scholarly journals A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4846 ◽  
Author(s):  
Zhifang Liang ◽  
Fengchun Tian ◽  
Ci Zhang ◽  
Liu Yang
Keyword(s):  
Wound Infection ◽  
Electronic Nose ◽  
Recognition Accuracy ◽  
Interference Suppression ◽  
Laboratory Data ◽  
Clinical Samples ◽  
Culture Solution ◽  
Practical Applications ◽  
Whole Space ◽  
Subspace Alignment

A medical electronic nose (e-nose) with 31 gas sensors is used for wound infection detection by analyzing the bacterial metabolites. In practical applications, the prediction accuracy drops dramatically when the prediction model established by laboratory data is directly used in human clinical samples. This is a key issue for medical e-nose which should be more worthy of attention. The host (carrier) of bacteria can be the culture solution, the animal wound, or the human wound. As well, the bacterial culture solution or animals (such as: mice, rabbits, etc.) obtained easily are usually used as experimental subjects to collect sufficient sensor array data to establish the robust predictive model, but it brings another serious interference problem at the same time. Different carriers have different background interferences, therefore the distribution of data collected under different carriers is different, which will make a certain impact on the recognition accuracy in the detection of human wound infection. This type of interference problem is called “transfer caused by different sample carriers”. In this paper, a novel subspace alignment-based interference suppression (SAIS) method with domain correction capability is proposed to solve this interference problem. The subspace is the part of space whose dimension is smaller than the whole space, and it has some specific properties. In this method, first the subspaces of different data domains are gotten, and then one subspace is aligned to another subspace, thereby the problem of different distributions between two domains is solved. From experimental results, it can be found that the recognition accuracy of the infected rat samples increases from 29.18% (there is no interference suppression) to 82.55% (interference suppress by SAIS).

A novel sensor array and classifier optimization method of electronic nose based on enhanced quantum-behaved particle swarm optimization

Sensor Review ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 304-311 ◽  
Author(s):  
Pengfei Jia ◽  
Fengchun Tian ◽  
Shu Fan ◽  
Qinghua He ◽  
Jingwei Feng ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Wound Infection ◽  
Electronic Nose ◽  
Classification Accuracy ◽  
Sensor Array ◽  
Particle Swarm ◽  
Optimization Method ◽  
Support Vector ◽  
Swarm Optimization ◽  
Content Type

Purpose – The purpose of the paper is to propose a new optimization algorithm to realize a synchronous optimization of sensor array and classifier, to improve the performance of E-nose in the detection of wound infection. When an electronic nose (E-nose) is used to detect the wound infection, sensor array’s optimization and parameters’ setting of classifier have a strong impact on the classification accuracy. Design/methodology/approach – An enhanced quantum-behaved particle swarm optimization based on genetic algorithm, genetic quantum-behaved particle swarm optimization (G-QPSO), is proposed to realize a synchronous optimization of sensor array and classifier. The importance-factor (I-F) method is used to weight the sensors of E-nose by its degree of importance in classification. Both radical basis function network and support vector machine are used for classification. Findings – The classification accuracy of E-nose is the highest when the weighting coefficients of the I-F method and classifier’s parameters are optimized by G-QPSO. All results make it clear that the proposed method is an ideal optimization method of E-nose in the detection of wound infection. Research limitations/implications – To make the proposed optimization method more effective, the key point of further research is to enhance the classifier of E-nose. Practical implications – In this paper, E-nose is used to distinguish the class of wound infection; meanwhile, G-QPSO is used to realize a synchronous optimization of sensor array and classifier of E-nose. These are all important for E-nose to realize its clinical application in wound monitoring. Originality/value – The innovative concept improves the performance of E-nose in wound monitoring and paves the way for the clinical detection of E-nose.

scholarly journals Electromyogram-based hand gesture recognition robust to various arm postures

2018 ◽  
Vol 14 (7) ◽  
pp. 155014771879075 ◽  
Author(s):  
Kiwon Rhee ◽  
Hyun-Chool Shin
Keyword(s):  
Gesture Recognition ◽  
Recognition Accuracy ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Hand Gestures ◽  
Practical Applications ◽  
Electrode Positioning ◽  
Recognition Technique

In the recognition of electromyogram-based hand gestures, the recognition accuracy may be degraded during the actual stage of practical applications for various reasons such as electrode positioning bias and different subjects. Besides these, the change in electromyogram signals due to different arm postures even for identical hand gestures is also an important issue. We propose an electromyogram-based hand gesture recognition technique robust to diverse arm postures. The proposed method uses both the signals of the accelerometer and electromyogram simultaneously to recognize correct hand gestures even for various arm postures. For the recognition of hand gestures, the electromyogram signals are statistically modeled considering the arm postures. In the experiments, we compared the cases that took into account the arm postures with the cases that disregarded the arm postures for the recognition of hand gestures. In the cases in which varied arm postures were disregarded, the recognition accuracy for correct hand gestures was 54.1%, whereas the cases using the method proposed in this study showed an 85.7% average recognition accuracy for hand gestures, an improvement of more than 31.6%. In this study, accelerometer and electromyogram signals were used simultaneously, which compensated the effect of different arm postures on the electromyogram signals and therefore improved the recognition accuracy of hand gestures.

Learn the Temporal-Spatial Feature of sEMG via Dual-Flow Network

2019 ◽  
Vol 16 (04) ◽  
pp. 1941004 ◽  
Author(s):  
Runze Tong ◽  
Yue Zhang ◽  
Hongfeng Chen ◽  
Honghai Liu
Keyword(s):  
Gesture Recognition ◽  
Short Term Memory ◽  
Recognition Accuracy ◽  
Human Machine Interaction ◽  
Flow Network ◽  
Spatial Feature ◽  
Practical Applications ◽  
Long Short Term Memory ◽  
Machine Interaction ◽  
Semg Signals

Surface electromyography (sEMG) signals have been widely used in human–machine interaction, providing more nature control expedience for external devices. However, due to the instability of sEMG, it is hard to extract consistent sEMG patterns for motion recognition. This paper proposes a dual-flow network to extract the temporal-spatial feature of sEMG for gesture recognition. The proposed network model uses convolutional neural network (CNN) and long short-term memory methods (LSTM) to, respectively, extract the spatial feature and temporal feature of sEMG, simultaneously. These features extracted by CNN and LSTM are merged into temporal-spatial feature to form an end-to-end network. A dataset was constructed for testing the performance of the network. In this database, the average recognition accuracy by using our dual-flow model reached 78.31%, which was improved by 6.69% compared to the baseline CNN (71.67%). In addition, NinaPro DB1 is also used to evaluate the proposed methods, receiving 1.86% higher recognition accuracy than the baseline CNN classifier. It is believed that the proposed dual-flow network owns the merit in extracting stable sEMG feature for gesture recognition, and can be further applied into practical applications.

scholarly journals Epidemiology of carbapenem-resistant Enterobacteriaceae in a Tertiary Care Center in the Kingdom of Bahrain

2019 ◽  
Vol 11 (02) ◽  
pp. 111-117 ◽  
Author(s):  
Nermin Kamal Saeed ◽  
Safaa Alkhawaja ◽  
Nashawa Fawzy Abd El Moez Azam ◽  
Khalil Alaradi ◽  
Mohammed Al-Biltagi
Keyword(s):  
Control Measure ◽  
Care Center ◽  
Tertiary Care ◽  
Laboratory Data ◽  
Control Measures ◽  
Clinical Samples ◽  
Common Source ◽  
Care Hospital ◽  
Carbapenem Resistant ◽  
Carbapenem Resistant Enterobacteriaceae

Abstract PURPOSE: The purpose of the study is to estimate the rate of infection with carbapenem-resistant Enterobacteriaceae (CRE) in the main governmental tertiary care hospital in Bahrain. MATERIALS AND METHODS: All clinical samples with positive growth of CRE over 6-year period (January 2012–December 2017) were collected from the microbiology laboratory data. RESULTS: The CRE incidence was high in the first half of study period (2012–2014) and then decreased between 2015 and 2017, after implementation of intensified CRE control measure bundle. About 49.4% of CRE-positive samples were isolated from the elderly age group (above 65 years old), most of them were admitted in the intensive care unit (ICU). The most common isolated organisms were Klebsiella pneumoniae (87.0%), followed by Escherichia coli (7.9%). Isolates from deep tracheal aspirate and midstream urine specimens were the most common source of CRE isolates (27.3%) and (26.3%), respectively. Bacteremia was documented in 21.2% of cases. CRE isolates in the study showed high rates of resistance to aminoglycosides (72.2% resistant to amikacin and 67.3% to gentamicin). Alternatively, most isolates retained their susceptibility to colistin and tigecycline with sensitivity of 83.9% and 85.7%, respectively. Combined resistance to both colistin and tigecycline was observed in 0.06% of total isolates. CONCLUSION: Elderly population and ICU admission were important risk factors for CRE acquisition. Most of CRE isolates were sensitive to both colistin and tigecycline, which make them the best combination for empiric frontline therapy for suspected serious CRE infection in our facility. Implementing CRE-bundled infection control measures significantly reduced the incidence of CRE infection in our hospital.

Fault Diagnosis of Pump Based on a Hybrid HMM/SVM Model

2011 ◽  
Vol 188 ◽  
pp. 629-635
Author(s):  
Xia Yue ◽  
Chun Liang Zhang ◽  
Jian Li ◽  
H.Y. Zhu
Keyword(s):  
Fault Diagnosis ◽  
Hybrid Model ◽  
Large Scale ◽  
Recognition Accuracy ◽  
Recognition Rate ◽  
Double Layers ◽  
Support Vector ◽  
Practical Applications ◽  
Average Recognition Rate ◽  
Svm Model

A hybrid support vector machine (SVM) and hidden Markov model (HMM) model was introduced into the fault diagnosis of pump. This model had double layers: the first layer used HMM to classify preliminarily in order to get the coverage of possible faults; the second layer utilized this information to activate the corresponding SVMs for improving the recognition accuracy. The structure of this hybrid model was clear and feasible. Especially the model had the potential of large-scale multiclass application in fault diagnosis because of its good scalability. The recognition experiments of 26 statuses on the ZLH600-2 pump showed that the recognition capability of this model was sound in multiclass problems. The recognition rate of one bearing eccentricity increased from SVM’s 84.42% to 89.61% while the average recognition rate of hybrid model reached 95.05%. Although some goals while model constructed did not be fully realized, this model was still very good in practical applications.

scholarly journals A review of the current state of antimicrobial susceptibility test methods for Brachyspira

2017 ◽  
Vol 63 (6) ◽  
pp. 465-474 ◽  
Author(s):  
D.G.R.S. Kulathunga ◽  
J.E. Rubin
Keyword(s):  
Antimicrobial Susceptibility ◽  
Susceptibility Testing ◽  
Treatment Plan ◽  
Laboratory Data ◽  
Test Methods ◽  
Clinical Samples ◽  
Antimicrobial Susceptibility Test ◽  
Future Directions ◽  
Diagnostic Strategies ◽  
Current State

The re-emergence of swine dysentery (Brachyspira-associated muco-haemorrhagic colitis) since the late 2000s has illuminated diagnostic challenges associated with this genus. The methods used to detect, identify, and characterize Brachyspira from clinical samples have not been standardized, and laboratories frequently rely heavily on in-house techniques. Particularly concerning is the lack of standardized methods for determining and interpreting the antimicrobial susceptibility of Brachyspira spp. The integration of laboratory data into a treatment plan is a critical component of prudent antimicrobial usage. Therefore, the lack of standardized methods is an important limitation to the evidence-based use of antimicrobials. This review will focus on describing the methodological limitations and inconsistencies between current susceptibility testing schemes employed for Brachyspira, provide an overview of what we do know about the susceptibility of these organisms, and suggest future directions to improve and standardize diagnostic strategies.

Inherent biological variation and reference values

2004 ◽  
Vol 42 (7) ◽  
Author(s):  
Callum G. Fraser
Keyword(s):  
Reference Values ◽  
Laboratory Data ◽  
Population Based ◽  
Biological Variation ◽  
Specific Reference ◽  
Theoretical Concepts ◽  
Practical Applications ◽  
Medical Laboratories ◽  
Clinical Purpose ◽  
Traditional Population

AbstractThere is a need for revisiting theoretical concepts and practical applications of conventional population-based reference values to make for better clinical use of laboratory data. Knowledge of the underlying biological variation of quantities examined in medical laboratories is vital to understanding the proper generation and application of traditional population-based reference values. Appreciation of the biological changes that occur over the span of life is a necessary prerequisite to deciding whether stratification of reference values according to age is likely to be necessary. Knowledge of the detail of predictable biological cyclical rhythms is required for correct clinical interpretation of laboratory data and appropriate collection of specimens at times relevant to the clinical purpose. Quantitative data on inherent within- and between-subject biological components of variation have shown the marked individuality of most quantities of interest in laboratory medicine. This individuality casts light on why examinations are not generally very successfully applied in population screening or case-finding. Consideration of individuality demonstrates why stratification of reference values is often very advantageous. Individuality provides an indisputable argument for better use of individual specific reference values.

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