Robustness of Using Dynamic Motions and Template Matching to the Limb Position Effect in Myoelectric Classification

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Sungtae Shin ◽  
Reza Tafreshi ◽  
Reza Langari
Keyword(s):  
Template Matching ◽  
Human Subjects ◽  
Position Effect ◽  
Correlation Coefficients ◽  
Skin Condition ◽  
Prosthetic Devices ◽  
Linear Discriminant ◽  
Limb Position ◽  
External Conditions ◽  
Dynamic Time

Myoelectric classification has been widely studied for controlling prosthetic devices and human computer interface (HCI). However, it is still not robust due to external conditions: limb position changes, electrode shifts, and skin condition changes. These issues compromise the reliability of pattern recognition techniques in myoelectric systems. In order to increase the reliability in the limb position effect when a limb position is changed from the position in which the system is trained, this paper proposes a myoelectric system using dynamic motions. Dynamic time warping (DTW) technique was used for the alignment of two different time-length motions, and correlation coefficients were then calculated as a similarity metric to classify dynamic motions. On the other hand, Fisher's linear discriminant analysis was applied on static motions for the purpose of dimensionality reduction and Naïve Bayesian classifier for classifying the motions. To estimate the robustness to the limb position effect, static and dynamic motions were collected at four different limb positions from eight human subjects. The statistical analysis, t-test (p < 0.05), showed that, for all subjects, dynamic motions were more robust to the limb position effect than static motions when training and validation sets were extracted from different limb positions with the best classification accuracy of 97.59% and 3.54% standard deviation (SD) for dynamic motions compared with 71.85% with 12.62% SD for static motions.

scholarly journals An Adaptive Multi-Modal Control Strategy to Attenuate the Limb Position Effect in Myoelectric Pattern Recognition

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7404
Author(s):  
Veronika Spieker ◽  
Amartya Ganguly ◽  
Sami Haddadin ◽  
Cristina Piazza
Keyword(s):  
Pattern Recognition ◽  
Position Effect ◽  
Adaptive Method ◽  
Completion Rate ◽  
Hand Motion ◽  
Limb Position ◽  
Upper Limb Prostheses ◽  
New Information ◽  
Classical Pattern ◽  
External Loads

Over the last few decades, pattern recognition algorithms have shown promising results in the field of upper limb prostheses myoelectric control and are now gradually being incorporated in commercial devices. A widely used approach is based on a classifier which assigns a specific input value to a selected hand motion. While this method guarantees good performance and robustness within each class, it still shows limitations in adapting to different conditions encountered in real-world applications, such as changes in limb position or external loads. This paper proposes an adaptive method based on a pattern recognition classifier that takes advantage of an augmented dataset—i.e., representing variations in limb position or external loads—to selectively adapt to underrepresented variations. The proposed method was evaluated using a series of target achievement control tests with ten able-bodied volunteers. Results indicated a higher median completion rate >3.33% for the adapted algorithm compared to a classical pattern recognition classifier used as a baseline model. Subject-specific performance showed the potential for improved control after adaptation and a ≤13% completion rate; and in many instances, the adapted points were able to provide new information within classes. These preliminary results show the potential of the proposed method and encourage further development.

Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices

2013 ◽  
pp. 322-427
Keyword(s):  
External Validation ◽  
Correlation Coefficients ◽  
Classification Models ◽  
Training Set ◽  
Linear Discriminant ◽  
Oecd Principles ◽  
Qsar Models ◽  
Validation Set ◽  
Global Accuracy

In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 for C. All individual models were validated and fulfilled by OECD principles. A brief analysis of AD for the training set of 478 compounds and the new active compounds included in the re-training was carried out. Various assembled multiclassifier systems contained eighteen models using different selection criterions were obtained, which provide possibility of select the best strategy for particular problem. The various assembled multiclassifier systems also estimated the potency of active identified compounds. Eighteen validated potency models by OECD principles were used.

An Improved Method In Speech Signal Input Representation Based On DTW Technique For NN Speech Recognition System

2012 ◽  
Author(s):  
Rubita Sudirman ◽  
Sh. Hussain Salleh ◽  
Shaharuddin Salleh
Keyword(s):  
Neural Network ◽  
Speech Recognition ◽  
Conjugate Gradient ◽  
Template Matching ◽  
Dynamic Time Warping ◽  
Gradient Descent ◽  
Reference Frames ◽  
Time Warping ◽  
Dynamic Time ◽  
Quasi Newton

Kertas kerja ini membentangkan pemprosesan semula ciri pertuturan pemalar Pengekodan Ramalan Linear (LPC) bagi menyediakan template rujukan yang boleh diharapkan untuk set perkataan yang hendak dicam menggunakan rangkaian neural buatan. Kertas kerja ini juga mencadangkan penggunaan cirian kenyaringan yang ditakrifkan dari data pertuturan sebagai satu lagi ciri input. Algoritma Warping Masa Dinamik (DTW) menjadi asas kepada algoritma baru yang dibangunkan, ia dipanggil sebagai DTW padanan bingkai (DTW–FF). Algoritma ini direka bentuk untuk melakukan padanan bingkai bagi pemprosesan semula input LPC. Ia bertujuan untuk menyamakan bilangan bingkai input dalam set ujian dengan set rujukan. Pernormalan bingkaian ini adalah diperlukan oleh rangkaian neural yang direka untuk membanding data yang harus mempunyai kepanjangan yang sama, sedangkan perkataan yang sama dituturkan dengan kepanjangan yang berbeza–beza. Dengan melakukan padanan bingkai, bingkai input dan rujukan boleh diubahsuai supaya bilangan bingkaian sama seperti bingkaian rujukan. Satu lagi misi kertas kerja ini ialah mentakrif dan menggunakan cirian kenyaringan menggunakan algoritma penapis harmonik. Selepas kenyaringan ditakrif dan pemalar LPC dinormalkan kepada bilangan bingkaian dikehendaki, pengecaman pertuturan menggunakan rangkaian neural dilakukan. Keputusan yang baik diperoleh sehingga mencapai ketepatan setinggi 98% menggunakan kombinasi cirian DTW–FF dan cirian kenyaringan. Di akhir kertas kerja ini, perbandingan kadar convergence antara Conjugate gradient descent (CGD), Quasi–Newton, dan Steepest Gradient Descent (SGD) dilakukan untuk mendapatkan arah carian titik global yang optimal. Keputusan menunjukkan CGD memberikan nilai titik global yang paling optimal dibandingkan dengan Quasi–Newton dan SGD. Kata kunci: Warping masa dinamik, pernormalan masa, rangkaian neural, pengecaman pertuturan, conjugate gradient descent A pre–processing of linear predictive coefficient (LPC) features for preparation of reliable reference templates for the set of words to be recognized using the artificial neural network is presented in this paper. The paper also proposes the use of pitch feature derived from the recorded speech data as another input feature. The Dynamic Time Warping algorithm (DTW) is the back–bone of the newly developed algorithm called DTW fixing frame algorithm (DTW–FF) which is designed to perform template matching for the input preprocessing. The purpose of the new algorithm is to align the input frames in the test set to the template frames in the reference set. This frame normalization is required since NN is designed to compare data of the same length, however same speech varies in their length most of the time. By doing frame fixing, the input frames and the reference frames are adjusted to the same number of frames according to the reference frames. Another task of the study is to extract pitch features using the Harmonic Filter algorithm. After pitch extraction and linear predictive coefficient (LPC) features fixed to a desired number of frames, speech recognition using neural network can be performed and results showed a very promising solution. Result showed that as high as 98% recognition can be achieved using combination of two features mentioned above. At the end of the paper, a convergence comparison between conjugate gradient descent (CGD), Quasi–Newton, and steepest gradient descent (SGD) search direction is performed and results show that the CGD outperformed the Newton and SGD. Key words: Dynamic time warping, time normalization, neural network, speech recognition, conjugate gradient descent

Resolving the Limb Position Effect in Myoelectric Pattern Recognition

2011 ◽  
Vol 19 (6) ◽  
pp. 644-651 ◽  
Author(s):  
A. Fougner ◽  
E. Scheme ◽  
A. D. C. Chan ◽  
K. Englehart ◽  
Ø. Stavdahl
Keyword(s):  
Pattern Recognition ◽  
Position Effect ◽  
Limb Position

Neural networks as a unifying learning model for random normal form games

2011 ◽  
Vol 19 (6) ◽  
pp. 383-408 ◽  
Author(s):  
Leonidas Spiliopoulos
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Normal Form ◽  
Human Behavior ◽  
Nash Equilibria ◽  
Human Subjects ◽  
Correlation Coefficients ◽  
Normal Form Games ◽  
The Neural Network ◽  
Iterated Dominance

This article models the learning process of a population of randomly rematched tabula rasa neural network agents playing randomly generated 3 × 3 normal form games of all strategic types. Evidence was found of the endogenous emergence of a similarity measure of games based on the number and types of Nash equilibria, and of heuristics that have been found effective in describing human behavior in experimental one-shot games. The neural network agents were found to approximate experimental human behavior very well across various dimensions such as convergence to Nash equilibria, equilibrium selection, and adherence to principles of dominance and iterated dominance. This is corroborated by evidence from five studies of experimental one-shot games, because the Spearman correlation coefficients of the probability distribution over the neural networks’ and human subjects’ actions ranged from 0.49 to 0.89.

scholarly journals IMPLEMETASI OFFLINE PENGENALAN SISTEM ISYARAT BAHASA INDONESIA MENGGUNAKAN METODE DYNAMIC TIME WARPING PADA PERANGKAT ANDROID

2015 ◽  
Vol 6 (2) ◽  
pp. 391
Author(s):  
Mohammad Iqbal ◽  
Endang Supriyati ◽  
Tri Listyorini
Keyword(s):  
Time Series ◽  
Template Matching ◽  
Dynamic Time Warping ◽  
Time Warping ◽  
Dynamic Time ◽  
Bahasa Indonesia ◽  
Data Template

ABSTRAK Algoritma Dynamic Time Warping (DTW) digunakan secara luas untuk berbagai penelitian, salah satunya di bidang bahasa isyarat. DTW adalah algoritma pencocokan pola (template matching) untuk mengukur kemiripan dua data sekuensial (time series) temporal yang berbeda waktu dan kecepatan. Pada penelitian ini disajikan implementasi algoritma DTW untuk pengenalan bahasa isyarat Indonesia (Sistem Isyarat Bahasa Indonesia SIBI) secara offline. Dataset yang digunakan dalam penelitian ini sebanyak 900 data untuk dengan jumlah kelas 50 kata isyarat, yaitu dengan rincian untuk masing-masing kelas adalah 3 data sebagai data template dan 15 data sebagai data testing. Hasil pengujian menunjukkan bahwa tingkat pengenalan atau nilai accuracy adalah 89,73%. Waktu rata-rata yang dibutuhkan adalah 654.59 milidetik untuk proses pengenalan satu data testing dengan menggunakan template sebanyak 3 data per kelas atau total template 150 data. Kata kunci: pengenalan, offline, SIBI, bahasa isyarat Indonesia, android.

scholarly journals Multivariate statistical methods for characterization of waste water quality

2021 ◽  
Vol 9 (3) ◽  
Author(s):  
Darja Kavšek ◽  
Darinka Brodnjak Vončina
Keyword(s):  
Water Quality ◽  
Statistical Methods ◽  
Oxygen Demand ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Waste Waters ◽  
Prevention Measures ◽  
Mutual Correlation ◽  
Seasonal Behavior ◽  
Linear Discriminant

The aim of this work is focused on water quality classification of the waste waters and evaluation of pollution by the monitoring measurements during period 2006-2008. Environmental monitoring was performed in the region of Trbovlje, Slovenia, with two sampling sites and 15 chemical and physicochemical water quality parameters (pH, temperature, suspended solids, settling matter, chemical oxygen demand, biochemical oxygen demand, AOX (adsorbable organic halogens), total phosphorus, ammonium, nitrite, sulphate, chloride, fluoride, sulphide and mineral oil content) monitored in monthly periods (total of 60 objects x 15 variables). For handling the results different chemometric methods were employed, such as basic statistical methods for the determination of mean and median values, standard deviations, minimal and maximal values of measured parameters and their mutual correlation coefficients, the principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA). Monitoring of general pollution of waste waters and following measuring parameters which are above permitted concentration level can be used for searching of pollution source and for planning prevention measures from pollution, as well. The study allows drawing new information from the data sets such as patterns of similarity between sampling locations, sources of pollution in the environment, seasonal behavior of chemical contents and time trends.

scholarly journals Use of Dynamic Time Warping for Object Shape Classification through Signature

1970 ◽  
Vol 6 (1) ◽  
pp. 33-49 ◽  
Author(s):  
KC Santosh
Keyword(s):  
Template Matching ◽  
Dynamic Time Warping ◽  
Center Of Gravity ◽  
Shape Classification ◽  
Time Warping ◽  
Similarity Matching ◽  
Object Shape ◽  
Boundary Points ◽  
Engineering And Technology ◽  
Dynamic Time

This paper expresses an application of similarity matching of the signatures through DTW.Fundamental aspect of classification is template matching. The classification is robust tonoise, scaling, and rotation. Feature includes radius plus angle along the boundary points withrespect to center of gravity. The classification automatically and confidently discloses theshape of every object at once throughout page from top to bottom. The paper expresses itspromising results within an average of a few seconds (cheaper classification) for an object. Aseries of tests is done with all possible configurations of geometrical shapes.Keywords: Signature; Dynamic Time Warping; Uniform ScalingDOI: 10.3126/kuset.v6i1.3308Kathmandu University Journal of Science, Engineering and Technology Vol.6(1) 2010, pp33-49

Calibration of a new ear oximeter in humans during exposure to centrifugation

1978 ◽  
Vol 44 (3) ◽  
pp. 483-487 ◽  
Author(s):  
E. L. Besch ◽  
F. W. Baumgardner ◽  
R. R. Burton ◽  
K. K. Gillingham ◽  
R. F. McPherson ◽  
...  
Keyword(s):  
Base Excess ◽  
Human Subjects ◽  
Arterial Oxygen Saturation ◽  
Correlation Coefficients ◽  
Arterial Oxygen ◽  
Hypoxic Exposure ◽  
Similar Data ◽  
Gas Analyzer ◽  
Arterial Blood ◽  
Blood Gas Analyzer

An optoelectronic ear oximeter (Hewlett-Packard, model 47201A) was evaluated as a noninvasive method for determining arterial oxygen saturation (SaO2) in human subjects during exposure to various levels of accelerative forces. This physiological calibration involved exposing five subjects, while breathing air and wearing the ear oximeter for 60 s to each of three levels of accelerative forces (3, 5, and 7 G); arterial blood samples were withdrawn concurrently. SaO2 was calculated indirectly from the oxygen tensions (PaO2) measured from the sampled arterial blood with a blood gas analyzer and corrected for pH and base excess. These data were compared, as were similar data taken from the same subjects breathing three different hypoxic gas mixtures while resitng at earth's gravity (1 G). Regression analyses of these data for both experimental groups (a, G exposure, or b, hypoxic exposure), comparing the ear-oximeter SaO2 with the calculated SaO2, showed the ear oximeter to be accurate with correlation coefficients of 0.95 and 0.98, respectively.

A fast template matching method based on improved ring projection transformation and local dynamic time warping

Optik ◽  
2020 ◽  
Vol 216 ◽  
pp. 164954
Author(s):  
Yulin Wang ◽  
Wen Liu ◽  
Fei Li ◽  
Heng Li ◽  
Wenbin Zha ◽  
...  
Keyword(s):  
Template Matching ◽  
Dynamic Time Warping ◽  
Local Dynamic ◽  
Time Warping ◽  
Matching Method ◽  
Dynamic Time ◽  
Projection Transformation
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