Multiple sclerosis (MS) is an autoimmunogenic disease involving demyelination within the central nervous system. Many of the typical impairments associated with MS can affect gait patterns. With walking ability being one of the most decisive factors when assessing quality of life and independent living, this review focuses on matters, which are considered of significance for maintaining and supporting ambulation. This article is an attempt to describe current research and available interventions that the caring healthcare professional can avail of and to review the present trends in research to further these available options. Evidence-based rehabilitation techniques are of interest in the care of patients with MS, given the various existing modalities of treatment. In this review, we summarise the primary factors affecting ambulation and highlight available treatment methods. We review studies that have attempted to characterise gait deficits within this patient population. Finally, as ambulatory rehabilitation requires multidisciplinary interventions, we examine approaches, which may serve to support and maintain ambulation within this patient group for as long as possible.
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http://dx.doi.org/10.1080/09638280902751931 | DOI Listing |
J Phys Ther Educ
January 2025
John J. DeWitt is the associate director, education and professional development and associate clinical professor in the Rehab Services at The Ohio State University Wexner Medical Center, and School of Health & Rehabilitation Sciences, College of Medicine, The Ohio State University, 453 W 10th Ave, Rm 516, Columbus, OH 43210 Please address all correspondence to John J. DeWitt.
Introduction: Emerging evidence shows positive impact of postprofessional physical therapy education (residency and fellowship) specific to participants; however, outcomes on organizational impact are largely unknown. The purpose of this project was to describe the impact residency and fellowship training has on financial metrics. A secondary purpose of this case study was to describe trends associated with higher productivity.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Science and Engineering, Saga University, Saga 840-8502, Japan.
Infrared array sensor-based fall detection and activity recognition systems have gained momentum as promising solutions for enhancing healthcare monitoring and safety in various environments. Unlike camera-based systems, which can be privacy-intrusive, IR array sensors offer a non-invasive, reliable approach for fall detection and activity recognition while preserving privacy. This work proposes a novel method to distinguish between normal motion and fall incidents by analyzing thermal patterns captured by infrared array sensors.
View Article and Find Full Text PDFDiagnostics (Basel)
January 2025
Department of General Medicine, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Bunkyo-ku, Tokyo 113-8510, Japan.
: The effects of ageing on the diaphragm are unclear. This study examined the association between ageing and diaphragm thickness, thickening fraction (TF), and diaphragm excursion (DE) as assessed by ultrasonography after adjusting for other factors. The relationship between these parameters and maximal inspiratory pressure (MIP) was also investigated.
View Article and Find Full Text PDFJ Frailty Aging
February 2025
Division of Geriatrics and Osher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.
Background: Pre-frailty is highly prevalent and multimodal lifestyle interventions are effective for preventing transition to frailty. However, little is known about the potential for medical group visits (MGV) to prevent frailty progression.
Objectives: To assess the feasibility and acceptability of the MGV Age Self Care-Resilience.
ACS Appl Mater Interfaces
January 2025
Center for Wearable Intelligent Systems and Healthcare, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
Recognizing human body motions opens possibilities for real-time observation of users' daily activities, revolutionizing continuous human healthcare and rehabilitation. While some wearable sensors show their capabilities in detecting movements, no prior work could detect full-body motions with wireless devices. Here, we introduce a soft electronic textile-integrated system, including nanomaterials and flexible sensors, which enables real-time detection of various full-body movements using the combination of a wireless sensor suit and deep-learning-based cloud computing.
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