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Gestures

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Improving the Accuracy of Spiking Neural Networks for Radar Gesture Recognition Through Preprocessing.

IEEE transactions on neural networks and learning systems
Event-based neural networks are currently being explored as efficient solutions for performing AI tasks at the extreme edge. To fully exploit their potential, event-based neural networks coupled to adequate preprocessing must be investigated. Within ...

A Deep Q-Network based hand gesture recognition system for control of robotic platforms.

Scientific reports
Hand gesture recognition (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) has been investigated for human-machine applications in the last few years. The information obtained from the HGR systems has the pot...

Motor differences in autism during a human-robot imitative gesturing task.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Difficulty with imitative gesturing is frequently observed as a clinical feature of autism. Current practices for assessment of imitative gesturing ability-behavioral observation and parent report-do not allow precise measurement of speci...

Hand Gesture Interface for Robot Path Definition in Collaborative Applications: Implementation and Comparative Study.

Sensors (Basel, Switzerland)
The article explores the possibilities of using hand gestures as a control interface for robotic systems in a collaborative workspace. The development of hand gesture control interfaces has become increasingly important in everyday life as well as pr...

Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks.

Sensors (Basel, Switzerland)
In recent years, hand gesture recognition (HGR) technologies that use electromyography (EMG) signals have been of considerable interest in developing human-machine interfaces. Most state-of-the-art HGR approaches are based mainly on supervised machin...

Using Gesture Recognition for AGV Control: Preliminary Research.

Sensors (Basel, Switzerland)
In this paper, we present our investigation of the 2D Hand Gesture Recognition (HGR) which may be suitable for the control of the Automated Guided Vehicle (AGV). In real conditions, we deal with, among others, a complex background, changing lighting ...

An Extended Spatial Transformer Convolutional Neural Network for Gesture Recognition and Self-Calibration Based on Sparse sEMG Electrodes.

IEEE transactions on biomedical circuits and systems
sEMG-based gesture recognition is widely applied in human-machine interaction system by its unique advantages. However, the accuracy of recognition drops significantly as electrodes shift. Besides, in applications such as VR, virtual hands should be ...

sEMG-Based Hand Gesture Recognition Using Binarized Neural Network.

Sensors (Basel, Switzerland)
Recently, human-machine interfaces (HMI) that make life convenient have been studied in many fields. In particular, a hand gesture recognition (HGR) system, which can be implemented as a wearable system, has the advantage that users can easily and in...

On lightmyography based muscle-machine interfaces for the efficient decoding of human gestures and forces.

Scientific reports
Conventional muscle-machine interfaces like Electromyography (EMG), have significant drawbacks, such as crosstalk, a non-linear relationship between the signal and the corresponding motion, and increased signal processing requirements. In this work, ...

Deep Learning Framework for Controlling Work Sequence in Collaborative Human-Robot Assembly Processes.

Sensors (Basel, Switzerland)
The human-robot collaboration (HRC) solutions presented so far have the disadvantage that the interaction between humans and robots is based on the human's state or on specific gestures purposely performed by the human, thus increasing the time requi...