AIMC Topic: Cognition
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Quantifying changes over 1 year in motor and cognitive skill after transient ischemic attack (TIA) using robotics.
Scientific reports
Aug 23, 2021
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 ...
The Humanoid Robot Sil-Bot in a Cognitive Training Program for Community-Dwelling Elderly People with Mild Cognitive Impairment during the COVID-19 Pandemic: A Randomized Controlled Trial.
International journal of environmental research and public health
Aug 3, 2021
BACKGROUND: Mild cognitive impairment (MCI) is a stage preceding dementia, and early intervention is critical. This study investigated whether multi-domain cognitive training programs, especially robot-assisted training, conducted 12 times, twice a w...
Beyond motor recovery after stroke: The role of hand robotic rehabilitation plus virtual reality in improving cognitive function.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jul 31, 2021
Robot-assisted hand training adopting end-effector devices results in an additional reduction of motor impairment in comparison to usual care alone in different stages of stroke recovery. These devices often allow the patient to perform practical, at...
Design of a Robotic Coach for Motor, Social and Cognitive Skills Training Toward Applications With ASD Children.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 1, 2021
Socially assistive robots may help the treatment of autism spectrum disorder(ASD), through games using dyadic interactions to train social skills. Existing systems are mainly based on simplified protocols which qualitatively evaluate subject performa...
Biological constraints on neural network models of cognitive function.
Nature reviews. Neuroscience
Jun 28, 2021
Neural network models are potential tools for improving our understanding of complex brain functions. To address this goal, these models need to be neurobiologically realistic. However, although neural networks have advanced dramatically in recent ye...
A Knowledge-Based Cognitive Architecture Supported by Machine Learning Algorithms for Interpretable Monitoring of Large-Scale Satellite Networks.
Sensors (Basel, Switzerland)
Jun 22, 2021
Cyber-physical systems such as satellite telecommunications networks generate vast amounts of data and currently, very crude data processing is used to extract salient information. Only a small subset of data is used reactively by operators for troub...
Machine learning-based analysis of operator pupillary response to assess cognitive workload in clinical ultrasound imaging.
Computers in biology and medicine
Jun 20, 2021
INTRODUCTION: Pupillometry, the measurement of eye pupil diameter, is a well-established and objective modality correlated with cognitive workload. In this paper, we analyse the pupillary response of ultrasound imaging operators to assess their cogni...
Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD.
Journal of healthcare engineering
Jun 4, 2021
Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify the corresponding chronic diseases, it can effectively reduce the labor cost, improve the accuracy of ...
Biomarker-Informed Machine Learning Model of Cognitive Fatigue from a Heart Rate Response Perspective.
Sensors (Basel, Switzerland)
Jun 2, 2021
Cognitive fatigue is a psychological state characterised by feelings of tiredness and impaired cognitive functioning arising from high cognitive demands. This paper examines the recent research progress on the assessment of cognitive fatigue and prov...
Application of deep learning to understand resilience to Alzheimer's disease pathology.
Brain pathology (Zurich, Switzerland)
May 19, 2021
People who have Alzheimer's disease neuropathologic change (ADNC) typically associated with dementia but not the associated cognitive decline can be considered to be "resilient" to the effects of ADNC. We have previously reported lower neocortical le...
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