Physiotherapy students are expected to master a range of complex manual skills to safely and effectively assess and treat physical conditions caused by mechanical dysfunctions of the spine. The current method for teaching these skills involves a demonstration by the instructor on a student or skeleton model, followed by students practicing on a peer. Some of the major challenges in learning these techniques include the ability to discern tactile sensations of resistance and the ability to effectively assess the mobility range of the spine. These movements are very subtle and difficult for students to perform and feel in their own practice.
This project aims to improve students’ mastery of manual skills in physiotherapy by targeting experiential learning using passive haptic sensor technology. Building on technology previously developed by SocialNUI researchers (eg: HandLog, pictured below), we aim to build a passive haptic device called SpinalLog, which uses conductive foam sensors to measure the pressure being applied to the spine by the whole hand or by individual fingers during a simulated spinal assessment.
The passive haptic sensor device represents an evolution of pedagogical practice in physiotherapy and related disciplines, using tangible and passive haptic technology. Students are exposed to authentic simulations of clinical conditions, replicating the conditions of real life patients with different tissues and clinical scenarios, such as swelling. A visual guidance system that enables the students to match their movements to the instructor’s movements provides important feedback for the students in terms of their performance and practice. Students can also visualise the subtle movements demonstrated by the instructor using a force distribution chart in real time. Students’ out of class practice is enhanced with reflective feedback and instructor demonstrations as a bench mark for performance.
The project aims to deliver positive learning outcomes for physiotherapy students by accelerating the conversion of theoretical concepts into manual skills for the effective delivery of therapeutic spinal assessments and mobilisation treatment techniques.
This project is a collaboration between the Microsoft Research Centre for Social Natural User Interfaces (SocialNUI) in the School of Computing and Information Systems and the Department of Physiotherapy at the University of Melbourne.
The project is supported by a University of Melbourne Learning and Teaching Initiative (LTI) Grant 2016.
Eduardo Velloso, Lecturer, School of Computing and Information Systems, The University of Melbourne
Antony Chacon, Masters of Philosophy student, Microsoft Research Centre for SocialNUI, The University of Melbourne
Frank Vetere, Professor, The University of Melbourne
Thuong Hoang, Lecturer, School of Information Technology, Deakin University
Louisa Remedios, Associate Professor, Department of Physiotherapy, The University of Melbourne
David Kelly, Lecturer, Department of Physiotherapy, The University of Melbourne