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Head Movements

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Controlling a robotic arm for functional tasks using a wireless head-joystick: A case study of a child with congenital absence of upper and lower limbs.

PloS one
Children with movement impairments needing assistive devices for activities of daily living often require novel methods for controlling these devices. Body-machine interfaces, which rely on body movements, are particularly well-suited for children as...

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

Computational and mathematical methods in medicine
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research fi...

Automated detection of the head-twitch response using wavelet scalograms and a deep convolutional neural network.

Scientific reports
Hallucinogens induce the head-twitch response (HTR), a rapid reciprocal head movement, in mice. Although head twitches are usually identified by direct observation, they can also be assessed using a head-mounted magnet and a magnetometer. Procedures ...

DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection.

Communications biology
In general, animal behavior can be described as the neuronal-driven sequence of reoccurring postures through time. Most of the available current technologies focus on offline pose estimation with high spatiotemporal resolution. However, to correlate ...

Saliency Prediction on Omnidirectional Image With Generative Adversarial Imitation Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
When watching omnidirectional images (ODIs), subjects can access different viewports by moving their heads. Therefore, it is necessary to predict subjects' head fixations on ODIs. Inspired by generative adversarial imitation learning (GAIL), this pap...

Prediction of Head Movement in 360-Degree Videos Using Attention Model.

Sensors (Basel, Switzerland)
In this paper, we propose a prediction algorithm, the combination of Long Short-Term Memory (LSTM) and attention model, based on machine learning models to predict the vision coordinates when watching 360-degree videos in a Virtual Reality (VR) or Au...

Effect of head motion-induced artefacts on the reliability of deep learning-based whole-brain segmentation.

Scientific reports
Due to their robustness and speed, recently developed deep learning-based methods have the potential to provide a faster and hence more scalable alternative to more conventional neuroimaging analysis pipelines in terms of whole-brain segmentation bas...

Viewport-Based CNN: A Multi-Task Approach for Assessing 360° Video Quality.

IEEE transactions on pattern analysis and machine intelligence
For 360° video, the existing visual quality assessment (VQA) approaches are designed based on either the whole frames or the cropped patches, ignoring the fact that subjects can only access viewports. When watching 360° video, subjects select viewpor...

A Driver Gaze Estimation Method Based on Deep Learning.

Sensors (Basel, Switzerland)
Car crashes are among the top ten leading causes of death; they could mainly be attributed to distracted drivers. An advanced driver-assistance technique (ADAT) is a procedure that can notify the driver about a dangerous scenario, reduce traffic cras...

Gaze Point Tracking Based on a Robotic Body-Head-Eye Coordination Method.

Sensors (Basel, Switzerland)
When the magnitude of a gaze is too large, human beings change the orientation of their head or body to assist their eyes in tracking targets because saccade alone is insufficient to keep a target at the center region of the retina. To make a robot g...