Handchir Mikrochir Plast Chir 2018; 50(06): 425-432
DOI: 10.1055/a-0747-6037
Fallbericht
© Georg Thieme Verlag KG Stuttgart · New York

Smart Rehab: App-basiertes Rehabilitations-Training für Patienten nach Amputation der oberen Extremität – Case Report

Smart Rehab: App-based rehabilitation training for upper extremity amputees – Case Report
Cosima Prahm
1   Medizinische Universität Wien Chirurgie
,
Agnes Sturma
1   Medizinische Universität Wien Chirurgie
,
Fares Kayali
2   Technische Universitat Wien Human Computer Interaction
,
Eric Mörth
3   Medizinische Universität Wien Medizinische Statistik, Informatik und intelligente Systeme
,
Oskar Aszmann
1   Medizinische Universität Wien Chirurgie
› Author Affiliations
Further Information

Publication History

07/21/2018

09/16/2018

Publication Date:
08 January 2019 (online)

Zusammenfassung

Hintergrund Die Kontrolle einer myoelektrischen Prothese erfordert ein umfangreiches rehabilitatives Training, welches auf repetitiven Übungen basiert, angeleitet unter physiotherapeutischer Aufsicht. Doch zuhause fehlt vielen Patienten die Motivation, die Übungen aus der Physiotherapie weiterzuführen. Mobile Spiele auf dem Smartphone können zu einer Langzeit-Motivation beitragen, das Heimtraining mit der notwendigen Intensität fortzuführen.

Patienten und Methodik Wir entwickelten ein Trainingssystem, welches aus einer spielbasierten mobilen Rehabilitationsanwendung besteht, die mit dem Muskelsignal des Patienten gesteuert wird, außerdem einem Tablett zum Spielen der App, einem Elektrodenarmband und einem Handbuch. Bisher haben zwei Patienten an dieser Studie teilgenommen. Sie wurden gebeten die App für 4 Wochen zu Hause, 5 Mal pro Woche, für 10 bis 15 Minuten zu benutzen. Gemäß eines Prä- und Post-Test-Designs wurden die neuromuskulären Parameter der Patienten vor und nach dem mobilen Training untersucht. Evaluiert wurden u. a. die maximale Kontraktionskraft, Muskelseparation, proportionale Ansteuerung und Muskelausdauer, sowie die Nutzerstatistiken während der App-Benutzung.

Resultate Nach dem Training mit der App konnte eine signifikante Verbesserung (p < .01) aller untersuchten klinischen Parameter zur myoelektrischen Steuerung einer Prothese erzielt werden. Die Nutzerstatistiken ließen eine hohe Motivation zur Benutzung des Spiels und dem zusätzlichen Ausführen eines diagnostischen EMG-Tests bei einem Patienten erkennen, der andere teilnehmende Patient jedoch hatte zwar das Spiel gespielt, jedoch den EMG-Test vernachlässigt und diesen nur zur Hälfte absolviert.

Conclusio Die Trainings-App „MyoBeatz“ bietet nicht nur Anleitung und Feedback zur korrekten Ausführung von myoelektrischen Kommandos, sondern erhält auch die Motivation des Patienten durch verschiedene Spielmodi und Feedbackelemente. Durch eine Übersicht des Trainingsfortschritts in Form von Nutzer-Statistiken und Highscores kann der Rehabilitationsprozess überwacht und verglichen werden. Es konnte gezeigt werden, dass Patienten mit Amputation der oberen Extremität nach der Nutzung der spielbasierten App ihre neuromuskuläre Kontrolle, Kraft und Koordination signifikant verbessern konnten, so dass sie das Potential einer myoelektrischen Prothese voll ausschöpfen können.

Abstract

Background Control of a myoelectric prostheses entails rehabilitative training, based on repetitive exercises with a physiotherapist. However, many patients lack the motivation to continue the exercises in their home environment. Mobile games on the smartphone can provide patients with long-term motivation to continue the repetitive exercises that prepare the muscles for controlling a prosthesis at home. The aim of this study was to confirm the feasibility of a myoelectrical controlled mobile application and the impact of this game-based rehabilitation on the patient’s maximum voluntary contraction strength, proportionally activated muscle contraction and ability to separate muscle groups.

Patients and Methods We developed a training system that consisted of a game-based mobile rehabilitation application that is controlled by the patient’s muscle signal, a tablet to play on, an electrode armband and a manual. So far two patients have participated in this study. They were asked to use the app for 4 weeks at home, 5 times a week, for 10 to 15 minutes. The intervention was designed in a randomised controlled pre-test/post-test design and patients were measured for neuromuscular parameters before the intervention and afterwards. Evaluated parameters included maximum voluntary contraction force, muscle separation, proportional control and muscle endurance, as well as user statistics.

Results After training with the app, a significant improvement (p < .01) in all examined clinical parameters for myoelectric control of a prosthesis could be achieved. The user statistics showed a high motivation to play the game and ran an additional diagnostic EMG-Test on one patient; the other participating patient, however, had played the game but neglected the EMG test and only completed half of it.

Conclusion The training app not only provides instruction and feedback on the correct execution of myoelectric commands, but also maintains patient motivation through various game modes and feedback elements. The rehabilitation process could be monitored and compared through an overview of training progress in the form of user statistics and high scores. It could be shown that patients with upper extremity amputation could significantly improve their neuromuscular control, strength and coordination after using the game-based app so that they can fully benefit from the potential of a myoelectric prosthesis.

 
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