Abstract
In rehabilitation medicine and in occupational therapy (OT) in particular the assessment tool is essentially the human eye observing the person performing activities of daily living to evaluate his/her level of independence, efficacy, effort, and safety, in order to design an individualized treatment program. On the contrary, in other clinical settings, diagnostics have very sophisticated technological tools such as the Computed Axial Tomography, 3D ultrasound, Functional Magnetic Resonance Imaging, Positron Emission Tomography and many others. Now it is possible to fill this gap in rehabilitation using various enabling technologies currently in a phase of real explosion, through which it will be possible to provide the rehabilitator, in addition to the evidence provided by the human eye, also a large amount of data describing the person’s motion in 3D, the interaction with the environment (forces, contact pressure maps, motion parameters related to the manipulation of objects, etc.), and the ‘internal’ parameters (heart rate, blood pressure, respiratory rate, sweating, etc.). This amount of information can be fed back to the clinician in an animation that represents the reality augmented with all the above parameters using methodologies of Augmented Reality (AR). The main benefit of this new interaction methodology is twofold: the observed scenarios depicted in animations contain all the relevant parameters simultaneously and the related data are well defined and contextualized. This new methodology is a revolution in rehabilitative evaluation methods that allow on one hand to increase the objectivity and effectiveness of clinical observation, and on the other hand to re-define more reliable assessment scales and more effective rehabilitation programs, more user-centered.
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This project was partially funded by the Provincia Autonoma di Trento in the framework of the AUSILIA project.
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De Cecco, M. et al. (2017). Augmented Reality to Enhance the Clinician’s Observation During Assessment of Daily Living Activities. In: De Paolis, L., Bourdot, P., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2017. Lecture Notes in Computer Science(), vol 10325. Springer, Cham. https://doi.org/10.1007/978-3-319-60928-7_1
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