Proof-of-Concept of Pressure-Ulcer-Associated VOC Biomarkers’ Detection Using a Nanocomposite-Based Quantum Resistive Vapour Sensor Array

Pressure ulcers (PUs), commonly referred to as bedsores, are a major health problem for which early detection remains challenging. Volatile organic compounds (VOCs) released from pressure-affected skin have been proposed as potential biomarkers, providing a complementary approach to conventional visual and pressure-based monitoring. In this study, a cross-reactive electronic nose (e-nose) comprising nine quantum resistive vapour sensors (vQRSs) was evaluated for the detection of three VOCs previously associated with pressure-ulcer-related skin emissions: benzyl alcohol, pentadecane and 1-tetradecene. The vQRS transducers consisted of carbon nanotube (CNT) networks functionalized with different polymer matrices, namely poly (vinylpyrrolidone), poly (vinyl acetate), poly (lactic acid), poly (ethylene glycol), poly (caprolactone), poly (methyl methacrylate), poly (styrene-co-acrylonitrile), polystyrene and sulfonated poly (ether ether ketone). The individual sensors were first evaluated using benzyl alcohol and water vapour at concentrations ranging from approximately 100 ppb to 1 ppm. A measurable response was obtained at 100 ppb, with signal-to-noise ratios exceeding five for six vQRSs. Water vapour modified the response amplitude and apparent sensitivity to benzyl alcohol, highlighting the importance of humidity effects under skin-relevant conditions. The sensor array was subsequently exposed to synthetic mixtures containing the selected biomarkers in a complex VOC background with controlled water vapour content. Principal component analysis (PCA) of the sensor responses enabled discrimination between the different biomarker-containing mixtures, their concentrations, and the background mixture. Combining the maximum response amplitude with the integrated response area further improved separation in the PCA score space compared with amplitude alone. PCA was used as an exploratory visualization tool; no supervised classification or cross-validation was performed, and the data were obtained from synthetic mixtures and a single background donor. These results demonstrate the feasibility of using a cross-reactive CNT/polymer vQRS array to detect pressure-ulcer-associated VOC signatures under controlled laboratory conditions. The study illustrates the possible recognition of synthetic blends of three candidate VOCs added to a healthy-skin background (one donor, four skin sites). Further studies using real skin emissions from individuals will target the discrimination between healthy and patients with pressure ulcers to assess the robustness and clinical diagnostic value of the approach.

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Publication Details

Journal
Journal of Nanotheranostics
Published
2026-10-26
DOI
https://doi.org/10.3390/jnt7040025
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
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article

Proof-of-Concept of Pressure-Ulcer-Associated VOC Biomarkers’ Detection Using a Nanocomposite-Based Quantum Resistive Vapour Sensor Array

Abhishek Sachan, Mickaël Castro, Jean‐François Feller, Tran Manh Trung
Journal of Nanotheranostics
Advanced Chemical Sensor Technologies
article

Proof-of-Concept of Pressure-Ulcer-Associated VOC Biomarkers’ Detection Using a Nanocomposite-Based Quantum Resistive Vapour Sensor Array

Abhishek Sachan, Mickaël Castro, Jean‐François Feller, Tran Manh Trung
article en

Abstract

Pressure ulcers (PUs), commonly referred to as bedsores, are a major health problem for which early detection remains challenging. Volatile organic compounds (VOCs) released from pressure-affected skin have been proposed as potential biomarkers, providing a complementary approach to conventional visual and pressure-based monitoring. In this study, a cross-reactive electronic nose (e-nose) comprising nine quantum resistive vapour sensors (vQRSs) was evaluated for the detection of three VOCs previously associated with pressure-ulcer-related skin emissions: benzyl alcohol, pentadecane and 1-tetradecene. The vQRS transducers consisted of carbon nanotube (CNT) networks functionalized with different polymer matrices, namely poly (vinylpyrrolidone), poly (vinyl acetate), poly (lactic acid), poly (ethylene glycol), poly (caprolactone), poly (methyl methacrylate), poly (styrene-co-acrylonitrile), polystyrene and sulfonated poly (ether ether ketone). The individual sensors were first evaluated using benzyl alcohol and water vapour at concentrations ranging from approximately 100 ppb to 1 ppm. A measurable response was obtained at 100 ppb, with signal-to-noise ratios exceeding five for six vQRSs. Water vapour modified the response amplitude and apparent sensitivity to benzyl alcohol, highlighting the importance of humidity effects under skin-relevant conditions. The sensor array was subsequently exposed to synthetic mixtures containing the selected biomarkers in a complex VOC background with controlled water vapour content. Principal component analysis (PCA) of the sensor responses enabled discrimination between the different biomarker-containing mixtures, their concentrations, and the background mixture. Combining the maximum response amplitude with the integrated response area further improved separation in the PCA score space compared with amplitude alone. PCA was used as an exploratory visualization tool; no supervised classification or cross-validation was performed, and the data were obtained from synthetic mixtures and a single background donor. These results demonstrate the feasibility of using a cross-reactive CNT/polymer vQRS array to detect pressure-ulcer-associated VOC signatures under controlled laboratory conditions. The study illustrates the possible recognition of synthetic blends of three candidate VOCs added to a healthy-skin background (one donor, four skin sites). Further studies using real skin emissions from individuals will target the discrimination between healthy and patients with pressure ulcers to assess the robustness and clinical diagnostic value of the approach.

Journal of NanotheranosticsVol. 7(4)
Centre National de la Recherche Scientifique (FR), Université de Bretagne Sud (FR), Institut de Recherche Dupuy de Lôme (FR)
Openalex Percentile: Top 25%
Advanced Chemical Sensor Technologies
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