Tactile Pattern Recognition and Body Loci

Perception ◽  
1973 ◽  
Vol 2 (3) ◽  
pp. 333-336 ◽  
Author(s):  
L A Scadden
Keyword(s):  
Pattern Recognition ◽  
Recognition Accuracy ◽  
Vibratory Stimulation ◽  
Television Camera ◽  
Body Regions ◽  
Substitution System ◽  
Tactile Pattern ◽  
Three Body ◽  
Previous Learning ◽  
Body Locus

Experimentation was conducted to compare tactile pattern recognition on three body loci—back, abdomen, and inner thigh. Five blind subjects, experienced users of a tactile vision substitution system which displays images picked up by a television camera through patterns of vibratory stimulation on the skin, were asked to identify letter images displayed on three body regions. Though the previous experience had been limited to stimulation on the back, recognition accuracy and latency were significantly better on the abdomen. The results indicate that immediate transfer of previous learning occurs when body locus of stimulation is shifted, and further suggest that neural networks for tactile pattern recognition do not include specific peripheral neural receptors.

scholarly journals Age differences in tactile pattern recognition at the fingertip

2017 ◽  
Author(s):  
Hélène Manning ◽  
FranÇois Tremblay
Keyword(s):  
Pattern Recognition ◽  
Spatial Resolution ◽  
Age Differences ◽  
Recognition Accuracy ◽  
Young Group ◽  
Letter Recognition ◽  
Substantial Portion ◽  
Tactile Pattern ◽  
Central Level ◽  
Afferent Innervation

Young (21-26 years, n=20) and Old (55-86 years, n=25) participants were tested for their ability to recognize raised letters (6-mm high, 1-mm relief) by touch. Spatial resolution thresholds were also measured with grating domes to derive an index of the degree of afferent innervation at the fingertip. Letter recognition in the young group was very consistent and highly accurate (mean, 86% correct), contrasting with the performance of the old group, which was more variable and comparatively low in accuracy (mean, 53% correct). In both groups, spatial resolution thresholds accounted for a substantial portion of the variance in the performance, suggesting a strong link between age-dependant variations in tactile innervation and recognition accuracy. The patterns of errors in the old group showed that an inability to encode internal elements specific to certain letters was at the source of most confusion among letters. Whether this inability reflected only deficient peripheral encoding mechanisms or some other alterations at the central level is discussed.

scholarly journals Tactile pattern recognition by graphic display: Importance of 3-D information for haptic perception of familiar objects

1993 ◽  
Vol 53 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Yutaka Shimizu ◽  
Shinya Saida ◽  
Hiroshi Shimura
Keyword(s):  
Pattern Recognition ◽  
Haptic Perception ◽  
Graphic Display ◽  
Tactile Pattern ◽  
Familiar Objects

The Distribution of Glycogen in the Tissues of Siboglinum Atlanticum [Pogonophora]

1973 ◽  
Vol 53 (3) ◽  
pp. 665-671 ◽  
Author(s):  
Eve C. Southward
Keyword(s):  
Electron Microscopy ◽  
Light And Electron Microscopy ◽  
Epidermal Cells ◽  
Peritoneal Cells ◽  
Body Regions ◽  
Three Body

Light and electron microscopy showed the same distribution of glycogen. The peritoneal cells contain large amounts in all three body regions investigated: the forepart, metameric region and postannular region. Glycogen is present in most epidermal cells and is very abundant in some, particularly in the postannular region, but the cells which secrete the chitinous and proteinaceous components of the tube are almost devoid of glycogen.

scholarly journals Impact of Synaptic Device Variations on Pattern Recognition Accuracy in a Hardware Neural Network

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungho Kim ◽  
Meehyun Lim ◽  
Yeamin Kim ◽  
Hee-Dong Kim ◽  
Sung-Jin Choi
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Recognition Accuracy ◽  
Hardware Neural Network

scholarly journals Human Body Mixed Motion Pattern Recognition Method Based on Multi-Source Feature Parameter Fusion

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 537 ◽  
Author(s):  
Jiyuan Song ◽  
Aibin Zhu ◽  
Yao Tu ◽  
Yingxu Wang ◽  
Muhammad Affan Arif ◽  
...  
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Lower Extremity ◽  
Human Body ◽  
Recognition Accuracy ◽  
Screening Method ◽  
Motion Pattern ◽  
Recognition Method ◽  
Motion State ◽  
Motion Mode

Aiming at the requirement of rapid recognition of the wearer’s gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multi-source feature parameters. We obtain information on human lower extremity acceleration and plantar analyze the relationship between these parameters and gait cycle studying the motion state recognition method based on feature evaluation and neural network. Based on the actual requirements of exoskeleton per use, 15 common gait patterns were determined. Using this, the studies were carried out on the time domain, frequency domain, and energy feature extraction of multi-source lower extremity motion information. The distance-based feature screening method was used to extract the optimal features. Finally, based on the multi-layer BP (back propagation) neural network, a nonlinear mapping model between feature quantity and motion state was established. The experimental results showed that the recognition accuracy in single motion mode can reach up to 98.28%, while the recognition accuracy of the two groups of experiments in mixed motion mode was found to be 92.7% and 97.4%, respectively. The feasibility and effectiveness of the model were verified.

scholarly journals Impact of RTN on Pattern Recognition Accuracy of RRAM-Based Synaptic Neural Network

2018 ◽  
Vol 39 (11) ◽  
pp. 1652-1655 ◽  
Author(s):  
Zheng Chai ◽  
Pedro Freitas ◽  
Weidong Zhang ◽  
Firas Hatem ◽  
Jian Fu Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Recognition Accuracy

Spike-based tactile pattern recognition using an extreme learning machine

2015 ◽  
Author(s):  
Mahdi Rasouli ◽  
Chen Yi ◽  
Arindam Basu ◽  
Nitish V. Thakor ◽  
Sunil Kukreja
Keyword(s):  
Pattern Recognition ◽  
Extreme Learning Machine ◽  
Tactile Pattern ◽  
Learning Machine

scholarly journals Rapid body color brightening is associated with exposure to a stressor in an Anolis lizard

2017 ◽  
Vol 95 (3) ◽  
pp. 213-219 ◽  
Author(s):  
Jane F.F. Boyer ◽  
Lindsey Swierk
Keyword(s):  
Color Change ◽  
Light Exposure ◽  
Natural Populations ◽  
Body Color ◽  
Anolis Lizard ◽  
Body Coloration ◽  
Body Regions ◽  
Before And After ◽  
Three Body ◽  
Typical Skin

Many species use color change to optimize body coloration to changing environmental conditions, and drivers of rapid color change in natural populations are numerous and poorly understood. We examined factors influencing body coloration in the Water Anole (Anolis aquaticus Taylor, 1956), a lizard possessing color-changing stripes along the length of its body. We quantified the color of three body regions (the eye stripe, lateral stripe, and dorsum) before and after exposure to a mild stressor (handling and restraint). Based on current understanding of the genus Anolis Daudin, 1802, we hypothesized that exposure to a stressor would generate genus-typical skin darkening (i.e., increased melanism). Contrary to expectations, stress consistently brightened body coloration: eye and lateral stripes transitioned from brown to pale blue and green and the dorsum became lighter brown. Sex, size, and body temperature did not correlate with any aspect of body coloration, and a laboratory experiment confirmed that light exposure did not drive brightening. We propose that color change may serve to reduce conspicuousness through disruptive camouflage; lizards tended to display brighter stripes on mottled green–brown substrates. Together, these results improve our understanding of Anolis color change diversity and emphasize the need for a broader interpretation of the mechanism and functions of color change across taxa.

scholarly journals A Dynamic Interval-Valued Intuitionistic Fuzzy Sets Applied to Pattern Recognition

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Zhenhua Zhang ◽  
Min Wang ◽  
Yong Hu ◽  
Jingyu Yang ◽  
Youpei Ye ◽  
...  
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Medical Diagnosis ◽  
Recognition Accuracy ◽  
Intuitionistic Fuzzy Sets ◽  
Distance Measures ◽  
Intuitionistic Fuzzy ◽  
Simulation Results ◽  
Interval Valued

We present dynamic interval-valued intuitionistic fuzzy sets (DIVIFS), which can improve the recognition accuracy when they are applied to pattern recognition. By analyzing the degree of hesitancy, we propose some DIVIFS models from intuitionistic fuzzy sets (IFS) and interval-valued IFS (IVIFS). And then we present a novel ranking condition on the distance of IFS and IVIFS and introduce some distance measures of DIVIFS satisfying the ranking condition. Finally, a pattern recognition example applied to medical diagnosis decision making is given to demonstrate the application of DIVIFS and its distances. The simulation results show that the DIVIFS method is more comprehensive and flexible than the IFS method and the IVIFS method.

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