A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose
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 sampl...
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doaj-c39efdbe7b354513a3f09fe6bde954122020-11-25T01:35:03ZengMDPI AGSensors1424-82202019-11-011922484610.3390/s19224846s19224846A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic NoseZhifang Liang0Fengchun Tian1Ci Zhang2Liu Yang3School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongwen Road 2nd, Nan’an District, Chongqing 400065, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, 174 ShaZheng Street, ShaPingBa District, Chongqing 400044, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, 174 ShaZheng Street, ShaPingBa District, Chongqing 400044, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongwen Road 2nd, Nan’an District, Chongqing 400065, ChinaA 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).https://www.mdpi.com/1424-8220/19/22/4846electronic nosesubspace alignmentinterference suppressiontransfer |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhifang Liang Fengchun Tian Ci Zhang Liu Yang |
spellingShingle |
Zhifang Liang Fengchun Tian Ci Zhang Liu Yang A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose Sensors electronic nose subspace alignment interference suppression transfer |
author_facet |
Zhifang Liang Fengchun Tian Ci Zhang Liu Yang |
author_sort |
Zhifang Liang |
title |
A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose |
title_short |
A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose |
title_full |
A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose |
title_fullStr |
A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose |
title_full_unstemmed |
A Novel Subspace Alignment-Based Interference Suppression Method for the Transfer Caused by Different Sample Carriers in Electronic Nose |
title_sort |
novel subspace alignment-based interference suppression method for the transfer caused by different sample carriers in electronic nose |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2019-11-01 |
description |
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). |
topic |
electronic nose subspace alignment interference suppression transfer |
url |
https://www.mdpi.com/1424-8220/19/22/4846 |
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