AIMC Topic: Cues

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How to make nonhumanoid mobile robots more likable: Employing kinesic courtesy cues to promote appreciation.

Applied ergonomics
Service robots that mimic human social behavior can appear polite. We tested the social and behavioral efficacy and legibility of two kinesic courtesy cues on people's approval of a service robot. In a repeated-measures design, 29 volunteers were ran...

(Not) hearing happiness: Predicting fluctuations in happy mood from acoustic cues using machine learning.

Emotion (Washington, D.C.)
Recent popular claims surrounding virtual assistants suggest that computers will soon be able to hear our emotions. Supporting this possibility, promising work has harnessed big data and emergent technologies to automatically predict stable levels of...

Who is a better teacher for children with autism? Comparison of learning outcomes between robot-based and human-based interventions in gestural production and recognition.

Research in developmental disabilities
BACKGROUND: Individuals with autism spectrum disorder (ASD) tend to show deficits in engaging with humans. Previous findings have shown that robot-based training improves the gestural recognition and production of children with ASD. It is not known w...

Social-cue perception and mentalizing ability following traumatic brain injury: A human-robot interaction study.

Brain injury
PRIMARY OBJECTIVE: Research studies and clinical observations of individuals with traumatic brain injury (TBI) indicate marked deficits in mentalizing-perceiving social information and integrating it into judgements about the affective and mental sta...

The computerized scoring algorithm for the autobiographical memory test: updates and extensions for analyzing memories of English-speaking adults.

Memory (Hove, England)
The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In ...

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks.

Computational intelligence and neuroscience
Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. Th...

Humans, but Not Deep Neural Networks, Often Miss Giant Targets in Scenes.

Current biology : CB
Even with great advances in machine vision, animals are still unmatched in their ability to visually search complex scenes. Animals from bees [1, 2] to birds [3] to humans [4-12] learn about the statistical relations in visual environments to guide a...

Human interaction with robotic systems: performance and workload evaluations.

Ergonomics
We first tested the effect of differing tactile informational forms (i.e. directional cues vs. static cues vs. dynamic cues) on objective performance and perceived workload in a collaborative human-robot task. A second experiment evaluated the influe...

Multiple cues produced by a robotic fish modulate aggressive behaviour in Siamese fighting fishes.

Scientific reports
The use of robotics to establish social interactions between animals and robots, represents an elegant and innovative method to investigate animal behaviour. However, robots are still underused to investigate high complex and flexible behaviours, suc...

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability.

PloS one
Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent's environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past pr...