Deakin University
Browse

File(s) under permanent embargo

SpinalLog: visuo-haptic feedback in musculoskeletal manipulation training

conference contribution
posted on 2019-01-01, 00:00 authored by D Antony Chacon, Eduardo Velloso, Thuong HoangThuong Hoang, Katrin Wolf
Current techniques for teaching spinal mobilisation follow the traditional classroom approach: an instructor demonstrates a technique and students attempt to emulate it by practising on each other while receiving feedback from the instructor. This paper introduces SpinalLog, a novel tangible user interface (TUI) for teaching and learning spinal mobilisation. The system was co-designed with physiotherapy experts to look and feel like a human spine, supporting the learning of mobilisation techniques through real-time visual feedback and deformation based passive haptic feedback. We evaluated Physical Fidelity, Visual Feedback, and Passive Haptic Feedback in an experiment to understand their effects on physiotherapy students' ability to replicate a mobilisation pattern recorded by an expert. We found that simultaneous feedback has the largest effect, followed by passive haptic feedback. The high fidelity of the interface has little effect, but it plays an important role in the perception of the system's benefit.

History

Pagination

5-14

Location

Tempe, Ariz.

Start date

2019-03-17

End date

2019-03-20

ISBN-13

978-1-4503-6196-5

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2019, the author(s)

Editor/Contributor(s)

[Unknown]

Title of proceedings

TEI 2019 : Proceedings of the Thirteenth International Conference on Tangible, Embedded, and Embodied Interactions

Event

Association for Computing Machinery. Conference (13th : 2019 : Tempe, Ariz.)

Publisher

Association for Computing Machinery

Place of publication

New York, N.Y.

Series

Association for Computing Machinery Conference

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC