Today, most fatal accidents in commercial aviation are caused by loss of control in flight. Due to the increased reliance on automation and pilots being moved out of the loop, startling and surprising events can be contributing factors. To more effectively train pilots, startle and surprise are to be included in training scenario’s. A subjective scale indicating the level of startle and surprise is being developed to help build these training programs, but an objective baseline of whether pilots are startled or surprised is needed in order to validate and further develop this scale. In this way, the scale can be used in flight simulators to asses the pilot’s perceived level of startle and surprise during novel training scenario’s. This work aims to test a startle and surprise detection method using physiological data. Electromyography, electrocardiography and electroencephalography data were collected. A validation of the occurrence of physiological effects related to both startle and surprise was performed, after which a detection algorithm was constructed. Validation of effects was performed on data of 22 participants using a three-stimulus oddball task with additional auditory startling stimuli. It was found that all considered physiological effects related to startle can be reliably observed. Contrary, not all physiological effects related to surprise were observed. The detection algorithm was tuned on data of twelve participants and showed to generalise well to the other ten data points. Startle detection could be performed with high accuracy, although surprise detection was poor.