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A Quality of Experience assessment of haptic and augmented reality feedback modalities in a gait analysis system

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  • Thiago Braga Rodrigues
  • Ciarán Ó Catháin
  • Noel E O’Connor
  • Niall Murray

Abstract

Gait analysis is a technique that is used to understand movement patterns and, in some cases, to inform the development of rehabilitation protocols. Traditional rehabilitation approaches have relied on expert guided feedback in clinical settings. Such efforts require the presence of an expert to inform the re-training (to evaluate any improvement) and the patient to travel to the clinic. Nowadays, potential opportunities exist to employ the use of digitized “feedback” modalities to help a user to “understand” improved gait technique. This is important as clear and concise feedback can enhance the quality of rehabilitation and recovery. A critical requirement emerges to consider the quality of feedback from the user perspective i.e. how they process, understand and react to the feedback. In this context, this paper reports the results of a Quality of Experience (QoE) evaluation of two feedback modalities: Augmented Reality (AR) and Haptic, employed as part of an overall gait analysis system. The aim of the feedback is to reduce varus/valgus misalignments, which can cause serious orthopedics problems. The QoE analysis considers objective (improvement in knee alignment) and subjective (questionnaire responses) user metrics in 26 participants, as part of a within subject design. Participants answered 12 questions on QoE aspects such as utility, usability, interaction and immersion of the feedback modalities via post-test reporting. In addition, objective metrics of participant performance (angles and alignment) were also considered as indicators of the utility of each feedback modality. The findings show statistically significant higher QoE ratings for AR feedback. Also, the number of knee misalignments was reduced after users experienced AR feedback (35% improvement with AR feedback relative to baseline when compared to haptic). Gender analysis showed significant differences in performance for number of misalignments and time to correct valgus misalignment (for males when they experienced AR feedback). The female group self-reported higher utility and QoE ratings for AR when compared to male group.

Suggested Citation

  • Thiago Braga Rodrigues & Ciarán Ó Catháin & Noel E O’Connor & Niall Murray, 2020. "A Quality of Experience assessment of haptic and augmented reality feedback modalities in a gait analysis system," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.
  • Handle: RePEc:plo:pone00:0230570
    DOI: 10.1371/journal.pone.0230570
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    References listed on IDEAS

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    1. Audrey Baudet & Claire Morisset & Philippe d'Athis & Jean-Francis Maillefert & Jean-Marie Casillas & Paul Ornetti & Davy Laroche, 2014. "Cross-Talk Correction Method for Knee Kinematics in Gait Analysis Using Principal Component Analysis (PCA): A New Proposal," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-7, July.
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