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Surgical modality and task complexity: An fNIRS based investigation of cognitive load in minimally invasive techniques

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2025
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Özet (EN)

Minimally invasive surgical techniques, such as laparoscopic and robotic surgery, have advanced practice by improving precision, reducing recovery times, and minimizing complications. However, these approaches impose different cognitive demands and require distinct skills. This study uses functional near-infrared spectroscopy (fNIRS) to assess cognitive workload differences across surgical modalities and task complexities. We examined how surgical modality (laparoscopy vs. robotic surgery) and task complexity (pick and place vs. knot tying) influence cognitive workload, and compared demands in simulation based and real world environments. Twenty six trainees and specialists in general and gynecologic surgery participated. They performed standardized laparoscopic and robotic tasks of varying complexity while prefrontal cortex activity and task times were recorded using fNIRS. Both simulation based and real settings were included. Laparoscopic surgery induced greater prefrontal cortex activation than robotic surgery, especially during complex tasks like knot tying, indicating higher cognitive workload. Task complexity was a major factor, with more intricate procedures prompting increased neural activation. Real surgical environments led to greater cognitive engagement than simulations. Robotic surgery was linked to lower cognitive load, likely due to ergonomic and motor control advantages. While simulation based training prepares surgeons, it does not fully replicate the cognitive demands of real operations. These findings underscore the importance of cognitive workload assessment in surgical education and support integrating neuroimaging tools like fNIRS into training programs to improve skill acquisition and performance.

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Fuat Ücrak

Bu Yayına Nasıl Atıf Yapılır

Fuat Ücrak (Doctorate thesis). Surgical modality and task complexity: An fNIRS based investigation of cognitive load in minimally invasive techniques, 2025, Boğaziçi University.

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