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The performance of such teams relies on proper trust in the autonomous system, thus creating an urgent need to capture the dynamic nature of trust and devise objective, non-disruptive means of precisely modeling trust. This paper describes the use of bio-signals and embedded measures to create a model capable of inferring and predicting trust. Data (2304 observations) was collected via human subject testing (n = 12, 7M\/5F) during which participants interacted with a simulated autonomous system in an operationally relevant, human-on-the-loop, remote monitoring task and reported their subjective trust via visual analog scales. Electrocardiogram, respiration, electrodermal activity, electroencephalogram, functional near-infrared spectroscopy, eye-tracking, and button click data were collected during each trial. Operator background information were collected prior to the experiment. Features were extracted and algorithmically down-selected, then ordinary least squares regression was used to fit the model, and predictive capabilities were assessed on unseen trials. Model predictions achieved a high level of accuracy with a Q<jats:sup>2<\/jats:sup> of 0.64 and captured rapid changes in trust during an operationally relevant human-autonomy teaming task. The model advances the field of non-disruptive means of inferring trust by incorporating a broad suite of physiological signals into a model that is predictive, while many current models are purely descriptive. Future work should assess model performance on unseen participants.<\/jats:p>","DOI":"10.3389\/frobt.2025.1624777","type":"journal-article","created":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T04:18:44Z","timestamp":1760069924000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Modeling trust and its dynamics from physiological signals and embedded measures for operational human-autonomy teaming"],"prefix":"10.3389","volume":"12","author":[{"given":"Abigail","family":"Rindfuss","sequence":"first","affiliation":[]},{"given":"Sarah","family":"Leary","sequence":"additional","affiliation":[]},{"given":"Prachi","family":"Dutta","sequence":"additional","affiliation":[]},{"given":"Ryan","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Torin K.","family":"Clark","sequence":"additional","affiliation":[]},{"given":"Zhaodan","family":"Kong","sequence":"additional","affiliation":[]},{"given":"Allison P. 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