Mobile and Wearable Systems for Smarthealth

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensors and Healthcare".

Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 3335

Special Issue Editor


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Guest Editor
Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
Interests: cyber-security and privacy; smarthealth systems; mobile and wireless computing; Internet-of-Things

Special Issue Information

Dear Colleagues,

Smarthealth, the combination of computing technologies to address healthcare problems, is an interdisciplinary research area of great interest. Mobile and wearable devices, such as smartphones, smartwatches, and head-mounted displays, play an important role in smarthealth research by providing the ability to continuously collect, process, and display information on a personalized basis. Unlike conventional computing devices, mobile and wearable devices have their own challenges, including security/privacy concerns, usability design, computational and energy constraints, and so on. This Special Issue is devoted to recent advancements in mobile and wearable systems and applications in smarthealth, especially systems that address pressing healthcare issues.

Topics of interest for the Special Issue include (though are not restricted to) the following:

  • wearable/mobile computing support for pandemic management, e.g., social distancing and contact tracing
  • wearable cameras for healthcare applications;
  • algorithms and methods for processing wearable data;
  • security and privacy of wearable healthcare systems;
  • wearable assistive technologies, including applications supporting assisted living;
  • wearable/mobile sensing algorithms and systems related to healthcare;
  • experiences in real-world deployments of wearable/mobile-based healthcare systems

Prof. Chiu C. Tan
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • health data security/privacy
  • assistive technologies
  • telehealth
  • mobile health
  • wireless health

Published Papers (1 paper)

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Research

20 pages, 3169 KiB  
Article
A French–Greek Cross-Site Comparison Study of the Use of Automatic Video Analyses for the Assessment of Autonomy in Dementia Patients
by Anastasios Karakostas, Alexandra König, Carlos Fernando Crispim-Junior, François Bremond, Alexandre Derreumaux, Ioulietta Lazarou, Ioannis Kompatsiaris, Magda Tsolaki and Philippe Robert
Biosensors 2020, 10(9), 103; https://doi.org/10.3390/bios10090103 - 21 Aug 2020
Cited by 7 | Viewed by 2966
Abstract
Background: At present, the assessment of autonomy in daily living activities, one of the key symptoms in Alzheimer’s disease (AD), involves clinical rating scales. Methods: In total, 109 participants were included. In particular, 11 participants during a pre-test in Nice, France, and 98 [...] Read more.
Background: At present, the assessment of autonomy in daily living activities, one of the key symptoms in Alzheimer’s disease (AD), involves clinical rating scales. Methods: In total, 109 participants were included. In particular, 11 participants during a pre-test in Nice, France, and 98 participants (27 AD, 38 mild cognitive impairment—MCI—and 33 healthy controls—HC) in Thessaloniki, Greece, carried out a standardized scenario consisting of several instrumental activities of daily living (IADLs), such as making a phone call or preparing a pillbox while being recorded. Data were processed by a platform of video signal analysis in order to extract kinematic parameters, detecting activities undertaken by the participant. Results: The video analysis data can be used to assess IADL task quality and provide clinicians with objective measurements of the patients’ performance. Furthermore, it reveals that the HC statistically significantly outperformed the MCI, which had better performance compared to the AD participants. Conclusions: Accurate activity recognition data for the analyses of the performance on IADL activities were obtained. Full article
(This article belongs to the Special Issue Mobile and Wearable Systems for Smarthealth)
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