scholarly journals In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7752
Author(s):  
Jose M. Celaya-Padilla ◽  
Jonathan S. Romero-González ◽  
Carlos E. Galvan-Tejada ◽  
Jorge I. Galvan-Tejada ◽  
Huizilopoztli Luna-García ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Low Cost ◽  
Child Death ◽  
Classification Model ◽  
Selection Strategy ◽  
Drinking And Driving ◽  
Forward Selection ◽  
Vehicle Accidents ◽  
Non Invasive ◽  
Invasive Method

Worldwide, motor vehicle accidents are one of the leading causes of death, with alcohol-related accidents playing a significant role, particularly in child death. Aiming to aid in the prevention of this type of accidents, a novel non-invasive method capable of detecting the presence of alcohol inside a motor vehicle is presented. The proposed methodology uses a series of low-cost alcohol MQ3 sensors located inside the vehicle, whose signals are stored, standardized, time-adjusted, and transformed into 5 s window samples. Statistical features are extracted from each sample and a feature selection strategy is carried out using a genetic algorithm, and a forward selection and backwards elimination methodology. The four features derived from this process were used to construct an SVM classification model that detects presence of alcohol. The experiments yielded 7200 samples, 80% of which were used to train the model. The rest were used to evaluate the performance of the model, which obtained an area under the ROC curve of 0.98 and a sensitivity of 0.979. These results suggest that the proposed methodology can be used to detect the presence of alcohol and enforce prevention actions.

scholarly journals The prototype device for non-invasive diagnosis of arteriovenous fistula condition using machine learning methods

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Marcin Grochowina ◽  
Lucyna Leniowska ◽  
Agnieszka Gala-Błądzińska
Keyword(s):  
Machine Learning ◽  
Arteriovenous Fistula ◽  
Low Cost ◽  
Principal Component ◽  
Special Kind ◽  
Classification Model ◽  
Supervised Machine Learning ◽  
Signal Acquisition ◽  
Non Invasive ◽  
Prototype Device

Abstract Pattern recognition and automatic decision support methods provide significant advantages in the area of health protection. The aim of this work is to develop a low-cost tool for monitoring arteriovenous fistula (AVF) with the use of phono-angiography method. This article presents a developed and diagnostic device that implements classification algorithms to identify 38 patients with end stage renal disease, chronically hemodialysed using an AVF, at risk of vascular access stenosis. We report on the design, fabrication, and preliminary testing of a prototype device for non-invasive diagnosis which is very important for hemodialysed patients. The system includes three sub-modules: AVF signal acquisition, information processing and classification and a unit for presenting results. This is a non-invasive and inexpensive procedure for evaluating the sound pattern of bruit produced by AVF. With a special kind of head which has a greater sensitivity than conventional stethoscope, a sound signal from fistula was recorded. The proces of signal acquisition was performed by a dedicated software, written specifically for the purpose of our study. From the obtained phono-angiogram, 23 features were isolated for vectors used in a decision-making algorithm, including 6 features based on the waveform of time domain, and 17 features based on the frequency spectrum. Final definition of the feature vector composition was obtained by using several selection methods: the feature-class correlation, forward search, Principal Component Analysis and Joined-Pairs method. The supervised machine learning technique was then applied to develop the best classification model.

Spanish version of the Positive Expectancies for Drinking and Driving for Youth

2012 ◽  
Vol 15 (3) ◽  
pp. 1495-1502 ◽  
Author(s):  
José P. Espada ◽  
Kenneth W. Griffin ◽  
José L. Carballo ◽  
Denis M. McCarthy
Keyword(s):  
Psychometric Properties ◽  
Motor Vehicle ◽  
Developed Countries ◽  
Motor Vehicle Accidents ◽  
Spanish Version ◽  
Future Research ◽  
Drinking And Driving ◽  
Effective Prevention ◽  
Vehicle Accidents ◽  
Positive Expectancies

In most developed countries, motor vehicle accidents are a leading cause of death among young people, and a large proportion of motor vehicle accidents are alcohol-related. In Spain there are no currently available instruments for assessing positive expectancies related to drinking and driving behavior. Attempting to modify these expectancies may be an effective prevention approach, so there is a need for a valid and reliable scale to measure the construct. The aims of the present study were to translate, culturally adapt, and examine the psychometric properties of a Spanish-language version of the Positive Expectancies for Drinking and Driving for Youth (PEDD-Y) in a sample of Spanish young adults. A total of 352 college students with drivers licenses were recruited at a university in southeast Spain. We examined the factor structure, psychometric properties (reliability and validity) and temporal stability of the Spanish version of the PEDD-Y among Spanish young adult drivers. Findings indicated that the Spanish version of the PEDD-Y demonstrated satisfactory psychometric properties and was shown to significantly predict lifetime prevalence and future intentions to drink and drive as well as riding with a drunk driver. The Convenience factor performed with the most consistent reliability and predictive validity. Limitations and future research questions are discussed.

scholarly journals Development a low-cost electrical impedance tomography system for non-invasively detecting abnormal in breast tissue - Phantom study-

10.29007/x6vj ◽  
2022 ◽  
Author(s):  
Minh Quan Cao Dinh ◽  
Quoc Tuan Nguyen Diep ◽  
Hoang Nhut Huynh ◽  
Ngoc An Dang Nguyen ◽  
Anh Tu Tran ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Low Cost ◽  
Impedance Tomography ◽  
Non Invasive ◽  
Tomography System ◽  
Tissue Phantom ◽  
Cost System ◽  
Invasive Method ◽  
Breast Tissues

Electrical Impedance Tomography (EIT) is known as non-invasive method to detect and classify the abnormal breast tissues. Reimaging conductivity distribution within an area of the subject reveal abnormal tissues inside that area. In this work, we have created a very low-cost system with a simple 16-electrode phantom for doing research purposes. The EIT data were measured and reconstructed with EIDORS software.

Correção funcional e estética de sequela de fratura fronto-naso-órbito-etmoidal – relato de caso

2021 ◽  
Vol 12 (46) ◽  
pp. 70-75
Author(s):  
Dimas Albertiny Barradas de Sousa Varela ◽  
Priscila Vital Fialho ◽  
Mariana Mendes de Carvalho ◽  
Victor Hugo Moraes Salviano ◽  
Carlos Vinicius Moreira ◽  
...  
Keyword(s):  
Motor Vehicle ◽  
Low Cost ◽  
High Energy ◽  
Facial Trauma ◽  
Imaging Evaluation ◽  
Vehicle Accidents ◽  
Handling Characteristics ◽  
Good Imaging ◽  
Late Treatment ◽  
Type Of Fracture

Fronto-naso-orbito-etmoidal fractures, known as FNOE fractures, are the result of blunt trauma of high energy in the middle and upper third of the face. Presenting an approximate frequency of 5% to 15% of facial trauma in children and adults, respectively, FNOE fractures are found more commonly after motor vehicle accidents, physical aggression, falls or cycling accidents. The diagnosis and treatment of FNOE fractures are difficult to perform and, for this reason, the performance of a thorough clinical examination associated with a good imaging evaluation is of great importance in these traumas, as incorrect diagnosis and inadequate or late treatment generally result in aesthetic and functional. The treatment of this type of fracture must be defined after the identification of the extension, type of fracture, and affected structures in order to restore function and shape of the middle face. This study aimed to report a case of sequelae of FNOE fracture where there were aesthetic and respiratory complaints, treated with coronal access and subsequent reduction of nasal bones fracture and aesthetic correction of the nasal dorsum and glabella with the use of polymethylmethacrylate cement (PMMA). It was concluded that the early diagnosis of FNOE fractures is of great importance to avoid sequelae, with coronal access being a good access option for the surgical correction of these sequelae and the biocompatibility and handling characteristics, as well as the low cost of cement PMMA is a good option for grafting in corrections of craniofacial deformities.

scholarly journals Bovine Breeds Identification by Trichological Analysis

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 761 ◽  
Author(s):  
Felix ◽  
Soares Fioravanti ◽  
Cassandro ◽  
Tormen ◽  
Quadros ◽  
...  
Keyword(s):  
Microsatellite Markers ◽  
Genetic Characterization ◽  
Low Cost ◽  
Cattle Breed ◽  
Statistical Analyses ◽  
Genetic Analyses ◽  
Non Invasive ◽  
Morphometric Analyses ◽  
Invasive Method ◽  
Morphology And Morphometry

This study aimed to identify bovine breeds through trichological morphology and morphometry and to validate this technique by comparing it with genetic characterization. Animals from Caracu, Curraleiro Pé-Duro, Nelore, and Bovino Pantaneiro breeds were studied. Morphological and morphometric analyses of the guard hairs were performed. The cuticular pattern was observed on the shaft and the medulla pattern on the shield of the samples. The cattle genetic characterization was accomplished using microsatellite markers. Statistical analyses were performed using R version 3.2.4 software. Pearson’s correlation test showed a high positive and significant correlation between the matrices generated by trichological and genetic analyses (r = 0,996 and p < 0.001). Trichological analysis is a useful method for cattle breed identification. Its potential for identifying other species of interest for animal production should be studied since it is a simple, low-cost, and non-invasive method.

scholarly journals Raman spectroscopy as a non-invasive diagnostic technique for endometriosis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ugur Parlatan ◽  
Medine Tuna Inanc ◽  
Bahar Yuksel Ozgor ◽  
Engin Oral ◽  
Ercan Bastu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Diagnostic Technique ◽  
Principal Component ◽  
Classification Model ◽  
Support Vector ◽  
Serum Samples ◽  
K Nearest Neighbors ◽  
Non Invasive ◽  
Unseen Data ◽  
Invasive Method

AbstractEndometriosis is a condition in which the endometrium, the layer of tissue that usually covers the inside of the uterus, grows outside the uterus. One of its severe effects is sub-fertility. The exact reason for endometriosis is still unknown and under investigation. Tracking the symptoms is not sufficient for diagnosing the disease. A successful diagnosis can only be made using laparoscopy. During the disease, the amount of some molecules (i.e., proteins, antigens) changes in the blood. Raman spectroscopy provides information about biochemicals without using dyes or external labels. In this study, Raman spectroscopy is used as a non-invasive diagnostic method for endometriosis. The Raman spectra of 94 serum samples acquired from 49 patients and 45 healthy individuals were compared for this study. Principal Component Analysis (PCA), k- Nearest Neighbors (kNN), and Support Vector Machines (SVM) were used in the analysis. According to the results (using 80 measurements for training and 14 measurements for the test set), it was found that kNN-weighted gave the best classification model with sensitivity and specificity values of 80.5% and 89.7%, respectively. Testing the model with unseen data yielded a sensitivity value of 100% and a specificity value of 100%. To the best of our knowledge, this is the first study in which Raman spectroscopy was used in combination with PCA and classification algorithms as a non-invasive method applied on blood sera for the diagnosis of endometriosis.

NON-INVASIVE BLOOD OXYGEN SATURATION MONITORING (SpO2) USING TRANSMITTANCE FOR PULSE OXIMETER

2019 ◽  
Vol 31 (06) ◽  
pp. 1950043
Author(s):  
Anupama Sarkar ◽  
Vineet Sinha ◽  
Sadhana A. Mandlik ◽  
J. Kathirvelan
Keyword(s):  
Embedded System ◽  
Oxygen Saturation ◽  
Low Cost ◽  
Vital Role ◽  
Critical Conditions ◽  
Blood Oxygen Saturation ◽  
Respiratory Problems ◽  
Non Invasive ◽  
Photo Detectors ◽  
Invasive Method

Measuring oxygen saturation of blood (SpO2) clinically plays a vital role in patient’s health monitoring. In fact, monitoring oxygen level is necessary for people having respiratory problems (pulmonary hypertension) and in other critical conditions. The primary motivation of this work is to develop a low cost computer-based oxygen saturation monitoring system using an embedded system along with lab windows CVI platform. The process of calculating the level of oxygen saturation in the blood using non-invasive method is also called as pulse oximetry, which consists of LED and photo detectors, using MSP430FG4618 microcontroller. The MSP430 employed in designing the microcontroller firmware program for digitization and transmission of the data from sensor to the computer. NI-based Lab windows/CVI Platform was developed as a part of this project to receive, plot, save data and determine the accuracy of SpO2 value. In this proposed system, we have achieved the maximum accuracy of 99.49% which is better than the previously developed methods. The proposed system is also designed with the low cost and low power consuming modules.

scholarly journals Enhanced Access to the Health-Related Skin Metabolome by Fast, Reproducible and Non-Invasive WET PREP Sampling

Metabolites ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 415
Author(s):  
Jamie Afghani ◽  
Claudia Huelpuesch ◽  
Philippe Schmitt-Kopplin ◽  
Claudia Traidl-Hoffmann ◽  
Matthias Reiger ◽  
...  
Keyword(s):  
Low Cost ◽  
Sampling Technique ◽  
Ultra Performance Liquid Chromatography ◽  
Reversed Phase ◽  
The Body ◽  
Physical And Mental Health ◽  
Non Invasive ◽  
Health Related ◽  
Invasive Method ◽  
High Consistency

Our skin influences our physical and mental health, and its chemical composition can reflect environmental and disease conditions. Therefore, through sampling the skin metabolome, we can provide a promising window into the mechanisms of the body. However, the broad application of skin metabolomics has recently been hampered by a lack of easy and widely applicable sampling methods. Here, we present a novel rapid, simple, and, most importantly, painless and non-invasive sampling technique suitable for clinical studies of fragile or weakened skin. The method is called WET PREP and is simply a lavage of the skin which focuses on capturing the metabolome. We systematically evaluate WET PREPs in comparison with the non-invasive method of choice in skin metabolomics, swab collection, using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS2) on two complementary chromatographic columns (C18 reversed phase and hydrophilic interaction chromatography). We also integrate targeted analyses of key metabolites of skin relevance. Overall, WET PREP provides a strikingly more stable shared metabolome across sampled individuals, while also being able to capture unique individual metabolites with a high consistency in intra-individual reproducibility. With the exception of (phospho-)lipidomic studies, we recommend WET PREPs as the preferred skin metabolome sampling technique due to the quick preparation time, low cost, and gentleness for the patient.

scholarly journals An Application of Fish Detection Based on Eye Search with Artificial Vision and Artificial Neural Networks

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3013
Author(s):  
Ángel J. Rico-Díaz ◽  
Juan R. Rabuñal ◽  
Marcos Gestal ◽  
Omar A. Mures ◽  
Jerónimo Puertas
Keyword(s):  
Low Cost ◽  
Fish Farm ◽  
Artificial Vision ◽  
Stereo Image ◽  
Disparity Map ◽  
Image Recording ◽  
Non Invasive ◽  
Accuracy And Precision ◽  
Feed Forward Network ◽  
Invasive Method

A fish can be detected by means of artificial vision techniques, without human intervention or handling the fish. This work presents an application for detecting moving fish in water by artificial vision based on the detection of a fish′s eye in the image, using the Hough algorithm and a Feed-Forward network. In addition, this method of detection is combined with stereo image recording, creating a disparity map to estimate the size of the detected fish. The accuracy and precision of this approach has been tested in several assays with living fish. This technique is a non-invasive method working in real-time and it can be carried out with low cost. Furthermore, it could find application in aquariums, fish farm management and to count the number of fish which swim through a fishway. In a fish farm it is important to know how the size of the fish evolves in order to plan the feeding and when to be able to catch fish. Our methodology allows fish to be detected and their size and weight estimated as they move underwater, engaging in natural behavior.

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