Multichannel Hierarchical Analysis of Time-Resolved Hyperspectral Data for Advanced Colorimetric E-Nose.
Tae-In JeongThanh Mien NguyenEunji ChoiAlexander GliserinThu M T NguyenSan KimSehyeon KimHyunseo KimGyeong-Ha BakNa-Yeong KimVasanthan DevarajEunjung ChoiJin-Woo OhSeungchul KimPublished in: ACS sensors (2024)
The colorimetric sensor-based electronic nose has been demonstrated to discriminate specific gaseous molecules for various applications, including health or environmental monitoring. However, conventional colorimetric sensor systems rely on RGB sensors, which cannot capture the complete spectral response of the system. This limitation can degrade the performance of machine learning analysis, leading to inaccurate identification of chemicals with similar functional groups. Here, we propose a novel time-resolved hyperspectral (TRH) data set from colorimetric array sensors consisting of 1D spatial, 1D spectral, and 1D temporal axes, which enables hierarchical analysis of multichannel 2D spectrograms via a convolution neural network (CNN). We assessed the outstanding classification performance of the TRH data set compared to an RGB data set by conducting a relative humidity (RH) concentration classification. The time-dependent spectral response of the colorimetric sensor was measured and trained as a CNN model using TRH and RGB sensor systems at different RH levels. While the TRH model shows a high classification accuracy of 97.5% for the RH concentration, the RGB model yields 72.5% under identical conditions. Furthermore, we demonstrated the detection of various functional volatile gases with the TRH system by using experimental and simulation approaches. The results reveal distinct spectral features from the TRH system, corresponding to changes in the concentration of each substance.
Keyphrases
- gold nanoparticles
- machine learning
- hydrogen peroxide
- big data
- electronic health record
- optical coherence tomography
- fluorescent probe
- sensitive detection
- neural network
- deep learning
- living cells
- artificial intelligence
- public health
- aqueous solution
- label free
- mental health
- convolutional neural network
- dual energy
- data analysis
- high resolution
- risk assessment
- loop mediated isothermal amplification
- low cost
- human health
- high throughput
- computed tomography
- social media
- dna methylation
- magnetic resonance
- genome wide
- single molecule
- magnetic resonance imaging
- single cell
- body composition