AIMC Topic: Muscle Strength

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Machine learning approach to classifying declines of physical function and muscle strength associated with cognitive function in older women: gait characteristics based on three speeds.

Frontiers in public health
BACKGROUND: The aging process is associated with a cognitive and physical declines that affects neuromotor control, memory, executive functions, and motor abilities. Previous studies have made efforts to find biomarkers, utilizing complex factors suc...

Combining Sound and Deep Neural Networks for the Measurement of Jump Height in Sports Science.

Sensors (Basel, Switzerland)
Jump height tests are employed to measure lower-limb muscle power of athletic and non-athletic populations. The most popular instruments for this purpose are jump mats and, in recent years, smartphone apps, which compute jump height through the manua...

Performance of different machine learning algorithms in identifying undiagnosed diabetes based on nonlaboratory parameters and the influence of muscle strength: A cross-sectional study.

Journal of diabetes investigation
AIMS/INTRODUCTION: Machine learning algorithms based on the artificial neural network (ANN), support vector machine, naive Bayesian or logistic regression model are commonly used to identify diabetes. This study investigated which approach performed ...

PedBotLab: A Novel Video Game-Based Robotic Ankle Platform Created for Therapeutic Exercise for Children With Neurological Impairments.

Physical & occupational therapy in pediatrics
AIMS: Assess the potential benefits of using PedBotLab, a clinic based robotic ankle platform with integrated video game software, to improve ankle active and passive range of motion, strength, selective motor control, gait efficiency, and balance.

Prediction model of subacromial pain syndrome in assembly workers using shoulder range of motion and muscle strength based on support vector machine.

Ergonomics
Subacromial pain syndrome (SAPS) is the most common upper-extremity musculoskeletal problem among workers. In this study, a machine learning model was built to predict and classify the presence or absence of SAPS in assembly workers with shoulder joi...

Effects of robotic rehabilitation using the Erigo device on patients with neurological injury: a systematic review and meta-analysis of randomized clinical trials.

Disability and rehabilitation. Assistive technology
OBJECTIVE: To systematically review the effects of robotic rehabilitation with the Erigo device on patients with neurological injury on safety, spasticity, muscle strength, functionality, gait/balance, and changes in the level of consciousness.

Biomechanics of Volleyball Players' Run-Up and Take-Off Link under Deep Learning.

Computational intelligence and neuroscience
In volleyball, the correct approach and start (including the number of steps and stride speed) are a prerequisite for all technical movements to attack. It can not only improve the horizontal speed of the athlete, but also properly convert the total ...

Effectiveness of individualized training based on force-velocity profiling on physical function in older men.

Scandinavian journal of medicine & science in sports
The study aimed to investigate the effectiveness of an individualized power training program based on force-velocity (FV) profiling on physical function, muscle morphology, and neuromuscular adaptations in older men. Forty-nine healthy men (68 ± 5 ye...

Effects of Blood Flow Restriction Therapy for Muscular Strength, Hypertrophy, and Endurance in Healthy and Special Populations: A Systematic Review and Meta-Analysis.

Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine
OBJECTIVES: Blood flow restriction (BFR) training is an increasingly applied tool with potential benefits in muscular hypertrophy, strength, and endurance. This study investigates the effectiveness of BFR training relative to other forms of training ...