Personal Healthcare Agents (PHA)

 

“Agent” is an overloaded term in the computer science and artificial intelligence domain.

More recently researchers and practitioners have become acquainted to interact with digital agents, to speak natural language and have relatively simple tasks executed. Such agents can retrieve contacts, set alarms, provide driving directions to your work location and occasionally surprise with funny jokes.  This current state-of the-art has been a tremendous achievement following decades of research in the past 50 years [Riccardi , 2014].

Personal Healthcare Agents (PHA) will change people’s lives and revolutionize the way they manage their wellbeing and health. They will be able to sense the environment , the personal and social behavior , as well as the human organ systems. They will be elaborating, interpreting, summarizing and making sense of these signals and share it with you as well as your caregivers. They will be playing a key role in providing evidence for personalized therapies and in the doctors’ decision-making processes. PHAs will be supporting and motivating people to stir their habits towards healthy lifestyles. PHAs will be engaging patients to behave according to doctors’ recommendations and prescriptions. PHAs may be granted the mission to communicate  amongst themselves to share information and make sense of information and trends within demographic groups  across geographical and urban areas at different scales.

It will take at least  50 years. It will need new technology and research, change in people’s habits, disruption in doctors and health professionals protocols, innovation in healthcare services and education of next-generation doctors, engineers and professionals.

Let the research and technology journey begin.

 

 

PHA for Chronic  Conditions

Global increase in ageing population and incidence of chronic conditions such as hypertension, diabetes, and cardiovascular and mental diseases among others has created new challenges for healthcare systems. Research shows that early identification and continuous monitoring of these risk factors can open up opportunities for early intervention and improved management of these diseases.

The goal of this research stream is to develop technologies for creating intelligent agents which can support patients and users when out of the clinic while supporting the doctors to take more informed decisions about the patients by providing the most relevant information. This intelligent agents will be able to combine, extract knowledge, and learn from overt  (e.g. speech, text etc) and covert (e.g. heart rate, galvanic skin response) data streams generated by the patients with the world signals (traffic, weather, clinical, genomic, social, etc) which can be obtained through various sensors.

One overarching goal of this work is to take computational approaches out of the laboratory and simulation settings and evaluate  them in real world scenarios where doctors, health professionals, patients interact.

 

PHA for Hypertension >>

 

Riccardi G.,Towards Healthcare Personal Agents”, ACM International Conference on Multimodal Interaction, Workshop on Roadmapping the Future of Multimodal Interaction Research including Business Opportuinities and Challenges, Istanbul 2014.

Ghosh A., Stepanov E. A., Danieli M., and Riccardi G., “Are You Stressed? Detecting High Stress from User Diaries”, Proc. IEEE International Conference on Cognitive Infocommunications, Debrecen, 2017.

Ghosh A., Danieli M., Riccardi G., Annotation and Prediction of Stress and Workload from Physiological and Inertial Signals.” Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE