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Psychomotor Performance

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Direct Comparisons of Upper-Limb Motor Learning Performance Among Three Types of Haptic Guidance With Non-Assisted Condition in Spiral Drawing Task.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In robot-assisted rehabilitation, it is unclear which type of haptic guidance is effective for regaining motor function because of the lack of direct comparisons among multiple types of haptic guidance. The objective of this study was to investigate ...

Human manipulation strategy when changing object deformability and task properties.

Scientific reports
Robotic literature widely addresses deformable object manipulation, but few studies analyzed human manipulation accounting for different levels of deformability and task properties. We asked participants to grasp and insert rigid and deformable objec...

Grasp and remember: the impact of human and robotic actions on object preference and memory.

Scientific reports
Goal contagion, the tendency to adopt others' goals, significantly impacts cognitive processes, which gains particular importance in the emerging field of human-robot interactions. The present study explored how observing human versus robotic actions...

Robotic assessment of bilateral and unilateral upper limb functions in adults with cerebral palsy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Children with unilateral cerebral palsy (CP) exhibit motor impairments predominantly on one side of the body, while also having ipsilesional and bilateral impairments. These impairments are known to persist through adulthood, but their ex...

Pupillometry as a biomarker of postural control: Deep-learning models reveal side-specific pupillary responses to increased intensity of balance tasks.

Psychophysiology
Pupillometry has been used in the studies of postural control to assess cognitive load during dual tasks, but its response to increased balance task intensity has not been investigated. Furthermore, it is unknown whether side-specific changes in pupi...

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

Human factors
ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload associated with engaging in various surgical tasks.BackgroundTraditional methods of evaluating mental ...

Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.

Journal of sport & exercise psychology
Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable, it is unclear whether QE can directly predict performance, which has implications for training int...

NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation.

Science robotics
To achieve human-level dexterity, robots must infer spatial awareness from multimodal sensing to reason over contact interactions. During in-hand manipulation of novel objects, such spatial awareness involves estimating the object's pose and shape. T...

Tracking vigilance fluctuations in real-time: a sliding-window heart rate variability-based machine-learning approach.

Sleep
STUDY OBJECTIVES: Heart rate variability (HRV)-based machine learning models hold promise for real-world vigilance evaluation, yet their real-time applicability is limited by lengthy feature extraction times and reliance on subjective benchmarks. Thi...

Visuomotor Navigation for Embodied Robots With Spatial Memory and Semantic Reasoning Cognition.

IEEE transactions on neural networks and learning systems
The fundamental prerequisite for embodied agents to make intelligent decisions lies in autonomous cognition. Typically, agents optimize decision-making by leveraging extensive spatiotemporal information from episodic memory. Concurrently, they utiliz...