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Wearable Sensors for Neurological Diseases Remote Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 4354

Special Issue Editors


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Guest Editor
Instituto de Medicina Molecular, 1649-028 Lisbon, Portuga; CNS—Campus Neurológico, 2560-280 Torres Vedras, Portugal
Interests: digital health; wearable sensors; technology-based objective measure; neurodegenrative diseases; movement disorders

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Guest Editor
1. CNS-Campus Neurológico Senior, 2560-280 Torres Vedras, Portugal
2. Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal
3. Laboratory of Clinical Pharmacology and Therapeutics, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal
Interests: neurodegenerative diseases; clinical pharmacology

Special Issue Information

Dear Colleagues,

Many emerging technological devices have the potential to improve data capture sensitivity, accuracy, reproducibility, and feasibility, thus surpassing some of the limitations of traditional clinical tests.

So far, wearable devices have mostly been tested and used in laboratory settings. With the expected significant increase in the number of neurological patients in the coming decades, remote monitoring, with its ability to provide a more holistic and continuous view of a patient's condition in a given environment, will become a crucial tool for providing and optimizing patient care. Therefore, it is critical that researchers focus on developing devices, algorithms, and assessment protocols that can help us achieve this goal.

For this Special Issue, we encourage researchers working in the field of neurological patient remote monitoring to share their latest findings on this new method for evaluating patients.

Topic of interest include:

  • Advances in wearable technology for remote monitoring of neurological diseases;
  • Protocols developed for evaluating neurological patients in real-world scenarios;
  • Major roadblocks and challenges in developing new remote monitoring devices for neurological patients;
  • User perspective regarding using technology in real-life situations.

Dr. Raquel Bouça-Machado
Prof. Dr. Joaquim J. Ferreira
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.

Published Papers (2 papers)

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9 pages, 1395 KiB  
Article
Co-Designing Digital Technologies for Improving Clinical Care in People with Parkinson’s Disease: What Did We Learn?
by Mariana H. G. Monje, Sylvie Grosjean, Martin Srp, Laura Antunes, Raquel Bouça-Machado, Ricardo Cacho, Sergio Domínguez, John Inocentes, Timothy Lynch, Argyri Tsakanika, Dimitrios Fotiadis, George Rigas, Evžen Růžička, Joaquim Ferreira, Angelo Antonini, Norberto Malpica, Tiago Mestre, Álvaro Sánchez-Ferro and iCARE-PD Consortium
Sensors 2023, 23(10), 4957; https://doi.org/10.3390/s23104957 - 22 May 2023
Cited by 1 | Viewed by 1808
Abstract
The healthcare model is shifting towards integrated care approaches. This new model requires patients to be more closely involved. The iCARE-PD project aims to address this need by developing a technology-enabled, home-based, and community-centered integrated care paradigm. A central part of this project [...] Read more.
The healthcare model is shifting towards integrated care approaches. This new model requires patients to be more closely involved. The iCARE-PD project aims to address this need by developing a technology-enabled, home-based, and community-centered integrated care paradigm. A central part of this project is the codesign process of the model of care, exemplified by the active participation of patients in the design and iterative evaluation of three sensor-based technological solutions. We proposed a codesign methodology used for testing the usability and acceptability of these digital technologies and present initial results for one of them, MooVeo. Our results show the usefulness of this approach in testing the usability and acceptability as well as the opportunity to incorporate patients’ feedback into the development. This initiative will hopefully help other groups incorporate a similar codesign approach and develop tools that are well adapted to patients’ and care teams’ needs. Full article
(This article belongs to the Special Issue Wearable Sensors for Neurological Diseases Remote Monitoring)
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21 pages, 1189 KiB  
Review
A Clinical Perspective on Bespoke Sensing Mechanisms for Remote Monitoring and Rehabilitation of Neurological Diseases: Scoping Review
by Jia Min Yen and Jeong Hoon Lim
Sensors 2023, 23(1), 536; https://doi.org/10.3390/s23010536 - 03 Jan 2023
Cited by 7 | Viewed by 1966
Abstract
Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote [...] Read more.
Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote rehabilitation architecture and enabling technology mandates the elaboration of sensing mechanisms tailored to individual clinical needs. This study aims to review current trends in the application of sensing mechanisms in remote monitoring and rehabilitation in neurological diseases, and to provide clinical insights to develop bespoke sensing mechanisms. A systematic search was performed using the PubMED database to identify 16 papers published for the period between 2018 to 2022. Teleceptive sensors (56%) were utilized more often than wearable proximate sensors (50%). The most commonly used modality was infrared (38%) and acceleration force (38%), followed by RGB color, EMG, light and temperature, and radio signal. The strategy adopted to improve the sensing mechanism included a multimodal sensor, the application of multiple sensors, sensor fusion, and machine learning. Most of the stroke studies utilized biofeedback control systems (78%) while the majority of studies for neurodegenerative disorders used sensors for remote monitoring (57%). Functional assessment tools that the sensing mechanism may emulate to produce clinically valid information were proposed and factors affecting user adoption were described. Lastly, the limitations and directions for further development were discussed. Full article
(This article belongs to the Special Issue Wearable Sensors for Neurological Diseases Remote Monitoring)
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