AIMC Topic: Feedback, Psychological
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A new ML-based approach to enhance student engagement in online environment.
PloS one
Nov 10, 2021
The educational research is increasingly emphasizing the potential of student engagement and its impact on performance, retention and persistence. This construct has emerged as an important paradigm in the higher education field for many decades. How...
Augmented Performance Feedback during Robotic Gait Therapy Results in Moderate Intensity Cardiovascular Exercise in Subacute Stroke.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Mar 31, 2020
BACKGROUND: Low cardiovascular fitness is common poststroke. Conventional subacute stroke rehabilitation does not meet Australian National Stroke Guidelines for cardiovascular exercise, particularly in mobility-dependent patients. Walking robotics ca...
Prospective Studies
Female
Aged
Male
Humans
Mobility Limitation
Feedback, Psychological
Augmented Reality
Stroke
Gait
Exercise Therapy
Exercise Tolerance
Patient Satisfaction
Health Status
Middle Aged
Cardiorespiratory Fitness
Recovery of Function
Time Factors
Stroke Rehabilitation
Robotics
Treatment Outcome
Oxygen Consumption
Feedback delays can enhance anticipatory synchronization in human-machine interaction.
PloS one
Aug 22, 2019
Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has...
Design feasibility of an automated, machine-learning based feedback system for motivational interviewing.
Psychotherapy (Chicago, Ill.)
Apr 8, 2019
Direct observation of psychotherapy and providing performance-based feedback is the gold-standard approach for training psychotherapists. At present, this requires experts and training human coding teams, which is slow, expensive, and labor intensive...
Learning mechanisms in cue reweighting.
Cognition
Mar 28, 2019
Feedback has been shown to be effective in shifting attention across perceptual cues to a phonological contrast in speech perception (Francis, Baldwin & Nusbaum, 2000). However, the learning mechanisms behind this process remain obscure. We compare t...
Human-agent co-adaptation using error-related potentials.
Journal of neural engineering
Sep 11, 2018
OBJECTIVE: Error-related potentials (ErrP) have been proposed as an intuitive feedback signal decoded from the ongoing electroencephalogram (EEG) of a human observer for improving human-robot interaction (HRI). While recent demonstrations of this app...
Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.
Scientific reports
Dec 14, 2017
Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, ...
Robot Training With Vector Fields Based on Stroke Survivors' Individual Movement Statistics.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 16, 2017
The wide variation in upper extremity motor impairments among stroke survivors necessitates more intelligent methods of customized therapy. However, current strategies for characterizing individual motor impairments are limited by the use of traditio...
Semisupervised category learning facilitates the development of automaticity.
Attention, perception & psychophysics
Jan 1, 2019
In the human category of learning, learning is studied in a supervised, an unsupervised, or a semisupervised way. The rare human semisupervised category of learning studies all focus on early learning. However, the impact of the semisupervised catego...
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