Abstract
Balance and gait impairments are highly prevalent in the neurological population. Although current rehabilitation strategies focus on motor learning principles, it is of interest to expand into embodied sensori-motor learning; that is learning through a continuous interaction between cognitive and motor systems, within an enriched sensory environment. Current developments in engineering allow for the development of enriched sensory environments through interactive feedback. The Augmented Movement Platform for Embodied Learning (AMPEL) was developed, both in terms of hardware and software by an inter-disciplinary circular participatory design strategy. The developed device was then tested for in-between session reliability for the outcome measures inter-step interval and total onset time. Ten healthy participants walked in four experimental paths on the device in two different sessions, and between session correlations were calculated. AMPEL was developed both in terms of software and hardware, with three Plug-In systems (auditory, visual, auditory + visual). The auditory Plug-In allows for flexible application of augmented feedback. The in-between session reliability of the outcomes measured by the system were between high and very high on all 4 walked paths, tested on ten healthy participants [mean age 41.8 ± 18.5; BMI 24.8 ± 6.1]. AMPEL shows full functionality, and has shown between session reliability for the measures of inter-step-intervals and total-onset-time in healthy controls during walking on different paths.




Similar content being viewed by others
Change history
11 February 2021
A Correction to this paper has been published: https://doi.org/10.1007/s12193-020-00360-w
References
Schmidt RA, Lee TD (2011) Motor control and learning: a behavioral emphasis, 5th edn. Human Kinetics, Champaign
Fitts PM, Posner MI (1967) Human performance. Brooks/Cole Pub. Co., Belmont
Moe VF (2004) How to understand skill acquisition in sport. Bull Sci Technol Soc 24(3):213–224
Kleynen M, Beurskens A, Olijve H, Kamphuis J, Braun S (2020) Application of motor learning in neurorehabilitation: a framework for health-care professionals. Physiother Theory Pract 36(1):1–20. https://doi.org/10.1080/09593985.2018.1483987
Lesaffre M, Vets T, Moens B, Leman M (eds) (2015) Using auditory feedback for the rehabilitation of symmetrical body-weight distribution after ischemic stroke or brain trauma. In: Proceedings of the ninth triennial conference of the European society for the cognitive sciences of music. RNCM, Manchester
Lesaffre M (2018) Investigating embodied music cognition for health and well-being. In: Bader R (ed) Springer handbook of systematic musicology. Springer, Berlin, pp 779–791
Leman M (2016) The expressive moment: how interaction (with music) shapes human empowerment. MIT Press, Cambridge
Maes PJ, Buhmann J, Leman M (2016) 3Mo: a model for music-based biofeedback. Front Neurosci 10:548
Lorenzoni V, Van den Berghe P, Maes PJ, De Bie T, De Clercq D, Leman M (2018) Design and validation of an auditory biofeedback system for modification of running parameters. J Multimodal User Interfaces 13:167–180
Maes PJ, Lorenzoni V, Six J (2018) The SoundBike: musical sonification strategies to enhance cyclists’ spontaneous synchronization to external music. J Multimodal User Interfaces 13:155–166
Skulmowski A, Rey GD (2018) Embodied learning: introducing a taxonomy based on bodily engagement and task integration. Cogn Res Princ Implic 3(1):6
Kosmas P, Ioannou A, Zaphiris P (2019) Implementing embodied learning in the classroom: effects on children’s memory and language skills. Educ Med Int 56(1):59–74
Muller MJ, Kuhn S (1993) Participatory design. Commun ACM 36(4):24–28
Sigrist R, Rauter G, Riener R, Wolf P (2013) Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychon Bull Rev 20(1):21–53
Schmitz G, Bergmann J, Effenberg AO, Krewer C, Hwang TH, Muller F (2018) Movement sonification in stroke rehabilitation. Front Neurol 9:389
Stolze H, Klebe S, Zechlin C, Baecker C, Friege L, Deuschl G (2004) Falls in frequent neurological diseases–prevalence, risk factors and aetiology. J Neurol 251(1):79–84
Saverino A, Waller D, Rantell K, Parry R, Moriarty A, Playford ED (2016) The role of cognitive factors in predicting balance and fall risk in a neuro-rehabilitation setting. PLoS ONE 11(4):e0153469
Inc. LI. LUMO play 2013–2018 https://www.lumoplay.com/
Berg K, Wood-Dauphinee S, Williams JI (1995) The balance scale: reliability assessment with elderly residents and patients with an acute stroke. Scand J Rehabil Med 27(1):27–36
Newstead AH, Hinman MR, Tomberlin JA (2005) Reliability of the Berg balance scale and balance master limits of stability tests for individuals with brain injury. J Neurol Phys Ther 29(1):18–23
Franchignoni F, Martignoni E, Ferriero G, Pasetti C (2005) Balance and fear of falling in Parkinson’s disease. Park Relat Disord 11(7):427–433
Moumdjian L, Sarkamo T, Leone C, Leman M, Feys P (2017) Effectiveness of music-based interventions on motricity or cognitive functioning in neurological populations: a systematic review. Eur J Phys Rehabil Med 53(3):466–482
Wulf G, Lewthwaite R (2016) Optimizing performance through intrinsic motivation and attention for learning: the optimal theory of motor learning. Psychon Bull Rev 23(5):1382–1414
Thaut MH (2015) The discovery of human auditory-motor entrainment and its role in the development of neurologic music therapy. Prog Brain Res 217:253–266
Dalla Bella S (2018) Music and movement: towards a translational approach. Neurophysiol Clin 48(6):377–386
Hinkle DE, Wiersma W, Jurs SG (2002) Applied statistics for the behavioral sciences. Houghton Mifflin, Boston
Heyes CM, Foster CL (2002) Motor learning by observation: evidence from a serial reaction time task. Q J Exp Psychol A 55(2):593–607
Grau-Sanchez J, Duarte E, Ramos-Escobar N, Sierpowska J, Rueda N, Redon S, Veciana de Las Heras M, Pedro J, Särkämö T, Rodríguez-Fornells A (2018) Music-supported therapy in the rehabilitation of subacute stroke patients: a randomized controlled trial. Ann N Y Acad Sci. https://doi.org/10.1111/nyas.13590
Monster Piano (2020). http://www.monsterpiano.com/products.php
Acknowledgments
We acknowledge support by the UGent Expertise Center for Nano- and Microfabrication – NaMiFab.
Funding
We acknowledge the Methusalem project (awarded by the Flemish Government) at UGent and the UHasselt BOF grant for funding this study.
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.
The error in the affiliations of the co-authors Dr. Thomas Vervust and Prof. Peter Feys corrected.
Appendix
Appendix
See the Fig. 5.
Rights and permissions
About this article
Cite this article
Moumdjian, L., Vervust, T., Six, J. et al. The Augmented Movement Platform For Embodied Learning (AMPEL): development and reliability. J Multimodal User Interfaces 15, 77–83 (2021). https://doi.org/10.1007/s12193-020-00354-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12193-020-00354-8