AIMC Topic: Muscle, Skeletal

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Emerging therapeutic strategies in muscular dystrophy: an updated review on pathogenesis and treatment advances.

Molecular biology reports
Muscular dystrophy (MD) comprises a class of genetic conditions characterized by the progressive degeneration and weakness of skeletal muscle. Genetic etiologies differ among the major muscular dystrophies: myotonic dystrophy type 1 (DM1) is linked t...

High-level locomotion intent estimation from electromyography and body posture.

Journal of neural engineering
Once we learn a reliable gait, we no longer have to consciously contract individual muscles to walk, or think about the fine-grained low-level control of our joints. Instead, we mainly make decisions on where we want to end up, at what pace and throu...

Muscle synergy-driven ensemble learning framework for individualized stroke gait rehabilitation.

Scientific reports
This study proposes a novel ensemble machine learning (ML) framework integrating neurophysiological principles from muscle synergy analysis to support clinical decisions in stroke gait rehabilitation. The framework leverages spatial and temporal feat...

Perceived fatigue progression tracking during manual handling tasks using sEMG recordings.

Journal of neuroengineering and rehabilitation
Physical fatigue significantly contributes to work-related musculoskeletal disorders, highlighting the need to understand its effects during manual handling tasks for effective prevention strategies. This study examines the correlation between change...

A graph neural network model for inferring interindividual variation from experimental biological data.

Scientific reports
Interindividual variation in biological responses to physiological stimuli is a widely recognized phenomenon. However, effective computational tools for identifying the individual-specific mechanisms remain limited. We present the bioreaction-variati...

A neural network approach to sarcopenia prediction based on bioelectrical impedance in community-dwelling older adults.

PloS one
This study aimed to apply a neural network to raw bioelectrical impedance analysis data and to test whether sarcopenia could be predicted with high accuracy. The study population comprised 727 community-dwelling older adults aged 65-85 years who part...

Spinal interneuron population dynamics underlying flexible pattern generation.

Nature communications
The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. As the number of identified classes of spinal interneurons constituting the locomotor ...

Evaluation of normalized T1 signal intensity obtained using an automated segmentation model in lower leg MRI as a potential imaging biomarker in Charcot-Marie-Tooth disease type 1 A.

Scientific reports
We evaluated the potential utility of imaging parameters derived by normalizing muscle signal intensity on T1-weighted lower leg MRIs in Charcot-Marie-Tooth disease type 1 A (CMT1A) patients, using a deep learning-based automated muscle segmentation ...

Re-examining the association between region-specific pain recurrence and muscle force strategies in patients with patellofemoral pain via OpenSim and artificial intelligence: a prospective cohort study toward targeted rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: This study utilized artificial intelligence (AI)-based machine learning algorithms, alongside the shapley additive explanations (SHAP) framework, to identify lower-limb muscle force patterns associated with recurrent patellofemoral pain (...

Functional motor mapping of domestic pig lumbar spinal cord using penetrating microelectrodes.

Journal of neuroengineering and rehabilitation
The restoration of standing and walking after spinal cord injury (SCI) remains a top priority for individuals with paraplegia. Despite significant advancements in neuromodulation techniques, challenges such as limited selectivity and inconsistent out...