Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Patient Relationship Management (PRM) and AI: The role of Affective Computing

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceArtificial Intelligence (AI) has been praised as the next big thing in the computing revolution, and it's been touted as a game-changer in a variety of fields, including healthcare. The increasing popularity of this technology is driving early adoption and leading to a lack of consideration of the patient perspective in its use, bringing new sources of distrust that come from the absence of human attributes. This study aims to address this problem by presenting a strategy in the area of affective computing that will combat this absence of empathy experienced by the patient during a medical process. To reach this goal, a Design Science Research Methodology will be followed. A preliminary literature study had already been completed, and the research topic and objectives had been established. In addition, to apply the artifact developments, a bot will be built and evaluated by a set of users. The increased awareness of these AI systems will, expectedly, stimulate their use. By adding new research into the affective computing field, it is also expected to contribute to the digital healthcare evolution and to encourage further scientific progress in this area

Predicting continuous conflict perception with Bayesian Gaussian processes

Conflict is one of the most important phenomena of social life, but it is still largely neglected by the computing community. This work proposes an approach that detects common conversational social signals (loudness, overlapping speech, etc.) and predicts the conflict level perceived by human observers in continuous, non-categorical terms. The proposed regression approach is fully Bayesian and it adopts Automatic Relevance Determination to identify the social signals that influence most the outcome of the prediction. The experiments are performed over the SSPNet Conflict Corpus, a publicly available collection of 1430 clips extracted from televised political debates (roughly 12 hours of material for 138 subjects in total). The results show that it is possible to achieve a correlation close to 0.8 between actual and predicted conflict perception

Evaluating a Personal Stress Monitoring System

Now-a-days, Life is generally much more stressful than in the past. Stress is the word that we use when we feel that we are overloaded mentally in our thoughts and wonder whether we can really cope with those placed upon us. Sometimes, stress gets us going and they are good for us but at other times, it could be the cause to undermine both our mental and physical health. The way we respond to a challenge can be considered as a kind of stress. Part of our response to a challenge is physiological and affects our own physical state. When we are faced with a challenge or a threat, our body releases some resources to protect us against them - either to get away as fast as we can, or to fight against them. This fight-or-flight response is our body\u27s sympathetic nervous system reacting to a stressful event. During this response, our body produces larger quantities of the chemicals such as cortisol, adrenaline and noradrenaline, which triggers a higher heart rate, heightened muscle preparedness, sweating, and alertness. All these factors help us to protect ourselves in a dangerous or challenging situation. But based on the frequency of stress facing by a person, these changes may affect his or her health negatively. In order to evaluate an individual\u27s stress, I worked on this thesis in developing a personal stress monitoring system to capture the stress undergoing by an individual in his or her daily life

Enhancing health care via affective computing

Affective computing is a multidisciplinary field that studies the various ways by which computational processes are able to elicit, sense, and detect manifestations of human emotion. While the methods and technology delivered by affective computing have demonstrated very promising results across several domains, their adoption by healthcare is still at its initial stages. With that aim in mind, this commentary paper introduces affective computing to the readership of the journal and praises for the benefits of affect-enabled systems for prognostic, diagnostic and therapeutic purposes.peer-reviewe

Feasibility Pilot Outcomes of a Mammography Decision Support and Navigation Intervention for Women With Serious Mental Illness Living in Supportive Housing Settings.

Objective: People with serious mental illness (SMI) experience significant disparities in morbidity and mortality from preventable and treatable medical conditions. Women with SMI have low mammography screening rates. SMI, poverty, and poor access to care can have a significant effect on a woman’s opportunity to learn about and discuss breast cancer screening with health care providers. This study examines the feasibility pilot outcomes of mammography decision support and patient navigation intervention (DSNI) for women with SMI living in supportive housing settings. The primary research question was: Does the DSNI increase knowledge, promote favorable attitudes, and decrease decisional conflict relating to screening mammography? Methods: We developed the intervention with the community using participatory methods. Women (n = 21) with SMI who had not undergone screening mammography in the past year participated in an educational module and decision counseling session and received patient navigation over a 6-month period. We conducted surveys and interviews at baseline and follow-ups to assess mammography decisional conflict. Results: Among study participants, 67% received a mammogram. The mammogram DSNI was feasible and acceptable to women with SMI living in supportive housing settings. From baseline to 1-month follow-up, decisional conflict decreased significantly (P= .01). The patient navigation process resulted in 270 attempted contacts (M= 12.86, SD = 10.61) by study staff (phone calls and emails with patient and/or case manager) and 165 navigation conversations (M= 7.86, SD = 4.84). A barrier to navigation was phone communication, with in-person navigation being more successful. Participants reported they found the intervention helpful and made suggestions for further improvement. Conclusions: The process and outcomes evaluation support the feasibility and acceptability of the mammography DSNI. This project provides initial evidence that an intervention developed with participatory methods can improve cancer screening outcomes in supportive housing programs for people with SMI

Socially Assistive Robot Enabled Personalised Care for People with Dementia in Australian Private Homes

Australia’s population is ageing and a large number of people are living in their own homes. Motivated by design science as the research methodology, the authors in this paper embark the research on designing, implementing, trialling and evaluating robot enabled user-centred care for people with dementia in home-based settings. Given the importance of pursuing person-centred care practice, this research involves marrying personhood in health care with socially assistive robotics to the designs of social robot enabled person-centred care services. We have conducted first ever longitudinal robotic trials through real deployments in Australian private dwellings to evaluate the impact of the designed socially assistive robots on older people with dementia. The data analyses have been performed through both interactional data (with 2044 times of interaction and a total of 167 hours of usage) and quality of robot experience survey. The descriptive analysis of interactional data show that the designed socially assistive robot enabled care system has facilitated breaking the technology barrier of people with dementia, positively proving sensory enrichment to participants and provided respires to the participants’ carers. The quality of robot experience survey statistics indicate the participants had positive experience with their robot

Psychophysiology in games

Psychophysiology is the study of the relationship between psychology and its physiological manifestations. That relationship is of particular importance for both game design and ultimately gameplaying. Players’ psychophysiology offers a gateway towards a better understanding of playing behavior and experience. That knowledge can, in turn, be beneficial for the player as it allows designers to make better games for them; either explicitly by altering the game during play or implicitly during the game design process. This chapter argues for the importance of physiology for the investigation of player affect in games, reviews the current state of the art in sensor technology and outlines the key phases for the application of psychophysiology in games.The work is supported, in part, by the EU-funded FP7 ICT iLearnRWproject (project no: 318803).peer-reviewe