AIMC Topic: Intention

Clear Filters Showing 91 to 100 of 172 articles

Predicting Human Intention-Behavior Through EEG Signal Analysis Using Multi-Scale CNN.

IEEE/ACM transactions on computational biology and bioinformatics
At present, the application of Electroencephalogram (EEG) signal classification to human intention-behavior prediction has become a hot topic in the brain computer interface (BCI) research field. In recent studies, the introduction of convolutional n...

Radiation Oncologists' Perceptions of Adopting an Artificial Intelligence-Assisted Contouring Technology: Model Development and Questionnaire Study.

Journal of medical Internet research
BACKGROUND: An artificial intelligence (AI)-assisted contouring system benefits radiation oncologists by saving time and improving treatment accuracy. Yet, there is much hope and fear surrounding such technologies, and this fear can manifest as resis...

Optimizing Motor Intention Detection With Deep Learning: Towards Management of Intraoperative Awareness.

IEEE transactions on bio-medical engineering
OBJECTIVE: This article shows the interest in deep learning techniques to detect motor imagery (MI) from raw electroencephalographic (EEG) signals when a functional electrical stimulation is added or not. Impacts of electrode montages and bandwidth a...

Intentions with actions: The role of intentionality attribution on the vicarious sense of agency in Human-Robot interaction.

Quarterly journal of experimental psychology (2006)
Sense of Agency (SoA) is the feeling of control over one's actions and their consequences. In social contexts, people experience a "vicarious" SoA over other humans' actions; however, the phenomenon disappears when the other agent is a computer. This...

Toward a Unified Theory of Customer Continuance Model for Financial Technology Chatbots.

Sensors (Basel, Switzerland)
With the popularity of financial technology (fintech) chatbots equipped with artificial intelligence, understanding the user's response mechanism can help bankers formulate precise marketing strategies, which is a crucial issue in the social science ...

Multimodal Sensor Motion Intention Recognition Based on Three-Dimensional Convolutional Neural Network Algorithm.

Computational intelligence and neuroscience
With the development of microelectronic technology and computer systems, the research of motion intention recognition based on multimodal sensors has attracted the attention of the academic community. Deep learning and other nonlinear neural network ...

An integrated deep learning model for motor intention recognition of multi-class EEG Signals in upper limb amputees.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recognition of motor intention based on electroencephalogram (EEG) signals has attracted considerable research interest in the field of pattern recognition due to its notable application of non-muscular communication and con...

Human Motion Intent Description Based on Bumpless Switching Mechanism for Rehabilitation Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper aims to improve the performance of an electromyography (EMG) decoder based on a switching mechanism in controlling a rehabilitation robot for assisting human-robot cooperation arm movements. For a complex arm movement, the major difficulty...

Older adults' experiences with and perceptions of the use of socially assistive robots in aged care: A systematic review of quantitative evidence.

Archives of gerontology and geriatrics
BACKGROUND: Socially assistive robots (SARs) are created to meet challenges of the global increase of older adults. SARs are autonomous embodied technologies, equipped with auditory and visual faculties, enabling them to interact with users while per...

Variable Admittance Control Based on Human-Robot Collaboration Observer Using Frequency Analysis for Sensitive and Safe Interaction.

Sensors (Basel, Switzerland)
A collaborative robot should be sensitive to the user intention while maintaining safe interaction during tasks such as hand guiding. Observers based on the discrete Fourier transform have been studied to distinguish between the low-frequency motion ...