Explosive sensing with insect-based biorobots
Stand-off chemical sensing is an important capability with applications in several domains including homeland security. Engineered devices for this task, popularly referred to as electronic noses, have limited capacity compared to the broad-spectrum abilities of the biological olfactory system. Ther...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-12-01
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| Series: | Biosensors and Bioelectronics: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590137020300169 |
| _version_ | 1818623408605233152 |
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| author | Debajit Saha Darshit Mehta Ege Altan Rishabh Chandak Mike Traner Ray Lo Prashant Gupta Srikanth Singamaneni Shantanu Chakrabartty Baranidharan Raman |
| author_facet | Debajit Saha Darshit Mehta Ege Altan Rishabh Chandak Mike Traner Ray Lo Prashant Gupta Srikanth Singamaneni Shantanu Chakrabartty Baranidharan Raman |
| author_sort | Debajit Saha |
| collection | DOAJ |
| description | Stand-off chemical sensing is an important capability with applications in several domains including homeland security. Engineered devices for this task, popularly referred to as electronic noses, have limited capacity compared to the broad-spectrum abilities of the biological olfactory system. Therefore, we propose a hybrid bio-electronic solution that directly takes advantage of the rich repertoire of olfactory sensors and sophisticated neural computational framework available in an insect olfactory system. We show that select subsets of neurons in the locust (Schistocerca americana) brain were activated upon exposure to various explosive chemical species (such as DNT and TNT). Responses from an ensemble of neurons provided a unique, multivariate fingerprint that allowed discrimination of explosive vapors from non-explosive chemical species and from each other. Notably, target chemical recognition could be achieved within a few hundred milliseconds of exposure. In sum, our study provides the first demonstration of how biological olfactory systems (sensors and computations) can be hijacked to develop a cyborg chemical sensing approach. |
| first_indexed | 2024-12-16T18:40:35Z |
| format | Article |
| id | doaj.art-466e1f61c1ea404198451d492ef0adf4 |
| institution | Directory Open Access Journal |
| issn | 2590-1370 |
| language | English |
| last_indexed | 2024-12-16T18:40:35Z |
| publishDate | 2020-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Biosensors and Bioelectronics: X |
| spelling | doaj.art-466e1f61c1ea404198451d492ef0adf42022-12-21T22:21:04ZengElsevierBiosensors and Bioelectronics: X2590-13702020-12-016100050Explosive sensing with insect-based biorobotsDebajit Saha0Darshit Mehta1Ege Altan2Rishabh Chandak3Mike Traner4Ray Lo5Prashant Gupta6Srikanth Singamaneni7Shantanu Chakrabartty8Baranidharan Raman9Department of Biomedical Engineering, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USADepartment of Mechanical Engineering and Material Science, Washington University in St. Louis, USADepartment of Mechanical Engineering and Material Science, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USA; Department of Electrical and Systems Engineering, Washington University in St. Louis, USADepartment of Biomedical Engineering, Washington University in St. Louis, USA; Department of Electrical and Systems Engineering, Washington University in St. Louis, USA; Corresponding author. Department of Biomedical Engineering, Washington University in St. Louis, USA.Stand-off chemical sensing is an important capability with applications in several domains including homeland security. Engineered devices for this task, popularly referred to as electronic noses, have limited capacity compared to the broad-spectrum abilities of the biological olfactory system. Therefore, we propose a hybrid bio-electronic solution that directly takes advantage of the rich repertoire of olfactory sensors and sophisticated neural computational framework available in an insect olfactory system. We show that select subsets of neurons in the locust (Schistocerca americana) brain were activated upon exposure to various explosive chemical species (such as DNT and TNT). Responses from an ensemble of neurons provided a unique, multivariate fingerprint that allowed discrimination of explosive vapors from non-explosive chemical species and from each other. Notably, target chemical recognition could be achieved within a few hundred milliseconds of exposure. In sum, our study provides the first demonstration of how biological olfactory systems (sensors and computations) can be hijacked to develop a cyborg chemical sensing approach.http://www.sciencedirect.com/science/article/pii/S2590137020300169Insect-based machine olfactionChemical sensingExplosives detectionNeural signalsPattern recognitionNeural engineering |
| spellingShingle | Debajit Saha Darshit Mehta Ege Altan Rishabh Chandak Mike Traner Ray Lo Prashant Gupta Srikanth Singamaneni Shantanu Chakrabartty Baranidharan Raman Explosive sensing with insect-based biorobots Biosensors and Bioelectronics: X Insect-based machine olfaction Chemical sensing Explosives detection Neural signals Pattern recognition Neural engineering |
| title | Explosive sensing with insect-based biorobots |
| title_full | Explosive sensing with insect-based biorobots |
| title_fullStr | Explosive sensing with insect-based biorobots |
| title_full_unstemmed | Explosive sensing with insect-based biorobots |
| title_short | Explosive sensing with insect-based biorobots |
| title_sort | explosive sensing with insect based biorobots |
| topic | Insect-based machine olfaction Chemical sensing Explosives detection Neural signals Pattern recognition Neural engineering |
| url | http://www.sciencedirect.com/science/article/pii/S2590137020300169 |
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