{'fraction_non_alphanumeric': 0.012461059190031152, 'fraction_numerical': 0.0, 'mean_word_length': 5.6482758620689655, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Workload prediction and estimation of human mental resources in Helicopter Emergency Medical Service missions

Helicopter Emergency Medical Service (HEMS) missions are associated with high workload for the cockpit crew. Cognitive assistant systems investigated today to counteract high workload issues are proven beneficial in principle, but may also induce additional load for the pilot, especially if the system intervenes when the human operator has little or no free cognitive resources to adopt the offered support. The basis for counteracting such automation induced issues is the automatic, reliable, task-related assessment of the current workload of the human operator. In this article we present a concept and prototype implementation to estimate the usage of mental resources of the human pilot and his current workload level in HEMS missions. Furthermore we describe first evaluation experiments conducted in our research helicopter mission simulator.