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A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback

Abstract

Biofeedback from physical rehabilitation exercises has proved to lead to faster recovery, better outcomes, and increased patient motivation. In addition, it allows the physical rehabilitation processes carried out at the clinic to be complemented with exercises performed at home. However, currently existing approaches rely mostly on audio and visual reinforcement cues, usually presented to the user on a computer screen or a mobile phone interface. Some users, such as elderly people, can experience difficulties to use and understand these interfaces, leading to non-compliance with the rehabilitation exercises. To overcome this barrier, latest biosignal technologies can be used to enhance the efficacy of the biofeedback, decreasing the complexity of the user interface. In this paper we propose and validate a context-aware framework for the use of animatronic biofeedback, as a way of potentially increasing the compliance of elderly users with physical rehabilitation exercises performed at home. In the scope of our work, animatronic biofeedback entails the use of pre-programmed actions on a robot that are triggered in response to certain changes detected in the users biomechanical or electrophysiological signals. We use electromyographic and accelerometer signals, collected in real time, to monitor the performance of the user while executing the exercises, and a mobile robot to provide animatronic reinforcement cues associated with their correct or incorrect execution. A context-aware application running on a smartphone aggregates the sensor data and controls the animatronic feedback. The acceptability of the animatronic biofeedback has been tested on a set of volunteer elderly users, and results suggest that the participants found the animatronic feedback engaging and of added value.

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Acknowledgments

The authors gratefully acknowledge the support of the Spanish Ministry of Economy and Competitiveness through Project eGovernability (TIN2014-52665-C2-1-R). EGOKITUZ is funded by the Department of Education, Universities and Research of the Basque Government (grant IT395-10). The authors would also like to acknowledge the support of the Portuguese Fundação para a Ciência e Tecnologia (FCT) under the grant SFRH/BD/65248/2009, the company Bot’n Roll for supporting in use of their platform, as well as the Jatorra retired people association located in Donostia for giving us the opportunity to make the experiment in their facilities. We also want to thank Priscilla Alves, André Lourenço and Prof. Ana Fred for their collaboration in the foundational work for this research [30].

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Correspondence to Borja Gamecho.

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This article is part of the Topical Collection on Mobile Systems

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Gamecho, B., Silva, H., Guerreiro, J. et al. A Context-Aware Application to Increase Elderly Users Compliance with Physical Rehabilitation Exercises at Home via Animatronic Biofeedback. J Med Syst 39, 135 (2015). https://doi.org/10.1007/s10916-015-0296-1

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Keywords

  • Context-awareness
  • Mobile computing
  • Physiological signals
  • Human-computer interaction