Appliance Signature Extraction

2019 ◽  
pp. 45-78
Author(s):  
Hui Liu
Keyword(s):  
Signature Extraction

scholarly journals An Electro-Oculogram Based Vision System for Grasp Assistive Devices—A Proof of Concept Study

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4515
Author(s):  
Rinku Roy ◽  
Manjunatha Mahadevappa ◽  
Kianoush Nazarpour
Keyword(s):  
Vision System ◽  
Extraction Procedure ◽  
Orientation Angle ◽  
Object Orientation ◽  
Assistive Devices ◽  
Assistive Device ◽  
Vision Systems ◽  
Signature Extraction ◽  
Voluntary Muscle ◽  
Als Patients

Humans typically fixate on objects before moving their arm to grasp the object. Patients with ALS disorder can also select the object with their intact eye movement, but are unable to move their limb due to the loss of voluntary muscle control. Though several research works have already achieved success in generating the correct grasp type from their brain measurement, we are still searching for fine controll over an object with a grasp assistive device (orthosis/exoskeleton/robotic arm). Object orientation and object width are two important parameters for controlling the wrist angle and the grasp aperture of the assistive device to replicate a human-like stable grasp. Vision systems are already evolved to measure the geometrical attributes of the object to control the grasp with a prosthetic hand. However, most of the existing vision systems are integrated with electromyography and require some amount of voluntary muscle movement to control the vision system. Due to that reason, those systems are not beneficial for the users with brain-controlled assistive devices. Here, we implemented a vision system which can be controlled through the human gaze. We measured the vertical and horizontal electrooculogram signals and controlled the pan and tilt of a cap-mounted webcam to keep the object of interest in focus and at the centre of the picture. A simple ‘signature’ extraction procedure was also utilized to reduce the algorithmic complexity and system storage capacity. The developed device has been tested with ten healthy participants. We approximated the object orientation and the size of the object and determined an appropriate wrist orientation angle and the grasp aperture size within 22 ms. The combined accuracy exceeded 75%. The integration of the proposed system with the brain-controlled grasp assistive device and increasing the number of grasps can offer more natural manoeuvring in grasp for ALS patients.

An Efficient Worm Defense System Based Signature Extraction

2009 ◽  
Vol 5 (1) ◽  
pp. 23-23
Author(s):  
Hao Tu ◽  
Zhitang Li ◽  
Bin Liu ◽  
Yejiang Zhang
Keyword(s):  
Defense System ◽  
Signature Extraction ◽  
Worm Defense

Event signature extraction and traffic modeling in WSNs

2013 ◽  
Vol 55 (4) ◽  
pp. 513-523 ◽  
Author(s):  
Gergely Öllös ◽  
Rolland Vida
Keyword(s):  
Traffic Modeling ◽  
Signature Extraction

Buried target signature extraction from ground-penetrating radar signal: measurements and simulations

2005 ◽  
Vol 4 (1) ◽  
pp. 31-38 ◽  
Author(s):  
Idesbald van den Bosch ◽  
Sébastien Lambot ◽  
Pascal Druyts ◽  
Isabelle Huynen ◽  
Marc Acheroy
Keyword(s):  
Ground Penetrating Radar ◽  
Radar Signal ◽  
Signature Extraction ◽  
Ground Penetrating
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