Pain and anxiety treatment based on social robot interaction with children to improve patient experience
Total activity: 7
Type of activity
MIN DE ECONOMIA Y COMPETITIVIDAD
Funding entity code
A major focus for children's quality of life programs in hospitals is improving their experiences during procedures. In anticipation of treatment, children may become anxious and during procedures pain appears. The challenge of the coordinated project is to design pioneering techniques based on the use of social robots to improve the patient experience by eliminating or minimizing pain and anxiety. According to this proposed challenge, this research aims to design and develop specific human – social robot interaction with pet robots. Robot interactive behavior will be designed based on modular skills using soft-computing paradigms. Social skills are defined as the robot ability to adapt its behavior during the course of the interaction to remain a compelling companion and engage children over time even when novelty effect has worn off. In order to obtain user adaptation of the robot, machine learning and general soft computing paradigms will be designed and evaluated. Soft computing algorithms will be modularized in an easy form such that it can be implemented like simple building blocks in a specially designed programming environment. Methodological research will be completed by considering three different scenarios from three different points of views, building a 3x3 matrix of variable research difficulty. Scenarios will range from 'acute', even ER, patients (traumatism, for instance), middle-term intervention (up to around 8 days) and long-term interaction, including long-term hospitalization and companionship at home (chronic diseases). The three-fold research vision includes the therapeutic related effect (including children's biological stress, analgesics delivery, perceived health state, mood, perception of social support, willingness to follow treatment), measured with clinical instruments, the quality of the children-pet robot interaction, measured with direct observation and subjective report techniques, and behavior modelling from the robot register, including temporal series evaluation using machine learning and data mining techniques. Hence, project’s difficulty and novelty will vary from (i) the use of pet robots in short intercourses, where novelty effect is the most important factor for interactive behavior; (ii) to validate anxiety and FLACC pain scales when comparing clinical and psychological variables in middle-term interaction; (iii) to design effective behaviors for an engaging long-term interaction between children and pet robots; or (iv) to design new scales relating observed interaction and robot temporal series based on sensors and actuators. From the soft computing perspective, research will be performed (i) to design robot behaviors reducing pain and anxiety (machine learning), and (ii) to study relationships between clinical parameters, behavior and temporal series (data mining) in order to generate an evaluation method of pain and anxiety.
Angulo, C.; Pfeiffer, S.; Alenyà, G.; Téllez, R. Journal of ambient intelligence and smart environments Vol. 7, num. 3, p. 301-313 DOI: 10.3233/AIS-150315 Date of publication: 2015-01-01 Journal article
Diaz, M.; Paillacho, D.; Angulo, C.; Torres, O.; González, J.; Albo-Canals, J. ACM/IEEE International Conference on Human-Robot Interaction p. 152-153 DOI: 10.1145/2559636.2559797 Presentation's date: 2014-03 Presentation of work at congresses