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EAI Endorsed Transactions on Pervasive Health and Technology

Editor(s)-in-Chief: Thanos Vasilakos, Thaier Hayajneh and Muhammad Imran

It is internationally recognized that future healthcare systems will be supported by pervasive healthcare systems in order to target the upcoming societal health challenges. Pervasive Health and Technology (PHT) Journal is a cross-disciplinary journal focusing on issues related to development, deli…

It is internationally recognized that future healthcare systems will be supported by pervasive healthcare systems in order to target the upcoming societal health challenges. Pervasive Health and Technology (PHT) Journal is a cross-disciplinary journal focusing on issues related to development, delivery and management of pervasive healthcare and the impact of technology within future healthcare systems. The journal aims to become an information source and to create a community of shared interests between health professionals, technologists, patients and other professionals related to pervasive healthcare. The journal will present and discuss issues pertaining to personal electronic health assistants, health crowdsourcing, data mining and knowledge management, needs of patients, disease prevention and awareness, electronic and mobile health platforms including design, implementation and evaluation of supporting hardware and software in ambulant and hospital workflows, needs of physicians, nurses and other healthcare staff.

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Submission Instructions
Publisher
EAI
ISSN
2411-7145
Volume
1
Published
12th Oct 2015

  • Detecting affective states in virtual rehabilitation

    Research Article in EAI Endorsed Transactions on Pervasive Health and Technology 15(2): e1

    Jesús Rivas, Felipe Orihuela-Espina, L. Sucar, Lorena Palafox, Jorge Hernández-Franco, Nadia Bianchi-Berthouze

    Abstract
    Virtual rehabilitation supports motor training following stroke by means of tailored virtual environments. To optimize therapy outcome, virtual rehabilitation systems automatically adapt to the diffe…Virtual rehabilitation supports motor training following stroke by means of tailored virtual environments. To optimize therapy outcome, virtual rehabilitation systems automatically adapt to the different patients’ changing needs. Adaptation decisions should ideally be guided by both the observable performance and the hidden mind state of the user. We hypothesize that some affective aspects can be inferred from observable metrics. Here we present preliminary results of a classification exercise to decide on 4 states; tiredness, tension, pain and satisfaction. Descriptors of 3D hand movement and finger pressure were collected from 2 post-stroke participants while they practice on a virtual rehabilitation platform. Linear Support Vector Machine models were learnt to unfold a predictive relation between observation and the affective states considered. Initial results are promising (ROC Area under the curve (mean+/-std): 0.713 +/- 0.137). Confirmation of these opens the door to incorporate surrogates of mind state into the algorithm deciding on therapy adaptation.
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  • Improving classification of posture based attributed attention assessed by ranked crowd-raters

    Research Article in EAI Endorsed Transactions on Pervasive Health and Technology 15(2): e2

    Patrick Heyer, Jesus Rivas, Luis Sucar, Felipe Orihuela-Espina

    Abstract
    Attribution of attention from observable body posture is plausible, providing additional information for affective computing applications. We previously reported a promissory $69.72\pm10.50$ ($\mu\pm…Attribution of attention from observable body posture is plausible, providing additional information for affective computing applications. We previously reported a promissory $69.72\pm10.50$ ($\mu\pm \sigma$) of F-measure to use posture as a proxy for attributed attentional state with implications for affective computing applications. Here, we aim at improving that classification rate by reweighting votes of raters giving higher confidence to those raters that are representative of the raters population. An increase to $75.35\pm11.66$ in F-measure was achieved. The improvement in predictive power by the classifier is welcomed and its impact is still being assessed.
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  • Haptic Feedback in Motor Hand Virtual Therapy Increases Precision and Generates Less Mental Workload

    Research Article in EAI Endorsed Transactions on Pervasive Health and Technology 15(2): e3

    Cristina Ramírez-Fernández, Alberto L. Morán, Eloísa García-Canseco

    Abstract
    In this work we show that haptic feedback in upper limb motor therapy improves performance and generates a lower mental workload. To demonstrate this, two groups of participants (healthy adults and e…In this work we show that haptic feedback in upper limb motor therapy improves performance and generates a lower mental workload. To demonstrate this, two groups of participants (healthy adults and elders with hand motor problems) used a low-cost haptic device (Novint Falcon) and a non-robotic device (Leap Motion Controller). Participants conducted the same
    rehabilitation task by using a non-immersive virtual environment.
    Results show significant differences for all participants regarding precision on the use of the haptic feedback device. Additionally, participants in the older adult group demonstrated a lower mental workload while using the haptic device (Novint Falcon).
    Finally, qualitative results show that participants preferred to conduct their therapy exercises by using the haptic device, as they found it more useful, easier to use and easier to learn.
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  • Requirements Identification Towards a Design of Adaptive ICTs for Supporting Bipolar Disorder Treatment in Different Healthcare Contexts

    Research Article in EAI Endorsed Transactions on Pervasive Health and Technology 15(2): e4

    Emanuele Torri, Oscar Mayora, Jesus Cobo, Diego Palao

    Abstract
    This paper presents patient and caregiver perspective on ICTs supporting bipolar disorder management in multinational healthcare provisioning contexts. The envisioned mHealth solutions should adopt g…This paper presents patient and caregiver perspective on ICTs supporting bipolar disorder management in multinational healthcare provisioning contexts. The envisioned mHealth solutions should adopt general requirements that could be instantiated into different clinical settings. Engagement of users in designing new technologies for mental health is crucial to ensure empowerment and patient-centeredness of services.
    We performed focus groups to understand user needs, attitudes and experiences towards the supportive ICTs in two target regions where the expected solutions will operate. The survey offered valuable inputs for the construction of the clinical requirements used to produce a trans-national call for tender on mobile health solutions aimed at supporting bipolar disorders treatment among public purchasers in different European countries. The study was part of the NYMHPA-MD (Next Generation Mobile Platform for Health in Mental Disorders) project, co-funded by the European Commission.

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  • Mining Minds: an innovative framework for personalized health and wellness support

    Research Article in EAI Endorsed Transactions on Pervasive Health and Technology 15(2): e5

    Oresti Banos, Muhammad Amin, Wahajat Khan, Taqdir Ali, Muhammad Afzal, Byeong Kang, Sungyoung Lee

    Abstract
    The world is witnessing a spectacular shift in the delivery of health and wellness care. The key ingredient of this transformation consists in the use of revolutionary digital technologies to empower…The world is witnessing a spectacular shift in the delivery of health and wellness care. The key ingredient of this transformation consists in the use of revolutionary digital technologies to empower people in their self-management as well as to enhance traditional care procedures. While substantial domain-specific contributions have been provided to that end in the recent years, there is a clear lack of platforms that may orchestrate, and intelligently leverage, all the data, information and knowledge generated through these technologies. This work presents Mining Minds, an innovative framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized healthcare and wellness support. Mining Minds embraces some of the currently most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, and state-of-the-art concepts and methods, such as Context-Awareness, Knowledge Bases or Analytics, among others. This paper aims at thoroughly describing the efficient and rational combination and interoperation of these modern technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support.
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