Artificial Intelligence and Its Revolutionary Role in Physical and Mental Rehabilitation: A Review of Recent Advancements

BioMed Research International, Journal Year: 2024, Volume and Issue: 2024(1)

Published: Jan. 1, 2024

The integration of artificial intelligence (AI) technologies into physical and mental rehabilitation has the potential to significantly transform these fields. AI innovations, including machine learning algorithms, natural language processing, computer vision, offer occupational therapists advanced tools improve care quality. These facilitate more precise assessments, development tailored intervention plans, efficient treatment delivery, enhanced outcome evaluation. This review explores across various aspects rehabilitation, providing a thorough examination recent advancements current applications. It highlights how applications, such as virtual reality, learning, robotics, are shaping future recovery in therapy.

Language: Английский

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Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression

Frontiers in Rehabilitation Sciences, Journal Year: 2025, Volume and Issue: 6

Published: Feb. 19, 2025

The assessment of limb joint torque is essential for understanding musculoskeletal system dynamics. Yet, the lack direct muscle strength measurement techniques has prompted previous research to deploy estimation using machine learning models. These models often suffer from reduced accuracies due presence redundant and irrelevant information within rapidly expanding complex biomedical datasets as well suboptimal hyperparameters configurations. This study utilized a random forest regression (RFR) model estimate elbow flexion mechanomyography (MMG) signals recorded during electrical stimulation biceps brachii (BB) in 36 right-handed healthy subjects. Given significance both feature engineering hyperparameter tuning optimizing RFR performance, this proposes hybrid method leveraging General Learning Equilibrium Optimizer (GLEO) identify most informative MMG features tune hyperparameters. performance GLEO-coupled with was compared standard (EO) other state-of-the-art algorithms physical physiological function biological signals. Experimental results showed that selected tuned demonstrated significant improvement root mean square error (RMSE), coefficient determination (R2) slope values improving 0.1330 0.1174, 0.7228 0.7853 0.6946 0.7414, respectively test dataset. Convergence analysis further revealed GLEO algorithm exhibited superior capability EO. underscores potential approach selecting highly advancements are evaluating represent advancement biomechanics research.

Language: Английский

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From screens to scenes: A survey of embodied AI in healthcare

Information Fusion, Journal Year: 2025, Volume and Issue: unknown, P. 103033 - 103033

Published: Feb. 1, 2025

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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Harnessing Generative Artificial Intelligence for Exercise and Training Prescription: Applications and Implications in Sports and Physical Activity—A Systematic Literature Review

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3497 - 3497

Published: March 22, 2025

Regular physical activity plays a critical role in health promotion and athletic performance, necessitating personalized exercise training prescriptions. While traditional methods rely on expert assessments, artificial intelligence (AI), particularly generative AI models such as ChatGPT Google Gemini, has emerged potential tool for enhancing personalization scalability recommendations. However, the applicability, reliability, adaptability of AI-generated prescriptions remain underexplored. A comprehensive search was performed using UnoPerTutto metadatabase, identifying 2891 records. After duplicate removal (1619 records) screening, 61 full-text reports were assessed eligibility, resulting inclusion 10 studies. The studies varied methodology, including qualitative mixed-methods approaches, quasi-experimental designs, randomized controlled trial (RCT). ChatGPT-4, ChatGPT-3.5, Gemini evaluated across different contexts, strength training, rehabilitation, cardiovascular exercise, general fitness programs. Findings indicate that programs generally adhere to established guidelines but often lack specificity, progression, real-time physiological feedback. recommendations found emphasize safety broad making them useful guidance less effective high-performance training. GPT-4 demonstrated superior performance generating structured resistance compared older models, yet limitations individualization contextual adaptation persisted. appraisal METRICS checklist revealed inconsistencies study quality, regarding prompt model transparency, evaluation frameworks. holds promise democratizing access prescriptions, its remains complementary rather than substitutive guidance. Future research should prioritize adaptability, integration with monitoring, improved AI-human collaboration enhance precision effectiveness AI-driven

Language: Английский

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Artificial Intelligence in Medical Education and Mentoring in Rehabilitation Medicine

American Journal of Physical Medicine & Rehabilitation, Journal Year: 2024, Volume and Issue: 103(11), P. 1039 - 1044

Published: July 15, 2024

Artificial intelligence emerges as a transformative force, offering novel solutions to enhance medical education and mentorship in the specialty of physical medicine rehabilitation. is technology that being adopted nearly every industry. In medicine, use artificial growing. may also assist with some challenges mentorship, including limited availability experienced mentors, logistical difficulties time geography are constraints traditional mentorship. this commentary, we discuss various models mentoring, expert systems, conversational agents, hybrid models. These enable tailored guidance, broaden outreach within rehabilitation community, support continuous learning development. Balancing intelligence's technical advantages essential human elements while addressing ethical considerations, integration into presents paradigm shift toward more accessible, responsive, enriched experience medicine.

Language: Английский

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Impact of Artificial Intelligence on Healthcare and Its Challenges in the MENA Region

Published: Jan. 1, 2025

Language: Английский

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Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery

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

Published: March 1, 2025

Language: Английский

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Functional and Motoric Outcome of AI-Assisted Stroke Rehabilitation: A Meta-analysis of Randomized Controlled Trials

Brain Disorders, Journal Year: 2025, Volume and Issue: unknown, P. 100224 - 100224

Published: April 1, 2025

Language: Английский

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Myofascial Pain Syndrome: A Comprehensive Systematic Literature Review on Diagnostic Approaches, Treatment Modalities and Recent Advances

Indian Journal of Physical Medicine and Rehabilitation, Journal Year: 2025, Volume and Issue: 35(2), P. 59 - 70

Published: April 30, 2025

Abstract Myofascial pain syndrome (MPS) is a type of chronic that can occur in muscles, fascia or other soft tissues and often accompanied by emotional dysfunctions. It characterised myofascial trigger points (MTrPs), which are hyperirritable painful spots taut bands skeletal linked to musculoskeletal disorders. MPS affects many individuals, but its prevalence challenging determine due the lack clearly defined diagnostic criteria. Some studies indicate more common among young middle-aged individuals who visit clinics, occurring 30%–46% cases. This article reviews recent advancements management fibromyalgia, focusing on available therapeutic options for MPS. Several databases were evaluated consider pathophysiology, diagnosis

Language: Английский

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