# Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario
## 1 Introduction  
The Comprehensive Geriatric Assessment (CGA) is a clinical procedure designed to capture information on medical, psycho-social and functional resources and problems of elderly people. The collected data is subsequently used to personalize the treatment prescription, allowing the creation of an overall plan for follow-up. CGA is an interdisciplinary effort, requiring the coordination of several clinical professionals such as occupational therapists, physiotherapists, social workers, or medical doctors. At the end, a typical CGA session takes about three hours of clinicians' time, and it should be repeated every six months to be really efficient [1]. The CGA comprises three different types of activities: a clinical interview, a multidimensional assessment and a customized care plan. First, a clinical interview allows the patient and their relatives to discuss the elder health problems. Next, multidimensional clinical tests are performed to evaluate the overall patient status. Finally, clinical professionals can create a personalized care plan after taking into account the evidence gathered during the two previous phases and the patient's evolution since the last CGA session. The multidimensional clinical tests include questionnaires (functional tests such as the Barthel one [2]), cognitive exercises (e.g., the Mini-Mental State Examination or MMSE [3]), and motion analysis exercises (as the Get Up & Go test [4]). This important part of the CGA procedure could be automated, which has been considered by the European Union ECHORD++ (European Coordination Hub for Open Robotics Development) project as one of the initiatives to be covered within its Public end-user Driven Technological Innovation (PDTI) program ([[http://echord.eu/pdti/pdti-healthcare/](http://echord.eu/pdti/pdti-healthcare/)]([http://echord.eu/pdti/pdti-healthcare/](http://echord.eu/pdti/pdti-healthcare/))). CLARC ([[http://echord.eu/essential_grid/clark/](http://echord.eu/essential_grid/clark/)]([http://echord.eu/essential_grid/clark/](http://echord.eu/essential_grid/clark/))) is an autonomous robotic solution designed to support CGA in hospitals and retirement homes [5; 6; 7]. It was designed by a multidisciplinary team including robotics and software engineers, medical doctors and physiotherapists from the Hospital Virgen del Rocio (Seville, Spain), and experts on user-centered design from the University of Troyes. Users were involved during each phase of the design and development of the system [8]. CLARC is currently able to perform several kinds of tests, but in this paper, it was used for performing a functional test (the Barthel one), and a motion analysis test (the Get Up & Go one). These tests include closed-answer questions (\"Select one option: 1, 2, 3 or 4\"), and monitoring of patient movements (\"get up from the chair and walk three meters\"). While deploying CLARC in larger evaluation pilots, its suitability with real patients in real-life hospital environments has already been demonstrated [5; 6; 7]. However, CLARC is not limited to just executing multidimensional tests. For instance, some kinds of tests are usually conducted at different rooms in the care centre. Therefore, CLARC is a mobile robot that must be able to guide patients and go to rooms when required, while avoiding static or dynamic obstacles. It must also be able to detect and adapt to exogenous events during the execution of a test, such as the patient asking for help or leaving the room. Moreover, and before conducting the tests, the CLARC robot will need to introduce itself as an accessible and helpful _assistant_ (or, at least, tool). Last but not least, elderly people undergoing CGA procedures are usually not familiar at all with robotic technologies and, therefore, it will be also crucial for CLARC to make them feel comfortable and reassured, and to offer them natural and intuitive ways to interact. These described behaviors of CLARC comprise many requirements.