Ramón Hervás

Dr. Ramón Hervás

MAml Research Lab, Castilla La-Mancha University, 13071 Ciudad Real, Spain
orcid
Full Professor. Academic Dean.

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 July 2015 in Sensors
Verified
Journal Article
Open access
PDF file
IDIvan Gonzalez Diaz
Ivan Gonzalez Diaz
JFJesus Fontecha
Jesus Fontecha
Ramón HervásRamón Hervás
Ramón Hervás
Jose BravoJose Bravo
Jose Bravo
A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.

1 October 2016 in Journal of Biomedical Informatics
Verified
Journal Article
Closed access
TMTania MONDEJAR
Tania MONDEJAR
Ramón HervásRamón Hervás
Ramón Hervás
EJEsperanza Johnson
Esperanza Johnson
CGCarlos Gutierrez
Carlos Gutierrez
JLJose M. Latorre
Jose M. Latorre

12 May 2012 in Personal and Ubiquitous Computing
Verified
Journal Article
Open access
PDF file
JFJesus Fontecha
Jesus Fontecha
FNFco. Javier Navarro
Fco. Javier Navarro
Ramón HervásRamón Hervás
Ramón Hervás
Jose BravoJose Bravo
Jose Bravo
Elderly people become weak until they reach a state of frailty. At this time, their health begins to get worse and they are more likely to suffer bone fractures, disorders, and diseases, and they become dependent. Delaying or reducing frailty level is important to improve the quality of life of elderly people. There are many parameters to consider for frailty detection and diagnosis. In this sense, assessment of physical condition, through gait and other physical exercises, is the most important domain in frailty evaluation. Nowadays, geriatricians and physiotherapists use several tests and scales based on indicators to provide scores related to physical assessment. However, these scores depend on the viewpoint of the geriatrician. So, the assessment contains a level of subjectivity. Besides, frailty detection includes the study of other indicators from nutritional, cognitive, and social domains. In this paper, we propose a system to support physicians determining an accurate and centralized elderly frailty diagnosis, by using an accelerometer-enabled mobile phone. The accelerometer collects data movement from physical activity and calculates a set of measures that are combined with clinical indicators (from tests and medical instruments) providing a frailty assessment to facilitate decision-making and the subsequent treatment.

1 January 2014 in IEEE Journal of Biomedical and Health Informatics
Verified
Journal Article
Closed access
Ramón HervásRamón Hervás
Ramón Hervás
Jose BravoJose Bravo
Jose Bravo
JFJesus Fontecha
Jesus Fontecha
This paper presents a system for supplying spatial orientation and support to cognitively impaired people in their daily activities. The system is a technological solution based on external aid at a practical level (substitution-based rehabilitation). In particular, we propose a model focused on points of interest or well-known places, in which user-friendly routes to a destination are generated based on the user context rather than the conventional street names and quantitative distances. Moreover, the system offers augmented reality views that include contextual information. This philosophy of navigation more closely matches the needs of the user than do conventional navigation systems; the proposal is especially useful for users who are not accustomed to using new technologies (e.g., elderly people), people experiencing disorientation and, more generally, individuals with a slight cognitive deficit. The system also includes an application that allows the relatives of the user to establish tasks that must be performed at a specific location and to monitor the activities of the user to detect potentially risky situations.

23 May 2017
Verified
Conference Paper
Open access
PDF file
Ramón HervásRamón Hervás
Ramón Hervás
DRDavid Ruiz-Carrasco
David Ruiz-Carrasco
TMTania MONDEJAR
Tania MONDEJAR
JBJose Bravo
Jose Bravo

30 September 2016 in Health Informatics Journal
Verified
Journal Article
Closed access
PDF file
EJEsperanza Johnson
Esperanza Johnson
Ramón HervásRamón Hervás
Ramón Hervás
CFCarlos Gutiérrez López de la Franca
Carlos Gutiérrez López de la Franca
TMTania MONDEJAR
Tania MONDEJAR
SOSergio F Ochoa
Sergio F Ochoa
JFJesús Favela
Jesús Favela
Assistive technologies can improve the quality of life of people diagnosed with different forms of social communication disorders. We report on the design and evaluation of an affective avatar aimed at engaging the user in a social interaction with the purpose of assisting in communication therapies. A human–avatar taxonomy is proposed to assist the design of affective avatars aimed at addressing social communication disorder. The avatar was evaluated with 30 subjects to assess how effectively it conveys the desired emotion and elicits empathy from the user. Results provide evidence that users become used to the avatar after a number of interactions, and they perceive the defined behavior as being logical. The users’ interactions with the avatar entail affective reactions, including the mimic emotions that users felt, and establish a preliminary ground truth about prototypic empathic interactions with avatars that is being used to train learning algorithms to support social communication disorder evaluation.