ArticleMilitary medicine2023
Adaptive Human-Robotic Interaction for Robotic-assisted Surgical Settings.
Article in Military medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Neural insights on expert surgeons' mental workload during live robotic surgeries.Scientific reports · 2025Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
introductionIncreased complexity in robotic-assisted surgical system interfaces introduces problems with human-robot collaboration that result in excessive mental workload (MWL), adversely impacting a surgeon's task performance and increasing error probability. Real-time monitoring of the operator's MWL will aid in identifying when and how interventions can be best provided to moderate MWL. In this study, an MWL-based adaptive automation system is constructed and evaluated for its effectiveness during robotic-assisted surgery. MATERIALS AND
methodsThis study recruited 10 participants first to perform surgical tasks under different cognitive workload levels. Physiological signals were obtained and employed to build a real-time system for cognitive workload monitoring. To evaluate the effectiveness of the proposed system, 15 participants were recruited to perform the surgical task with and without the proposed system. The participants' task performance and perceived workload were collected and compared.
resultsThe proposed neural network model achieved an accuracy of 77.9% in cognitive workload classification. In addition, better task performance and lower perceived workload were observed when participants completed the experimental task under the task condition supplemented with adaptive aiding using the proposed system.
conclusionsThe proposed MWL monitoring system successfully diminished the perceived workload of participants and increased their task performance under high-stress conditions via interventions by a semi-autonomous suction tool. The preliminary results from the comparative study show the potential impact of automated adaptive aiding systems in enhancing surgical task performance via cognitive workload-triggered interventions in robotic-assisted surgery.
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