Abstract
With the increasing share of elderly population worldwide, the necessity of assistive technologies to support clinicians in monitoring their health conditions is becoming more and more relevant. Recent medical literature has proposed the notion of frail elderly, which rapidly became a key element of clinical practices for the estimation of well-being in aging population. The evaluation of frailty is commonly based on self reported outcomes and occasional physicians evaluations, leading to possibly biased results. In this work we propose a data driven method to automatically evaluate two of the main aspects contributing to the frailty estimation, i.e. the motility of the subject and his cognitive status. The first one is evaluated using visual computing tools, while the latter relies on a virtual reality based system. We provide an extensive experimental assessment performed on two sets of data acquired in a sensorised protected discharge facility located in a local hospital. Our results are in good agreement with the assessment manually performed by physicians, nicely showing the potential capability of our approach to complement current protocols of evaluation.
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Martini, C. et al. (2019). Visual Computing Methods for Assessing the Well-Being of Older People. In: Bechmann, D., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2018. Communications in Computer and Information Science, vol 997. Springer, Cham. https://doi.org/10.1007/978-3-030-26756-8_9
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