Workshop on Affective Computing in Pervasive Health
会议地点: Trento, Italy
Many recent ubiquitous computing technologies in healthcare and wellbeing do now consider the emotional state of involved actors including the patient, members of its social support circle and/or the healthcare providers. The incorporation of the affective component enhances the interaction of the actors with the computational system permitting a richer response from the system or facilitating its use by means of adaptive strategies. This improves the delivery of care throughout the different stages of the healthcare cycle; from prevention and diagnosis to treatment and monitoring.
The Affective Computing in Pervasive Health workshop focuses on the presentation and discussion of relevant scholarly works that include the affective component of the patient in the technologies, which could improve the medical treatments and health programs.
Topics of interest include, but are not limited to:
New strategies or sensors for sensing physiological information.
Methods and algorithms for automatic recognition, monitoring and assessment of affective states.
Artificial intelligent solutions to adapt systems’ response according to affective input.
Systems to improve emotional patients’ wellbeing, e.g. systems that promote motivation or engagement to the therapeutic program.
Telemedicine systems that include the affective component of the patient.
Informatics and/or cloud based solutions for remote monitoring of metabolic, physiological, or biomechanical information.
Multimodal sensing of affective information.
Algorithms for mining affective information in healthcare.
Human-Computer interface solutions exploiting affective states of users for healthcare purposes.
Affective hyper-scanning (of more than one stakeholder at once)-
Validation of affective models against behavioural or neurological data.
Observational or interventional studies of affective systems for healthcare including full randomized controlled trial (RCT), proof of concepts and case studies.