AIMC Topic: Motor Skills

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Towards functional robotic training: motor learning of dynamic tasks is enhanced by haptic rendering but hampered by arm weight support.

Journal of neuroengineering and rehabilitation
BACKGROUND: Current robot-aided training allows for high-intensity training but might hamper the transfer of learned skills to real daily tasks. Many of these tasks, e.g., carrying a cup of coffee, require manipulating objects with complex dynamics. ...

Automated recognition of objects and types of forceps in surgical images using deep learning.

Scientific reports
Analysis of operative data with convolutional neural networks (CNNs) is expected to improve the knowledge and professional skills of surgeons. Identification of objects in videos recorded during surgery can be used for surgical skill assessment and s...

Emerging of new bioartificial corticospinal motor synergies using a robotic additional thumb.

Scientific reports
It is likely that when using an artificially augmented hand with six fingers, the natural five plus a robotic one, corticospinal motor synergies controlling grasping actions might be different. However, no direct neurophysiological evidence for this ...

A cerebellar-based solution to the nondeterministic time delay problem in robotic control.

Science robotics
The presence of computation and transmission-variable time delays within a robotic control loop is a major cause of instability, hindering safe human-robot interaction (HRI) under these circumstances. Classical control theory has been adapted to coun...

Quantifying changes over 1 year in motor and cognitive skill after transient ischemic attack (TIA) using robotics.

Scientific reports
Recent work has highlighted that people who have had TIA may have abnormal motor and cognitive function. We aimed to quantify deficits in a cohort of individuals who had TIA and measured changes in their abilities to perform behavioural tasks over 1 ...

Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.

Developmental medicine and child neurology
AIM: To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66.

Assessing Children's Fine Motor Skills With Sensor-Augmented Toys: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Approximately 5%-10% of elementary school children show delayed development of fine motor skills. To address these problems, detection is required. Current assessment tools are time-consuming, require a trained supervisor, and are not mot...

A Deep Learning Approach for Table Tennis Forehand Stroke Evaluation System Using an IMU Sensor.

Computational intelligence and neuroscience
Psychological and behavioral evidence suggests that home sports activity reduces negative moods and anxiety during lockdown days of COVID-19. Low-cost, nonintrusive, and privacy-preserving smart virtual-coach Table Tennis training assistance could he...

Automation of training and testing motor and related tasks in pre-clinical behavioural and rehabilitative neuroscience.

Experimental neurology
Testing and training animals in motor and related tasks is a cornerstone of pre-clinical behavioural and rehabilitative neuroscience. Yet manually testing and training animals in these tasks is time consuming and analyses are often subjective. Conseq...

Brain-computer interface robotics for hand rehabilitation after stroke: a systematic review.

Journal of neuroengineering and rehabilitation
BACKGROUND: Hand rehabilitation is core to helping stroke survivors regain activities of daily living. Recent studies have suggested that the use of electroencephalography-based brain-computer interfaces (BCI) can promote this process. Here, we repor...