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Article

Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario

1
University of Málaga, 29071 Málaga, Spain
2
Biometric Vox S.L., 30100 Murcia, Spain
3
Quercus Software Engineering Group, University of Extremadura, 10003 Cáceres, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(18), 6618; https://doi.org/10.3390/app10186618
Received: 1 August 2020 / Revised: 11 September 2020 / Accepted: 18 September 2020 / Published: 22 September 2020
(This article belongs to the Special Issue Cognitive Robotics)
Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate frail elderly people in order to create therapy plans that improve their quality and quantity of life. The whole process includes the completion of standardized questionnaires or specific movements, which are performed by the patient and do not necessarily require the presence of a medical expert. With the aim of automatizing these parts of the CGA, we have designed and developed CLARC (smart CLinic Assistant Robot for CGA), a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Using CLARC to conduct geriatric tests will reduce the time medical professionals have to spend on purely mechanical tasks, giving them more time to develop individualised care plans for their patients. In fact, ideally, CLARC will perform these tests on its own. In parallel with the effort to correctly address the functional aspects, i.e., the development of the robot tasks, the design of CLARC must also deal with non-functional properties such as the degree of interaction or the performance. We argue that satisfying user preferences can be a good way to improve the acceptance of the robot by the patients. This paper describes the integration into the software architecture of the CLARC robot of the modules that allow these properties to be monitored at run-time, providing information on the quality of its service. Experimental evaluation illustrates that the defined quality of service metrics correctly capture the evolution of the aspects of the robot’s activity and its interaction with the patient covered by the non-functional properties that have been considered. View Full-Text
Keywords: assistive robotics; Comprehensive Geriatric Assessment; non-functional properties; QoS metrics assistive robotics; Comprehensive Geriatric Assessment; non-functional properties; QoS metrics
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MDPI and ACS Style

Romero-Garcés, A.; Martínez-Cruz, J.; Inglés-Romero, J.; Vicente-Chicote, C.; Marfil, R.; Bandera, A. Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario. Appl. Sci. 2020, 10, 6618. https://doi.org/10.3390/app10186618

AMA Style

Romero-Garcés A, Martínez-Cruz J, Inglés-Romero J, Vicente-Chicote C, Marfil R, Bandera A. Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario. Applied Sciences. 2020; 10(18):6618. https://doi.org/10.3390/app10186618

Chicago/Turabian Style

Romero-Garcés, Adrián, Jesús Martínez-Cruz, Juan F. Inglés-Romero, Cristina Vicente-Chicote, Rebeca Marfil, and Antonio Bandera. 2020. "Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario" Applied Sciences 10, no. 18: 6618. https://doi.org/10.3390/app10186618

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