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

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

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

Cloud computing application model for online recommendation through fuzzy logic system

Cloud computing can offer us different distance services over the internet. We propose an online application model for health care systems that works by use of cloud computing. It can provide a higher quality of services remotely and along with that, it decreases the cost of chronic patient. This model is composed of two sub-model that each one uses a different service, one of these is software as a service (SaaS) which is user related and another one is Platform as a service (PaaS) that is engineer related. Doctors classify the chronic diseases into different stages according to their symptoms. As the clinical data has a non-numeric value, we use the fuzzy logic system in Paas model to design this online application model. Based on this classification, patienst can receive the proper recommendation through smart devices (SaaS model).Facultad de Informátic

Cloud computing application model for online recommendation through fuzzy logic system

Cloud computing can offer us different distance services over the internet. We propose an online application model for health care systems that works by use of cloud computing. It can provide a higher quality of services remotely and along with that, it decreases the cost of chronic patient. This model is composed of two sub-model that each one uses a different service, one of these is software as a service (SaaS) which is user related and another one is Platform as a service (PaaS) that is engineer related. Doctors classify the chronic diseases into different stages according to their symptoms. As the clinical data has a non-numeric value, we use the fuzzy logic system in Paas model to design this online application model. Based on this classification, patienst can receive the proper recommendation through smart devices (SaaS model).Facultad de Informátic

HCI for health and wellbeing: challenges and opportunities

In terms of Human–Computer Interaction, healthcare presents paradoxes: on the one hand, there is substantial investment in innovative health technologies, particularly around “big data” analytics and personal health technologies; on the other hand, most interactive health technologies that are currently deployed at scale are difficult to use and few innovative technologies have achieved significant market penetration. We live in a time of change, with a shift from care being delivered by professionals towards people being expected to be actively engaged and involved in shared decision making. Technically, this shift is supported by novel health technologies and information resources; culturally, the pace of change varies across contexts. In this paper, I present a “space” of interactive health technologies, users and uses, and interdependencies between them. Based on a review of the past and present, I highlight opportunities for and challenges to the application of HCI methods in the design and deployment of digital health technologies. These include threats to privacy, patient trust and experience, and opportunities to deliver healthcare and empower people to manage their health and wellbeing in ways that better fit their lives and values

Интеллектуальные мультимодальные интерфейсы для обработки биомедицинских сигналов : практикум

Рассматривается использование биомедицинских сигналов при реализации интеллектуальных мультимодальных интерфейсов. Информационные характеристики биомедицинских сигналов, модулирующихся функциональными процессами организма, могут быть использованы в приложениях, с помощью которых требуется получать данные о психофизическом состоянии человека и производить количественную оценку изменения состояния человека. Разработка интеллектуальных мультимодальных интерфейсов рассматривается на примере интерфейсов мозг-компьютер. В качестве входных модальностей интерфейса используется сигнал ЭЭГ и данные с 3‑осевого акселерометра, размещенного на голове человека. В работе представлены материалы и методы, связанные с архитектурой мультимодальных интерфейсов, применением методов обработки сигналов и методов машинного обучения для формирования метрик изменения функционального состояния человека, а также спецификации для работы с облачным сервисом Google Fit для хранения данных приложений. Отдельное внимание уделено проектированию интерфейсов мозг-компьютер с применением открытых программных продуктов BCI2000 и Open Vibe

Developing multimodal intelligent affective interfaces for tele-home health care

Accounting for a patient\u27s emotional state is integral in medical care. Tele-health research attests to the challenge clinicians must overcome in assessing patient emotional state when modalities are limited (J. Adv. Nurs. 36(5) 668). The extra effort involved in addressing this challenge requires attention, skill, and time. Large caseloads may not afford tele-home health-care (tele-HHC) clinicians the time and focus necessary to accurately assess emotional states and trends. Unstructured interviews with experienced tele-HHC providers support the introduction of objective indicators of patients\u27 emotional status in a useful form to enhance patient care. We discuss our contribution to addressing this challenge, which involves building user models not only of the physical characteristics of users-in our case patients-but also models of their emotions. We explain our research in progress on Affective Computing for tele-HHC applications, which includes: developing a system architecture for monitoring and responding to human multimodal affect and emotions via multimedia and empathetic avatars; mapping of physiological signals to emotions and synthesizing the patient\u27s affective information for the health-care provider. Our results using a wireless non-invasive wearable computer to collect physiological signals and mapping these to emotional states show the feasibility of our approach, for which we lastly discuss the future research issues that we have identified. (C) 2003 Elsevier Science Ltd. All rights reserved