scholarly journals Single Trial Discrimination between Right and Left Hand Movement-Related EEG Activity

2004 ◽  
pp. 255-262 ◽  
Author(s):  
Sunyoung Cho ◽  
Jung Ae Kim ◽  
Dong-Uk Hwang ◽  
Seung Kee Han
Keyword(s):  
Hand Movement ◽  
Single Trial ◽  
Eeg Activity ◽  
Left Hand ◽  
Right And Left Hand

EEG efficient classification of imagined right and left hand movement using RBF kernel SVM and the joint CWT_PCA

AI & Society ◽  
2017 ◽  
Vol 33 (4) ◽  
pp. 621-629 ◽  
Author(s):  
Rihab Bousseta ◽  
Salma Tayeb ◽  
Issam El Ouakouak ◽  
Mourad Gharbi ◽  
Fakhita Regragui ◽  
...  
Keyword(s):  
Hand Movement ◽  
Left Hand ◽  
Rbf Kernel ◽  
Right And Left Hand ◽  
Kernel Svm

EEG-based discrimination between imagination of right and left hand movement

1997 ◽  
Vol 103 (6) ◽  
pp. 642-651 ◽  
Author(s):  
G. Pfurtscheller ◽  
Ch. Neuper ◽  
D. Flotzinger ◽  
M. Pregenzer
Keyword(s):  
Hand Movement ◽  
Left Hand ◽  
Right And Left Hand

Regional cerebral blood flow comparison of right and left hand movement

Neurology ◽  
1979 ◽  
Vol 29 (1) ◽  
pp. 21-21 ◽  
Author(s):  
J. H. Halsey ◽  
U. W. Blauenstein ◽  
E. M. Wilson ◽  
E. H. Wills
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Regional Cerebral Blood Flow ◽  
Hand Movement ◽  
Regional Cerebral Blood ◽  
Left Hand ◽  
Right And Left Hand

scholarly journals Towards Development of a 3-State Self-Paced Brain-Computer Interface

2007 ◽  
Vol 2007 ◽  
pp. 1-8 ◽  
Author(s):  
Ali Bashashati ◽  
Rabab K. Ward ◽  
Gary E. Birch
Keyword(s):  
Brain Computer Interface ◽  
False Positive Rate ◽  
Hand Movement ◽  
True Positive Rate ◽  
Computer Interface ◽  
True Positive ◽  
Left Hand ◽  
Positive Rate ◽  
Right And Left Hand ◽  
Ongoing Eeg

Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchronous switch design (LF-ASD) is a 2-state self-paced BCI that detects the presence of a specific finger movement in the ongoing EEG. Recent evaluations of the 2-state LF-ASD show an average true positive rate of 41% at the fixed false positive rate of 1%. This paper proposes two designs for a 3-state self-paced BCI that is capable of handling idle brain state. The two proposed designs aim at detecting right- and left-hand extensions from the ongoing EEG. They are formed of two consecutive detectors. The first detects the presence of a right- or a left-hand movement and the second classifies the detected movement as a right or a left one. In an offline analysis of the EEG data collected from four able-bodied individuals, the 3-state brain-computer interface shows a comparable performance with a 2-state system and significant performance improvement if used as a 2-state BCI, that is, in detecting the presence of a right- or a left-hand movement (regardless of the type of movement). It has an average true positive rate of 37.5% and 42.8% (at false positives rate of 1%) in detecting right- and left-hand extensions, respectively, in the context of a 3-state self-paced BCI and average detection rate of 58.1% (at false positive rate of 1%) in the context of a 2-state self-paced BCI.

scholarly journals Autonomous Surface Vehicle Controlling Menggunakan Kinect untuk Observasi Terumbu Karang

2019 ◽  
Vol 6 (2) ◽  
pp. 85-92
Author(s):  
Khafiddurrohman Agustianto ◽  
Dyah Ayu Dwijayanti
Keyword(s):  
Hand Movement ◽  
Left Hand ◽  
Autonomous Surface Vehicles ◽  
Brushless Motor ◽  
Autonomous Surface Vehicle ◽  
Tracking Process ◽  
Oceanographic Data ◽  
The Right ◽  
Right And Left Hand ◽  
Effect Of Light

Autonomous Surface Vehicles (ASV) is a platform that is capable of recognizing oceanographic data that is moving on the surface of the sea. The ASV is commonly controlled using a remote RC, smartphones, joysticks, and keyboards. The development of control system innovations in the form of NUI, then ASV can be controlled using Kinect by someone without having to touch the remote. The study developed a marker-less ASV control using the Kinect skeleton feature to get the coordinate value to be the angle value of the right and left hand movement in the implemation as the value of the input fuzzy sugeno algorithm, which resulted in PWM speed output value. This marker-less development communicates wirelessly using the Xbee Pro S28 received by the Arduino Mega for communication and processing the running brushless motor and the ASV generates the movement according to the value received. Effect of light on Kinect in the efficient skeleton tracking process in the room maximum 53105 lux, and in the room maximum 201 lux. Object Spacing (Brainware) to read in the tracking process of the Kinect position of the efficient at a height of 120cm, and angle 00. Kinect communication distance with ASV reaches up to 10000cm. The success of a fuzzy calculation with the result of the movement of the ASV robot is 89.9%.

IMPROVEMENT LAYOUT AND ELEMENTS WORK IN ERGONOMIC ASPECTS

2012 ◽  
Vol 2 (2) ◽  
pp. 84-99
Author(s):  
Beci Sariani ◽  
Meizul Zuki ◽  
Yusril Dany
Keyword(s):  
Working Conditions ◽  
Cycle Time ◽  
Completion Time ◽  
Content Creation ◽  
Left Hand ◽  
Total Distance ◽  
Standard Time ◽  
Before And After ◽  
Right And Left Hand

The purpose of this study is to describe layout and elements of the movement labor, determine cake making job completion time before and after repair, complaints of pain workers and recomendation improved layout and elements work in ergonomic aspects. Layout and elements of the cake making job is less visible than ergonomic working conditions with temperatures as high as 290C and 300C, total distance moving much material for the production namely 2407 cm, manufacture molen 180 cm, 2926 cm baking and packaging 626 cm. Percentage of use right and left hand at creation pia cake is 50.11% and 54.4%. Making molen is 100% and 76.69%. Pia cake making is 12.76% and 12.21%. Packaging is 100% and 84.8%. Cycle time, normal time and standard time of content creation, namely 17004.15, 18.534.52 and 25.577.64 seconds (2 basins). Making molen is 560.23, 616.25 and 751.82 seconds (1 basin). Pia cake making is 1.165,45, 1314.63 and 1.603,85 seconds (2 trays), and packaging is 15,40, 16,79 and 23.17 seconds (2 pack). The application of ergonomics : 8 types of grievances felt a bit sick and 1 type of grievances felt sick. Station molen manufacture, workers felt no pain. Baking station pia (sub-stations) only complaint molen rolling on his back felt a little sore. Sub-station charging only 3 workers who feel a little pain complaints and pain. In the sub-station : 6 types pengovenan grievances felt a little sick. The packing station after repairs only felt a little pain in the waist

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