2016 La recherche au service de la qualité de vie et de l’autonomie, pp. 81–86 (2016)Google Scholar
  15. 15.
    Kizony, R., et al.: Tablet apps and dexterity: comparison between 3 age groups and proof of concept for stroke rehabilitation. J. Neurol. Phys. Ther. 40(1), 31–39 (2016)CrossRefGoogle Scholar
  16. 16.
    Lin, P.-C., et al.: A digital assessment system for evaluating kinetic tremor in essential tremor and Parkinson’s disease. BMC Neurol. 18(1), 25 (2018)CrossRefGoogle Scholar
  17. 17.
    De Lattre, C., et al.: Motor function measure: validation of a short form for young children with neuromuscular diseases. Arch. Phys. Med. Rehabil. 94(11), 2218–2226 (2013)CrossRefGoogle Scholar
  18. 18.
    Bérard, C., et al.: A motor function measure scale for neuromuscular diseases. Construction and validation study. Neuromuscul. Disord. 15(7), 463–470 (2005)CrossRefGoogle Scholar
  19. 19.
    Salvo, M.J.: Ethics of engagement: user centered designand rhetorical methodology. Tech. Commun. Quarterly 10(3), 273–290 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Adriana Gomes L. de Souza
    • 1
    • 2
  • Dominique Vincent-Genod
    • 3
  • Carole Vuillerot
    • 3
  • Michel Dubois
    • 4
  • Guillaume Thomann
    • 1
    • 2
  1. 1.Univ. Grenoble Alpes, CNRSGrenobleFrance
  2. 2.INP, G-SCOPGrenobleFrance
  3. 3.Service de Rééducation Pédiatrique, L’Escale, Hospices Civils de LyonLyonFrance
  4. 4.Laboratoire Interdisciplinaire de Psychologie, Univ. Grenoble AlpesGrenobleFrance

Personalised recommendations