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Healthcare
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Comprehensive Care for Multiple Sclerosis
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Comprehensive Care for Multiple Sclerosis

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Chronic Care".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 329

Editors

Prof. Dr. Anastasios Orologas

E-Mail Website
Guest Editor
"Agios Loukas" Private Clinic, 55236 Thessaloniki, Greece
Interests: multiple sclerosis; neuroinflammation
Dr. Antonia Kaltsatou

E-Mail Website
Guest Editor
Physical Education and Sport Science, University of Thessaly, 42132 Trikala, Greece
Interests: chronic disease management; exercise physiology; clinical exercise physiology; environmental physiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue, “Comprehensive Care for Multiple Sclerosis”, brings together current advances and innovative approaches aimed at improving the diagnosis, management, and overall well-being of individuals living with Multiple Sclerosis (MS). It highlights the multifaceted nature of the disease and emphasizes the need for integrated, patient-centered strategies that address the physical, cognitive, psychological, and social aspects of health. The Special Issue showcases research on emerging therapeutic interventions, multidisciplinary rehabilitation, lifestyle and exercise-based strategies, technological innovations, and personalized care models. By presenting evidence-based insights and forward-looking perspectives, this collection aims to support clinicians, researchers, and healthcare professionals in optimizing long-term outcomes and enhancing quality of life for people with MS.

Prof. Dr. Anastasios Orologas
Dr. Antonia Kaltsatou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly 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

  • multiple sclerosis
  • interdisciplinary rehabilitation
  • comprehensive care
  • neurorehabilitation
  • chronic disease management

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Published Papers (1 paper)

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Review

22 pages, 1260 KB  
Review
Artificial Intelligence Applications to Support Physical Activity, Mobility, and Fatigue Management in People with Multiple Sclerosis: A Scoping Review
by Pantazis Deligiannis, Iosif Alexandros Kouidis, Anastasia Theofanous, Maria Anifanti, Asterios Deligiannis and Evangelia Kouidi
Healthcare 2026, 14(14), 2219; https://doi.org/10.3390/healthcare14142219 - 21 Jul 2026
Abstract
Background: Physical activity plays a vital role in caring for people with multiple sclerosis (MS). Yet, challenges like fatigue, mobility impairment, fall risk, symptom fluctuation, and poor access to rehabilitation often make sustained participation difficult. Adhering to physical activity programmes is tough. Artificial [...] Read more.
Background: Physical activity plays a vital role in caring for people with multiple sclerosis (MS). Yet, challenges like fatigue, mobility impairment, fall risk, symptom fluctuation, and poor access to rehabilitation often make sustained participation difficult. Adhering to physical activity programmes is tough. Artificial intelligence (AI) may transform wearable, smartphone, clinical, and patient-reported data into interpretable information for monitoring, prediction and individualized support. Objective: Building on the identified need for individualized support, this scoping review mapped original AI-based studies relevant to physical activity, gait, mobility, ambulation, fatigue, fall risk, and real-world functioning in people with MS. Methods: The review followed PRISMA-ScR principles. Search covered records published from 1 January 2016 to 14 May 2026 across biomedical, rehabilitation, technology-oriented, trial registry, and citation-searching sources. Eligible studies included MS or MS-specific data, an explicit AI/ML or model-derived predictive analytics component, and an activity-related clinical domain. Results: The search identified 332 records/reports. After removing 127 duplicates, 205 records were screened, 45 full texts were assessed, and 21 original AI studies met the eligibility criteria. These addressed inertial sensor deep learning, wearable gait speed estimation, postural sway fall risk prediction, connected device prediction of fatigue and health state, smartphone-based ambulation characterization, treadmill or walkway gait classification, chair stand fall status prediction, daily life gait/turning fall prediction, fear-of-falling detection, sensor-derived fatigue prediction, mobile/wearable modelling of MS, and physical activity prediction. Conclusions: AI can extract clinically relevant patterns from gait, wearable, smartphone, connected device, clinical, and patient-reported data in MS. However, evidence does not yet show that AI-supported systems improve physical activity, adherence, fatigue burden, fall risk, quality of life, or functional independence. AI is therefore promising but early, and prospective, externally validated, human-supervised, fatigue-aware, safety-sensitive studies are needed to support clinically meaningful, patient-centred MS rehabilitation and activity planning. Full article
(This article belongs to the Special Issue Comprehensive Care for Multiple Sclerosis)
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