Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario
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Autores: A. Romero Garcés, Jesús Martínez Cruz
, Juan F. Inglés Romero, Cristina Vicente Chicote , Rebeca Marfil Robles , Antonio Bandera
- Localización: Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021): [Málaga, 22 al 24 de septiembre de 2021] / coord. por Rafael Capilla Sevilla , Maider Azanza Sese , Miguel Rodríguez Luaces , M. M. Roldán García , Dolores Burgueño Caballero , José Raúl Romero Salguero , José Antonio Parejo Maestre , José Francisco Chicano García , Marcela Genero , Óscar Díaz García , José González Enríquez , Mª Carmen Penadés ; Silvia Mara Abrahao Gonzales (col.) , 2021
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate frail elderly people in order to provide them with customized therapy plans. 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 to automate CGA tests in as much as possible, we have designed and developed CLARC: a mobile robot aimed at helping physicians to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined tests. The design of CLARC has required dealing with both functional (robot's skills and tasks) and non-functional aspects (e.g. performance, safety, or user satisfaction, among others). This paper describes a novel model-based approach aimed at helping designers (1) to specify the contextual information available to the robot+ADs the Non-Functional Properties (NFP considered relevant for a given application+ADs and how (and to what extent) changes in the context may affect these properties+ADs and, from these models (2) to generate the runtime infrastructure allowing the robot to monitor its execution context and estimate high-level QoS metrics to know how well it is performing in terms of the selected NFPs.
