Organisation of left and right hand movement in a prehension task: A longitudinal study from 20 to 32 weeks

2000 ◽  
Vol 5 (4) ◽  
pp. 351-362 ◽  
Author(s):  
F. Morange-Majoux ◽  
A. Peze ◽  
H. Bloch
Keyword(s):  
Longitudinal Study ◽  
Hand Movement ◽  
Right Hand ◽  
Left And Right

scholarly journals Left and Right Hand Movements EEG Signals Classification Using Wavelet Transform and Probabilistic Neural Network

2015 ◽  
Vol 5 (1) ◽  
pp. 92 ◽  
Author(s):  
A. B. M. Aowlad Hossain ◽  
Md. Wasiur Rahman ◽  
Manjurul Ahsan Riheen
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Probabilistic Neural Network ◽  
Hand Movement ◽  
Hand Movements ◽  
Discrete Wavelet ◽  
Eeg Signals ◽  
Beta Band ◽  
Right Hand ◽  
Left And Right

Electroencephalogram (EEG) signals have great importance in the area of brain-computer interface (BCI) which has diverse applications ranging from medicine to entertainment. BCI acquires brain signals, extracts informative features and generates control signals from the knowledge of these features for functioning of external devices. The objective of this work is twofold. Firstly, to extract suitable features related to hand movements and secondly, to discriminate the left and right hand movements signals finding effective classifier. This work is a continuation of our previous study where beta band was found compatible for hand movement analysis. The discrete wavelet transform (DWT) has been used to separate beta band of the EEG signal in order to extract features.  The performance of a probabilistic neural network (PNN) is investigated to find better classifier of left and right hand movements EEG signals and compared with classical back propagation based neural network. The obtained results shows that PNN (99.1%) has better classification rate than the BP (88.9%). The results of this study are expected to be helpful in brain computer interfacing for hand movements related bio-rehabilitation applications.

Left Hand and Right Hand Throwing Mechanism Patterns Classification

2013 ◽  
Vol 61 (2) ◽  
Author(s):  
Ching Yee Yong ◽  
Rubita Sudirman ◽  
Nasrul Humaimi Mahmood ◽  
Kim Mey Chew
Keyword(s):  
Hand Movement ◽  
Human Motion ◽  
Graphical Form ◽  
Human Hand ◽  
Shoulder Injury ◽  
Hand Motion ◽  
Right Hand ◽  
Left And Right ◽  
2D And 3D

This study investigates and acts as a trial clinical outcome for human hand motion and behaviour analysis. It was analysed and accessed the quality of human motion that can be used to differentiate the left and right hand throwing action patterns and also the effect of throwing distance to shoulder pain. It aims to establish how widespread the quality of life effects of human motion especially hands movement. Gyroscope, accelerometer and compass sensors were used to measure the hand movement for a throwing process. 2D and 3D scatter plotting were proposed to represent data in graphical form. An experiment was set up in a laboratory environment with conjunction of analysing human motion. The instruments demonstrate 2D and 3D scatter plot enable distinguish left and right hand throwing action patterns significantly. Distribution of gyroscope data shows that a throwing mechanism for a greater distance may bring greater probability of shoulder injury.

scholarly journals Automatic Determination of Left- and Right-Hand Bone Age in the First Zurich Longitudinal Study

2010 ◽  
Vol 74 (1) ◽  
pp. 50-55 ◽  
Author(s):  
David D. Martin ◽  
Julia Neuhof ◽  
Oskar G. Jenni ◽  
Michael B. Ranke ◽  
Hans Henrik Thodberg
Keyword(s):  
Longitudinal Study ◽  
Bone Age ◽  
Automatic Determination ◽  
Right Hand ◽  
Left And Right

Visual context differentially mediates left- and right-hand reaching movements

2009 ◽  
Author(s):  
Jos J. Adam ◽  
Susan Hoonhorst ◽  
Rick Muskens ◽  
Jay Pratt ◽  
Martin H. Fischer
Keyword(s):  
Reaching Movements ◽  
Visual Context ◽  
Right Hand ◽  
Left And Right
Sign in / Sign up

Export Citation Format

Share Document