A Holistic Approach for Enhancing Museum Performance and Visitor Experience.

Managing modern museum content and visitor data analytics to achieve higher levels of visitor experience and overall museum performance is a complex and multidimensional issue involving several scientific aspects, such as exhibits' metadata management, visitor movement tracking and modelling, location/context-aware content provision, etc. In related prior research, most of the efforts have focused individually on some of these aspects and do not provide holistic approaches enhancing both museum performance and visitor experience. This paper proposes an integrated conceptualisation for improving these two aspects, involving four technological components. First, the adoption and parameterisation of four ontologies for the digital documentation and presentation of exhibits and their conservation methods, spatial management, and evaluation. Second, a tool for capturing visitor movement in near real-time, both anonymously (default) and eponymously (upon visitor consent). Third, a mobile application delivers personalised content to eponymous visitors based on static (e.g., demographic) and dynamic (e.g., visitor movement) data. Lastly, a platform assists museum administrators in managing visitor statistics and evaluating exhibits, collections, and routes based on visitors' behaviour and interactions. Preliminary results from a pilot implementation of this holistic approach in a multi-space high-traffic museum (MELTOPENLAB project) indicate that a cost-efficient, fully functional solution is feasible, and achieving an optimal trade-off between technical performance and cost efficiency is possible for museum administrators seeking unfragmented approaches that add value to their cultural heritage organisations.

Sollerman Hand Function Sub-Test "Write with a Pen": A Computer-Vision-Based Approach in Rehabilitation Assessment.

Impaired hand function is one of the most frequently persistent consequences of stroke. Throughout the rehabilitation process, physicians consistently monitor patients and perform kinematic evaluations in order to assess their overall progress in motor recovery. The Sollerman Hand Function Test (SHT) is a valuable assessment tool used to evaluate a patient's capacity to engage in daily activities. It holds great importance in the field of medicine as it aids in the assessment of treatment effectiveness. Nevertheless, the requirement for a therapist's physical presence and the use of specialized materials make the test time-consuming and reliant on clinic availability. In this paper, we propose a computer-vision-based approach to the "Write with a pen" sub-test, originally included in the SHT. Our implementation does not require extra hardware equipment and is able to run on lower-end hardware specifications, using a single RGB camera. We have incorporated all the original test's guidelines and scoring methods into our application, additionally providing an accurate hand spasticity evaluator. After briefly presenting the current research approaches, we analyze and demonstrate our application, as well as discuss some issues and limitations. Lastly, we share some preliminary findings from real-world application usage conducted at the University campus and outline our future plans.