scholarly journals Non-Linear Template-Based Approach for the Study of Locomotion

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1939
Author(s):  
Tristan Dot ◽  
Flavien Quijoux ◽  
Laurent Oudre ◽  
Aliénor Vienne-Jumeau ◽  
Albane Moreau ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Dynamic Time Warping ◽  
Detection Methods ◽  
Initial Contact ◽  
Time Warping ◽  
Input Signals ◽  
Step Duration ◽  
Non Linear ◽  
Dynamic Time ◽  
Inertial Measurements

The automatic detection of gait events (i.e., Initial Contact (IC) and Final Contact (FC)) is crucial for the characterisation of gait from Inertial Measurements Units. In this article, we present a method for detecting steps (i.e., IC and FC) from signals of gait sequences of individuals recorded with a gyrometer. The proposed approach combines the use of a dictionary of templates and a Dynamic Time Warping (DTW) measure of fit to retrieve these templates into input signals. Several strategies for choosing and learning the adequate templates from annotated data are also described. The method is tested on thirteen healthy subjects and compared to gold standard. Depending of the template choice, the proposed algorithm achieves average errors from 0.01 to 0.03 s for the detection of IC, FC and step duration. Results demonstrate that the use of DTW allows achieving these performances with only one single template. DTW is a convenient tool to perform pattern recognition on gait gyrometer signals. This study paves the way for new step detection methods: it shows that using one single template associated with non-linear deformations may be sufficient to model the gait of healthy subjects.

scholarly journals A Comprehensive Survey on On-line Handwriting Recognition Technology and its Real Application to the Nepalese Natural Handwriting

1970 ◽  
Vol 5 (1) ◽  
pp. 31-55 ◽  
Author(s):  
Santosh KC ◽  
Cholwich Nattee
Keyword(s):  
Dynamic Time Warping ◽  
Feature Vector ◽  
Handwriting Recognition ◽  
Recognition System ◽  
Time Warping ◽  
Real Application ◽  
Non Linear ◽  
Comprehensive Survey ◽  
On Line ◽  
Dynamic Time

Handwriting Recognition Technology has been improving much under the purview of pattern recognition and image processing since a few decades. This paper focuses on the comprehensive survey on on-line handwriting recognition system along with the real application by taking Nepali natural handwriting (a real example of one of the cursive handwritings). The survey mainly includes pre-processing, feature vector and similarity measures in between the non-linear 2D sequences of coordinates, and their effective applications. A very highlighting topic "Dynamic Time Warping Algorithm'' (DTW) is introduced, which has been popular in determining the distance between two non-linear sequences ranging from handwriting to speech recognition. Besides these contemporary research issues/areas, stroke number and order free Nepalese natural handwritten recognition system is presented in the second step. Writing one's own style brings unevenness in writing units, which is the most difficult part to classify. Writing units reveal number, shape, size, order of stroke, and speed in writing. Variation in the number of strokes, their order, shapes and sizes, tilting angles and similarities among characters from one another are the important factors, which are to be considered in classification for Nepali. This paper utilizes structural properties of those alphanumeric characters, which have variable writing units. It uses a string of pen tip's positions and tangent angles of every consecutive point as a feature vector sequence of a stroke. We constructed a prototype recognizer that uses the DTW algorithm to align handwritten strokes with stored strokes' templates and determine their similarity. Separate system is trained for original and preprocessed writing samples and achieved recognition rates of 85.87% and 88.59% respectively. This introduces novel real time handwriting recognition on Nepalese alphanumeric characters, which are independent of number of strokes, as well as their order. Key Words: Handwriting Recognition System; Pre-processing; Feature Vector; Dynamic Time Warping; Agglomerating Hierarchical Clustering; Nepali. DOI: 10.3126/kuset.v5i1.2845 Kathmandu University Journal of Science, Engineering and Technology Vol.5, No.1, January 2009, pp 31-55

scholarly journals Detection of Freezing of Gait Using Template-Matching-Based Approaches

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Cheng Xu ◽  
Jie He ◽  
Xiaotong Zhang ◽  
Cunda Wang ◽  
Shihong Duan
Keyword(s):  
Template Matching ◽  
Dynamic Time Warping ◽  
High Efficiency ◽  
Freezing Of Gait ◽  
Experimental Tests ◽  
High Accuracy ◽  
Detection Methods ◽  
Time Warping ◽  
Experimental Accuracy ◽  
Dynamic Time

Every year, injuries associated with fall incidences cause lots of human suffering and assets loss for Parkinson’s disease (PD) patients. Thereinto, freezing of gait (FOG), which is one of the most common symptoms of PD, is quite responsible for most incidents. Although lots of researches have been done on characterized analysis and detection methods of FOG, large room for improvement still exists in the high accuracy and high efficiency examination of FOG. In view of the above requirements, this paper presents a template-matching-based improved subsequence Dynamic Time Warping (IsDTW) method, and experimental tests were carried out on typical open source datasets. Results show that, compared with traditional template-matching and statistical learning methods, proposed IsDTW not only embodies higher experimental accuracy (92%) but also has a significant runtime efficiency. By contrast, IsDTW is far more available in real-time practice applications.

Multichannel sparse spike deconvolution based on dynamic time warping

2021 ◽  
Author(s):  
Xiaowei Zhao ◽  
Shangxu Wang ◽  
Sanyi Yuan ◽  
Liang Cheng ◽  
Youjun Cai
Keyword(s):  
Dynamic Time Warping ◽  
Time Warping ◽  
Dynamic Time
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