Rafael Ferro García

mHealthDroid: A Novel Framework for Agile Development of Mobile Health Applications

Mobile health is an emerging field which is attracting much attention. Nevertheless, tools for the development of mobile health applications are lacking. This work presents mHealthDroid, an open source Android implementation of a mHealth Framework designed to facilitate the rapid and easy development of biomedical apps. The framework is devised to leverage the potential of mobile devices like smartphones or tablets, wearable sensors and portable biomedical devices. The framework provides functionalities for resource and communication abstraction, biomedical data acquisition, health knowledge extraction, persistent data storage, adaptive visualization, system management and value-added services such as intelligent alerts, recommendations and guidelines.

Design, implementation and validation of a novel open framework for agile development of mobile health applications

The delivery of healthcare services has experienced tremendous changes during the last years. Mobile health or mHealth is a key engine of advance in the forefront of this revolution. Although there exists a growing development of mobile health applications, there is a lack of tools specifically devised for their implementation. This work presents mHealthDroid, an open source Android implementation of a mHealth Framework designed to facilitate the rapid and easy development of mHealth and biomedical apps. The framework is particularly planned to leverage the potential of mobile devices such as smartphones or tablets, wearable sensors and portable biomedical systems. These devices are increasingly used for the monitoring and delivery of personal health care and wellbeing. The framework implements several functionalities to support resource and communication abstraction, biomedical data acquisition, health knowledge extraction, persistent data storage, adaptive visualization, system management and value-added services such as intelligent alerts, recommendations and guidelines. An exemplary application is also presented along this work to demonstrate the potential of mHealthDroid. This app is used to investigate on the analysis of human behavior, which is considered to be one of the most prominent areas in mHealth. An accurate activity recognition model is developed and successfully validated in both offline and online conditions.

Psychometric properties of the Spanish version of the Experiencing of Self Scale (EOSS) for assessment in Functional Analytic Psychotherapy

BACKGROUND The Experiencing of Self Scale (EOSS) was created to evaluate the experience of the personal self, within the field of Functional Analytic Psychotherapy. This paper presents a study of the reliability and validity of the EOSS in a Spanish sample. METHOD The study sample, chosen from 24 different centres, comprised 1,040 participants aged between 18-75, of whom 32% were men and 68% women. The clinical sample was made up of 32.7%, whereas 67.3% had no known problem. To obtain evidence of convergent validity, other questionnaires related to the self (EPQ-R, DES, RSES) were used for comparison. RESULTS The EOSS showed high internal consistency (Cronbachs α = .941) and significantly high correlations with the EPQ-R Neuroticism scale and the DES Dissociation scale, while showing negative correlations with the Rosenberg Self-Esteem Scale (RSES). The EOSS revealed 4 principal factors: a self in close relationships, a self with casual social relationships, a self in general and a positive self-concept. Significant statistical differences were found between the clinical and standard sample, the former showing a higher average. CONCLUSIONS The EOSS had high internal consistency, showing evidence of convergent validity with similar scales and proving useful for the assessment of people with psychological problems related to the self.