AIMC Topic: Psychomotor Performance
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When performing actions with robots, attribution of intentionality affects the sense of joint agency.
Science robotics
Jun 26, 2024
Sense of joint agency (SoJA) is the sense of control experienced by humans when acting with others to bring about changes in the shared environment. SoJA is proposed to arise from the sensorimotor predictive processes underlying action control and mo...
The independence of impairments in proprioception and visuomotor adaptation after stroke.
Journal of neuroengineering and rehabilitation
May 18, 2024
BACKGROUND: Proprioceptive impairments are common after stroke and are associated with worse motor recovery and poor rehabilitation outcomes. Motor learning may also be an important factor in motor recovery, and some evidence in healthy adults sugges...
Multi-Task Heterogeneous Ensemble Learning-Based Cross-Subject EEG Classification Under Stroke Patients.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 6, 2024
Robot-assisted motor training is applied for neurorehabilitation in stroke patients, using motor imagery (MI) as a representative paradigm of brain-computer interfaces to offer real-life assistance to individuals facing movement challenges. However, ...
Visual feedbacks influence short-term learning of torque versus motion profile with robotic guidance among young adults.
Human movement science
May 1, 2024
Robotic assistance can improve the learning of complex motor skills. However, the assistance designed and used up to now mainly guides motor commands for trajectory learning, not dynamics learning. The present study explored how a complex motor skill...
Convolutional neural networks reveal properties of reach-to-grasp encoding in posterior parietal cortex.
Computers in biology and medicine
Feb 19, 2024
Deep neural networks (DNNs) are widely adopted to decode motor states from both non-invasively and invasively recorded neural signals, e.g., for realizing brain-computer interfaces. However, the neurophysiological interpretation of how DNNs make the ...
Estimating vigilance from the pre-work shift sleep using an under-mattress sleep sensor.
Journal of sleep research
Jan 7, 2024
Predicting vigilance impairment in high-risk shift work occupations is critical to help to reduce workplace errors and accidents. Current methods rely on multi-night, often manually entered, sleep data. This study developed a machine learning model f...
Evaluation of different feedback designs for target guidance in human controlled robotic cranes: A comparison between high and low performance groups.
Applied ergonomics
Dec 20, 2023
Labour shortages and costly operator training are driving the need for digital on-board robotic crane operator support in forestry and construction. This simulator study investigated the effects of sonification (auditory, pitch/loudness) and continuo...
Eye-Tracking in Physical Human-Robot Interaction: Mental Workload and Performance Prediction.
Human factors
Oct 4, 2023
BACKGROUND: In Physical Human-Robot Interaction (pHRI), the need to learn the robot's motor-control dynamics is associated with increased cognitive load. Eye-tracking metrics can help understand the dynamics of fluctuating mental workload over the co...
Bimanual Motor Strategies and Handedness Role in Human-Robot Haptic Interaction.
IEEE transactions on haptics
Jun 20, 2023
Bimanual object manipulation involves using both hands to interact with objects in the environment, and the process requires the central nervous system to process sensory feedback and translate it into motor commands. Although there have been signifi...
Robot-assisted investigation of sensorimotor control in Parkinson's disease.
Scientific reports
Mar 23, 2023
Sensorimotor control (SMC) is a complex function that involves sensory, cognitive, and motor systems working together to plan, update and execute voluntary movements. Any abnormality in these systems could lead to deficits in SMC, which would negativ...
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