Print Email Facebook Twitter Early detection of exposure to toxic chemicals using continuously recorded multi-sensor physiology Title Early detection of exposure to toxic chemicals using continuously recorded multi-sensor physiology Author van Baardewijk, Jan Ubbo (TNO) Agarwal, Sarthak (Student TU Delft; TNO) Cornelissen, Alex S. (TNO) Joosen, Marloes J. A. (TNO) Kentrop, Jiska (TNO) Varon, Carolina (TU Delft Signal Processing Systems) Brouwer, Anne-Marie (TNO) Date 2021 Abstract Early detection of exposure to a toxic chemical, e.g., in a military context, can be life-saving. We propose to use machine learning techniques and multiple continuously measured physiological signals to detect exposure, and to identify the chemical agent. Such detection and identification could be used to alert individuals to take appropriate medical counter measures in time. As a first step, we evaluated whether exposure to an opioid (fentanyl) or a nerve agent (VX) could be detected in freely moving guinea pigs using features from respiration, electrocardiography (ECG) and electroencephalography (EEG), where machine learning models were trained and tested on different sets (across subject classification). Results showed this to be possible with close to perfect accuracy, where respiratory features were most relevant. Exposure detection accuracy rose steeply to over 95% correct during the first five minutes after exposure. Additional models were trained to correctly classify an exposed state as being induced either by fentanyl or VX. This was possible with an accuracy of almost 95%, where EEG features proved to be most relevant. Exposure detection models that were trained on subsets of animals generalized to subsets of animals that were exposed to other dosages of different chemicals. While future work is required to validate the principle in other species and to assess the robustness of the approach under different, realistic circumstances, our results indicate that utilizing different continuously measured physiological signals for early detection and identification of toxic agents is promising. Subject Chemical exposureDifferential diagnosisElectrocardiographyElectroencephalographyMachine learningNerve agentOpioidRespirationToxidrome detection To reference this document use: http://resolver.tudelft.nl/uuid:c0c4374b-55c3-43c4-b51b-43f261a8abea DOI https://doi.org/10.3390/s21113616 ISSN 1424-8220 Source Sensors, 21 (11), 1-10 Part of collection Institutional Repository Document type journal article Rights © 2021 Jan Ubbo van Baardewijk, Sarthak Agarwal, Alex S. Cornelissen, Marloes J. A. Joosen, Jiska Kentrop, Carolina Varon, Anne-Marie Brouwer Files PDF sensors_21_03616_v2.pdf 634.92 KB Close viewer /islandora/object/uuid:c0c4374b-55c3-43c4-b51b-43f261a8abea/datastream/OBJ/view