scholarly journals Development of Classification Algorithms for the Detection of Postures Using Non-Marker-Based Motion Capture Systems

2020 ◽  
Vol 10 (11) ◽  
pp. 4028
Author(s):  
Tatiana Klishkovskaia ◽  
Andrey Aksenov ◽  
Aleksandr Sinitca ◽  
Anna Zamansky ◽  
Oleg A. Markelov ◽  
...  
Keyword(s):  
Low Cost ◽  
Total Error ◽  
Rapid Development ◽  
Simple Algorithm ◽  
Classification Algorithms ◽  
Health And Wellbeing ◽  
Cost System ◽  
Two Parameters ◽  
Subject Performance

The rapid development of algorithms for skeletal postural detection with relatively inexpensive contactless systems and cameras opens up the possibility of monitoring and assessing the health and wellbeing of humans. However, the evaluation and confirmation of posture classifications are still needed. The purpose of this study was therefore to develop a simple algorithm for the automatic classification of human posture detection. The most affordable solution for this project was through using a Kinect V2, enabling the identification of 25 joints, so as to record movements and postures for data analysis. A total of 10 subjects volunteered for this study. Three algorithms were developed for the classification of different postures in Matlab. These were based on a total error of vector lengths, a total error of angles, multiplication of these two parameters and the simultaneous analysis of the first and second parameters. A base of 13 exercises was then created to test the recognition of postures by the algorithm and analyze subject performance. The best results for posture classification were shown by the second algorithm, with an accuracy of 94.9%. The average degree of correctness of the exercises among the 10 participants was 94.2% (SD1.8%). It was shown that the proposed algorithms provide the same accuracy as that obtained from machine learning-based algorithms and algorithms with neural networks, but have less computational complexity and do not need resources for training. The algorithms developed and evaluated in this study have demonstrated a reasonable level of accuracy, and could potentially form the basis for developing a low-cost system for the remote monitoring of humans.

scholarly journals Improvement of the Classification Algorithms of Postures for Non-Marker Systems of Human Motion Capture

2018 ◽  
Author(s):  
Tatiana Klishkovskaia ◽  
Andrey Aksenov
Keyword(s):  
Motion Capture ◽  
Remote Monitoring ◽  
Total Error ◽  
Rapid Development ◽  
Human Motion ◽  
Classification Algorithms ◽  
Human Motion Capture ◽  
Two Parameters ◽  
Subject Performance

The rapid development of algorithms for skeleton detection with relatively inexpensive contactless systems and cameras opens the possibility of virtual exercise therapy for patients with different complications. However, evaluation and confirmation of posture classifications is still needed. The purpose of this study was therefore to find the most accurate algorithm for automatic classification of human exercise movement. A Kinect V2 with 25 joints identification was used to record movements for data analysis. A total of 10 subjects volunteered for this study. Four algorithms were tested for the classification of different postures in Matlab. These were based on: total error of vector lengths, total error of angles, multiplication of these two parameters and simultaneous analysis of the first and second parameters. A base of 13 exercises was then created to test the recognition of postures by the algorithm, and to analyse subject performance. The best results for posture classification was shown by the second algorithm with an accuracy of 94.9%. The average correctness of exercises among the 10 participants was 94.2% (SD1.8%). The algorithms tested in this study therefore proved to be effective and could potentially form the basis for developing a system for remote monitoring of rehabilitation involving exercise.

Wavelet-Based Online Evaluation and Classification of Wear State Using Acoustic Emission

2012 ◽  
Author(s):  
Dorra Baccar ◽  
Dirk Söffker
Keyword(s):  
Acoustic Emission ◽  
Low Cost ◽  
Time Frequency ◽  
Online Evaluation ◽  
Cost System ◽  
State Classification ◽  
Online Examination ◽  
Field Programmable ◽  
Short Time

Advanced signal processing approaches such time-frequency analysis are widely used for online evaluation, damage detection, and wear state classification. The idea of this paper is to introduce a new methodology for online examination of wear phenomena in metallic structure by means of acoustic emission (AE), Short-Time Fourier Transform (STFT) and Wavelet Transform (WT). The proposed novel low-cost system is developed for analyzing and monitoring specific signals indicating tribological effects with focus on field programmable gate array (FPGA) implementation of discrete WT (DWT). In addition, experimental results obtained from each approach are given showing the success of the introduced approach.

scholarly journals A Customizable Low-Cost System for Massively Parallel Zebrafish Behavioral Phenotyping

2021 ◽  
Vol 14 ◽  
Author(s):  
William Joo ◽  
Michael D. Vivian ◽  
Brett J. Graham ◽  
Edward R. Soucy ◽  
Summer B. Thyme
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Low Cost ◽  
Rapid Development ◽  
Aquatic Organisms ◽  
Behavioral Screening ◽  
Chemical Screening ◽  
Behavioral Phenotyping ◽  
Stimulus Response ◽  
Cost System

High-throughput behavioral phenotyping is critical to genetic or chemical screening approaches. Zebrafish larvae are amenable to high-throughput behavioral screening because of their rapid development, small size, and conserved vertebrate brain architecture. Existing commercial behavioral phenotyping systems are expensive and not easily modified for new assays. Here, we describe a modular, highly adaptable, and low-cost system. Along with detailed assembly and operation instructions, we provide data acquisition software and a robust, parallel analysis pipeline. We validate our approach by analyzing stimulus response profiles in larval zebrafish, confirming prepulse inhibition phenotypes of two previously isolated mutants, and highlighting best practices for growing larvae prior to behavioral testing. Our new design thus allows rapid construction and streamlined operation of many large-scale behavioral setups with minimal resources and fabrication expertise, with broad applications to other aquatic organisms.

Low-Cost System Handles Patient Phone Calls

2007 ◽  
Vol 40 (11) ◽  
pp. 53
Author(s):  
BRUCE K. DIXON
Keyword(s):  
Low Cost ◽  
Cost System ◽  
Phone Calls

Intelligent, low-cost system for fume control during laser material processing

2005 ◽  
Author(s):  
Ramin Sattari ◽  
Stephan Barcikowski ◽  
Thomas Püster ◽  
Andreas Ostendorf ◽  
Heinz Haferkamp
Keyword(s):  
Material Processing ◽  
Low Cost ◽  
Laser Material Processing ◽  
Laser Material ◽  
Cost System

The Chemistry Of Antibiofilm Phytocompounds.

2020 ◽  
Vol 20 ◽  
Author(s):  
Dibyajit Lahiri ◽  
Moupriya Nag ◽  
Sayantani Garai ◽  
Rina Rani Ray
Keyword(s):  
Antimicrobial Activity ◽  
Antibiotic Resistance ◽  
Antibiotic Therapy ◽  
Antimicrobial Agents ◽  
Chemical Nature ◽  
Rapid Development ◽  
Wide Spread ◽  
Chronic Infections ◽  
Therapeutic Uses

: Phytocompounds are long known for their therapeutic uses due to their competence as antimicrobial agents. The antimicrobial activity of these bioactive compounds manifests their ability as an antibiofilm agent and is thereby proved to be competent to treat the wide spread of biofilm-associated chronic infections. Rapid development of antibiotic resistance in bacteria has made the treatment of these infections almost impossible by conventional antibiotic therapy, which forced in the switch over to the use of phytocompounds. The present overview deals with the classification of the huge array of phytocompounds according to their chemical nature, detection of their target pathogen, and elucidation of their mode of action.

scholarly journals A Multi-Loop Vehicle-Counting Method under Gray Mode and RGB Mode

2021 ◽  
Vol 11 (15) ◽  
pp. 6831
Author(s):  
Yue Chen ◽  
Jian Lu
Keyword(s):  
Intelligent Transportation Systems ◽  
High Efficiency ◽  
Road Traffic ◽  
Low Cost ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Counting Method ◽  
Moving Vehicle ◽  
Available Information

With the rapid development of road traffic, real-time vehicle counting is very important in the construction of intelligent transportation systems (ITSs). Compared with traditional technologies, the video-based method for vehicle counting shows great importance and huge advantages in its low cost, high efficiency, and flexibility. However, many methods find difficulty in balancing the accuracy and complexity of the algorithm. For example, compared with traditional and simple methods, deep learning methods may achieve higher precision, but they also greatly increase the complexity of the algorithm. In addition to that, most of the methods only work under one mode of color, which is a waste of available information. Considering the above, a multi-loop vehicle-counting method under gray mode and RGB mode was proposed in this paper. Under gray and RGB modes, the moving vehicle can be detected more completely; with the help of multiple loops, vehicle counting could better deal with different influencing factors, such as driving behavior, traffic environment, shooting angle, etc. The experimental results show that the proposed method is able to count vehicles with more than 98.5% accuracy while dealing with different road scenes.

scholarly journals Quantification and Classification of Diclofenac Sodium Content in Dispersed Commercially Available Tablets by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

2021 ◽  
Vol 14 (5) ◽  
pp. 440
Author(s):  
Eirini Siozou ◽  
Vasilios Sakkas ◽  
Nikolaos Kourkoumelis
Keyword(s):  
Infrared Spectroscopy ◽  
Low Cost ◽  
Diclofenac Sodium ◽  
Reference Method ◽  
Sodium Content ◽  
Attenuated Total Reflection ◽  
Accuracy And Precision ◽  
Significant Difference ◽  
Ft Ir

A new methodology, based on Fourier transform infrared spectroscopy equipped with an attenuated total reflectance accessory (ATR FT-IR), was developed for the determination of diclofenac sodium (DS) in dispersed commercially available tablets using chemometric tools such as partial least squares (PLS) coupled with discriminant analysis (PLS-DA). The results of PLS-DA depicted a perfect classification of the tablets into three different groups based on their DS concentrations, while the developed model with PLS had a sufficiently low root mean square error (RMSE) for the prediction of the samples’ concentration (~5%) and therefore can be practically used for any tablet with an unknown concentration of DS. Comparison with ultraviolet/visible (UV/Vis) spectrophotometry as the reference method revealed no significant difference between the two methods. The proposed methodology exhibited satisfactory results in terms of both accuracy and precision while being rapid, simple and of low cost.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

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