scholarly journals Feature Extraction from MEMS Accelerometer and Motion Tracking Measurements in Comparison with Smart Bands during Running

Proceedings ◽  
2018 ◽  
Vol 2 (6) ◽  
pp. 197 ◽  
Author(s):  
Andy Stamm ◽  
Ronny Hartanto
Keyword(s):  
Feature Extraction ◽  
Motion Tracking ◽  
Mems Accelerometer

Iris Motion Tracking - Using Feature Extraction by Shape Matching

2011 ◽  
Author(s):  
C. R. Bernadelli ◽  
A. C. P. Veiga ◽  
E. L. Flores ◽  
M. B. Pereira
Keyword(s):  
Feature Extraction ◽  
Motion Tracking ◽  
Shape Matching

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

Physiologic Studies Provide New Perspectives on Early Speech Development

2010 ◽  
Vol 20 (2) ◽  
pp. 29-36
Author(s):  
Erin M. Wilson ◽  
Ignatius S. B. Nip
Keyword(s):  
Motor Control ◽  
Motor Development ◽  
Motion Tracking ◽  
Speech Development ◽  
Speech Motor Control ◽  
Therapeutic Approaches ◽  
Facial Motion ◽  
Disordered Speech ◽  
Speech Motor ◽  
Physiologic Data

Abstract Although certain speech development milestones are readily observable, the developmental course of speech motor control is largely unknown. However, recent advances in facial motion tracking systems have been used to investigate articulator movements in children and the findings from these studies are being used to further our understanding of the physiologic basis of typical and disordered speech development. Physiologic work has revealed that the emergence of speech is highly dependent on the lack of flexibility in the early oromotor system. It also has been determined that the progression of speech motor development is non-linear, a finding that has motivated researchers to investigate how variables such as oromotor control, cognition, and linguistic factors affect speech development in the form of catalysts and constraints. Physiologic data are also being used to determine if non-speech oromotor behaviors play a role in the development of speech. This improved understanding of the physiology underlying speech, as well as the factors influencing its progression, helps inform our understanding of speech motor control in children with disordered speech and provide a framework for theory-driven therapeutic approaches to treatment.

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