Telerehabilitation: lessons from the COVID-19 pandemic and future perspectives

Rheumatology International, Journal Year: 2024, Volume and Issue: 44(4), P. 577 - 582

Published: Feb. 6, 2024

Language: Английский

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Exploring Augmented Reality Integration in Diagnostic Imaging: Myth or Reality?

Diagnostics, Journal Year: 2024, Volume and Issue: 14(13), P. 1333 - 1333

Published: June 23, 2024

This study delves into the transformative potential of integrating augmented reality (AR) within imaging technologies, shedding light on this evolving landscape. Through a comprehensive narrative review, research uncovers wealth literature exploring intersection between AR and medical imaging, highlighting its growing prominence in healthcare. AR's integration offers host opportunities to enhance surgical precision, bolster patient engagement, customize interventions. Moreover, when combined with technologies like virtual (VR), artificial intelligence (AI), robotics, opens up new avenues for innovation clinical practice, education, training. However, amidst these promising prospects lie numerous unanswered questions areas ripe exploration. emphasizes need rigorous elucidate efficacy AR-integrated interventions, optimize workflows, address technological challenges. As healthcare landscape continues evolve, sustained efforts are crucial fully realizing impact imaging. Systematic reviews also overlook regulatory developmental factors, particularly regard devices. These include compliance standards, safety regulations, risk management, validation, processes. Addressing aspects will provide understanding challenges settings, informing stakeholders about considerations successful implementation. navigating approval process requires substantial financial resources expertise, presenting barriers entry smaller innovators. Collaboration across disciplines concerted overcome be essential frontier harnessing revolutionize delivery.

Language: Английский

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AI-Driven Telerehabilitation: Benefits and Challenges of a Transformative Healthcare Approach

AI, Journal Year: 2025, Volume and Issue: 6(3), P. 62 - 62

Published: March 17, 2025

Artificial intelligence (AI) has revolutionized telerehabilitation by integrating machine learning (ML), big data analytics, and real-time feedback to create adaptive, patient-centered care. AI-driven systems enhance analyzing patient personalize therapy, monitor progress, suggest adjustments, eliminating the need for constant clinician oversight. The benefits of AI-powered include increased accessibility, especially remote or mobility-limited patients, greater convenience, allowing patients perform therapies at home. However, challenges persist, such as privacy risks, digital divide, algorithmic bias. Robust encryption protocols, equitable access technology, diverse training datasets are critical addressing these issues. Ethical considerations also arise, emphasizing human oversight maintaining therapeutic relationship. AI aids clinicians automating administrative tasks facilitating interdisciplinary collaboration. Innovations like 5G networks, Internet Medical Things (IoMT), robotics further telerehabilitation’s potential. By transforming rehabilitation into a dynamic, engaging, personalized process, together represent paradigm shift in healthcare, promising improved outcomes broader worldwide.

Language: Английский

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Kinematic and plantar pressure analysis in Strumpell-Lorrain disease: A case report

Brain Disorders, Journal Year: 2023, Volume and Issue: 11, P. 100097 - 100097

Published: Sept. 1, 2023

Background: Hereditary Spastic Paraparesis (HSP), also known as Strumpell-Lorrain disease, is a neurodegenerative disorder characterized by progressive muscle weakness, lower limb spasticity, and abnormal gait. It genetically inherited condition affecting the spinal cord. Currently, there lack of scientific literature on evaluation space-time parameters plantar pressures in individuals with HSP. Therefore, objective this study to assess spatial-temporal using motion sensors baropodometric platform. Case presentation: A 50-year-old female patient body mass index (BMI) 22.28 presented our hospital 12-year history disease. She exhibited typical symptoms including spastic paraparesis limbs, leading difficulty walking. The initial symptom walking was diagnosed when she 38 years old. Apart from impairments associated spasticity ataxia, demonstrated weakness without any cognitive deficits. Conclusions: This analysis elucidates challenges faced disease walking, particularly during swing phase, resulting reliance monopodal support. Additionally, experiences dorsiflexion ankle due gastrocnemius muscle, an increased load forefoot. These findings contribute better understanding specific gait abnormalities biomechanical

Language: Английский

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Unlocking the potential of RNN and CNN models for accurate rehabilitation exercise classification on multi-datasets

Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: April 12, 2024

Abstract Physical rehabilitation is crucial in healthcare, facilitating recovery from injuries or illnesses and improving overall health. However, a notable global challenge stems the shortage of professional physiotherapists, particularly acute some developing countries, where ratio can be as low one physiotherapist per 100,000 individuals. To address these challenges elevate patient care, field physical progressively integrating Computer Vision Human Activity Recognition (HAR) techniques. Numerous research efforts aim to explore methodologies that assist exercises evaluate movements, which incorrect potentially worsen conditions. This study investigates applying various deep-learning models for classifying using benchmark KIMORE UI-PRMD datasets. Employing Bi-LSTM, LSTM, CNN, CNN-LSTM, alongside Random Search architectural design Hyper-parameter tuning, our investigation reveals (CNN) model top performer. After cross-validation, technique achieves remarkable mean testing accuracy rates 93.08% on dataset 99.7% dataset. marks slight improvement 0.75% 0.1%, respectively, compared previous In addition, expanding beyond exercise classification, this explores dataset’s utility disease identification, consistently demonstrates an outstanding 89.87%, indicating its promising role both identification within context rehabilitation.

Language: Английский

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Evaluation of Patient-Facing Mobile Apps to Support Physiotherapy Care: Systematic Review

JMIR mhealth and uhealth, Journal Year: 2024, Volume and Issue: 12, P. e55003 - e55003

Published: Jan. 24, 2024

Background Mobile health interventions delivered through mobile apps are increasingly used in physiotherapy care. This may be because of the potential to facilitate changes behavior, which is central aims care by physiotherapists. A benefit using their ability incorporate behavior change techniques (BCTs) that can optimize effectiveness physiotherapeutic interventions. Research continues suggest despite importance, strategies often missing patient management. Evaluating physiotherapists use drive inform clinical practice and potentially improve outcomes. Examining quality exploring key features support important aspects such an evaluation. Objective The primary aim this study was describe range app stores intended for patients secondary were assess quality, BCTs, potential. Methods systematic review undertaken. Apple App Store Google Play searched a 2-step search strategy, terms relevant discipline. Strict inclusion exclusion criteria applied: had self-contained (or stand-alone) without requirement conjunction with partner wearable device or another plugin. Included coded BCTs Behavior Change Technique Taxonomy version 1. assessed Rating Scale, Scale app’s behavior. Results In total, 1240 screened, 35 included. Of these apps, 22 (63%) available on both platforms. 24 (69%) general focus (eg, not condition-specific), remaining 11 (31%) being more specific knee rehabilitation pelvic floor training). mean score (Mobile Scale) 3.7 (SD 0.4) 5 (range 2.8-4.5). number identified per 8.5 3.6). most frequently included instruction how perform (n=32), action planning (n=30), self-monitoring (n=28). (App 3.1) 21 3-15). Conclusions received from physiotherapist variable quality. Although they contain some varied widely across apps. International Registered Report Identifier (IRRID) RR2-10.2196/29047

Language: Английский

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Supervised or Home-Based? Exploring the Best Exercise Approach for Knee Osteoarthritis Management: A Systematic Review and Meta-Analysis

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(2), P. 525 - 525

Published: Jan. 15, 2025

Background/Objective: Knee osteoarthritis (OA) is a common and debilitating condition affecting older adults, often progressing to advanced stages requiring total joint replacement. Exercise therapy widely recognized as the first-line approach for prevention initial management of OA. This systematic review assessed effectiveness home-based exercises (HBEs) compared supervised in alleviating pain reducing disability among patients with knee Methods: A search PubMed, Cochrane Library, ScienceDirect identified randomized controlled trials (RCTs) published between January 2001 October 2024. Methodological quality was evaluated using Physiotherapy Evidence Database (PEDro) scale, meta-analysis conducted quantify efficacy these interventions. Results: Ten RCTs involving 917 were included, ranging moderate high methodological (PEDro score: 6.3 ± 1.2). Intervention durations ranged from 4 12 weeks. Both HBEs found be effective, but demonstrated statistically significant improvements (SMD = −0.45 [95% CI −0.79; −0.11], p 0.015) −0.28 −0.42; −0.14], < 0.001) HBEs. Conclusions: Despite superiority over HBEs, considering cost-effectiveness ease implementation we developed recommendations create hybrid rehabilitation program that combines both approaches maximize clinical outcomes.

Language: Английский

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Innovations in surgical management of frail elderly adults: an overview of current guidance and recent advances

Surgery (Oxford), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Impact of Virtual Reality, Augmented Reality, and Sensor Technology in Knee Osteoarthritis Rehabilitation: A Systematic Review

Cureus, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 14, 2025

Knee osteoarthritis (KOA) is a progressive degenerative joint disorder that significantly impacts mobility, pain levels, and overall quality of life. Conventional rehabilitation methods, while effective, often suffer from limitations related to patient adherence, accessibility, cost. This systematic review examines the role virtual reality (VR), augmented (AR), sensor-based technologies in KOA rehabilitation, evaluating their effectiveness reduction, functional improvement, engagement. A comprehensive literature search identified four randomized controlled trials (RCTs) comprising 405 participants, with an average Physiotherapy Evidence Database (PEDro) score 6/10, indicating moderate high methodological quality. Findings suggest VR AR interventions enhance adherence engagement, systems provide real-time biofeedback, enabling personalized therapeutic adjustments. These demonstrated significant improvements management, muscle strength, mobility. However, challenges such as costs, limited absence standardized treatment protocols remain barriers widespread clinical adoption. Further research should focus on long-term efficacy, cost-effectiveness, integration these innovations into routine practice.

Language: Английский

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The effects of digital health on exercise adherence and intervention outcomes in older adults with knee diseases: A systematic review

Annals of Physical and Rehabilitation Medicine, Journal Year: 2025, Volume and Issue: 68(5), P. 101952 - 101952

Published: March 12, 2025

Language: Английский

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