As one of the modern minimally invasive procedures, laparoscopic surgery has become popular primarily due to its small wounds and rapid recovery. However, residents generally have a long training period (6 years at least) to be trained as qualified laparoscopic surgeons . In the narrow operation space, mistakes may easily occur if laparoscopic surgeons do not handle procedures properly. Traditional laparoscopic surgical training usually chooses the training box within vitro animals or corpses organs, which could give rise to negative effects, such as high cost, low reusability, and related ethical issues . The advent of VR surgical simulators has changed the surgeons learning mode. It can simulate the surgery from the visual, auditory, and tactile aspects. It not only reconstructs the real surgical environment and procedures but also can be reused for a variety of designed training tasks without surgical risk . Thus, training on laparoscopic surgical simulator based on virtual reality (VR) has gradually becoming a standard in Europe at present. There are many pieces of research that validate the effectiveness of VR based laparoscopic surgery simulators (VRLS) on training surgeons [4, 5, 6]. To our knowledge, most of them employ subjective methods to study the improvement of medical students’ surgical skills through VRLS . But few papers investigate how to substantially improve the surgery skills on specific dimensions, such as physiological and psychological perspectives.
In this paper, we resort to physiological approaches to quantitatively measure the influence (cognitive load and flow experience) of VRLS on medical students.
Cognitive load theory (CLT) builds on established models of memory, including subsystems of sense, work, and long-term memory. John Sweller first put forward a systematic study in 1988 and established a theoretical hypothesis . He believed that cognitive load refers to the total amount of mental activities exerted on an individual’s cognitive system during a specific time of operation. CLT is an important learning theory, which is paid more and more attention in medical education. The medical field is a complex knowledge field. Medical workers need to integrate a variety of knowledge, skills and behaviors at a specific time and place at the same time, and make quick responses and decisions, which is prone to excessive cognitive load or even overload phenomenon. For novice physicians, complex tasks such as surgery can lead to excessive cognitive load (CL), which can have a negative impact on learning . Rasiah assessed the relationship between cognitive load and dexterity parameters and found that reduced cognitive load significantly affected learning outcomes .
Flow experience is the state of mind in which a person is fully engaged in some activity and reaches an extreme level of pleasure . It was first proposed by Csikszentmihalyi in the 1960s. He found that when people maximize their physical, mental, and mental states, they often produce the ultimate optimal experience . In simulated laparoscopic surgery, Flow experience is expressed as ”go all-out work”. Studies have shown that improving flow experience during laparoscopic surgery can improve the effectiveness of the operation, thereby improving patient safety .
To our knowledge, there is no research to directly and quantitatively explore the relationship between the flow and total cognitive load. However, some studies have shown that learners with good academic performance have higher flow experience, lower external cognitive load, and higher related cognitive load [13, 14]. Chang’s research has shown that flow experience is related to three different cognitive loads, confirming that media richness and game interaction can improve learners’ flow experience, reduce external cognitive load, and promote closely related cognitive load .
In the medical field, the methods of measuring the cognitive load of medical workers basically follow the measurement technology of cognitive load or cognitive load . The measurement methods for measuring cognitive load can generally be classified into three categories: subjective measurement, task performance, and physiological measurement. These three measurement approaches were all utilized in our study. At present, the main cognitive load measurement method is subjective measurement . Some studies have found that combining subjective mental effort indicators and objective behavioral performance indicators to form a comprehensive indicator that can reveal some important information about cognitive load [18, 19, 20]. At present, the more classic scale is the Pass scale , SWAT scale  and NASA-TLS scale .
The main advantages of the psychophysiological measurement of cognitive load are the objectivity of the measurement, the sensitivity to different cognitive processes, the non-interference of the program, and their implicitness and continuity . EEG is considered a physiological indicator, which can be used as an online and continuous cognitive load measurement method to detect subtle fluctuations in instantaneous load. Measuring the changes in alpha and theta brainwave rhythms reflects what happens in the participant’s information processing situation, even if the participant does not know these changes or cannot express them in words [24, 25]. As for the cognitive load, α is gradually suppressed. As the difficulty of the task increases, so does the amount of θ activity [26, 27, 28].
The most commonly used methods to measure flow experience are retrospective questionnaires and interviews [29, 30]. The Flow State Scale compiled by Jackson is mainly developed from the nine elements proposed by Csikszentimihalyi . Many scholars develop a new flow scale based on the characteristics and needs of VR learning situations, but a sense of control, immersion, clear goals and feedback are still indispensable dimensions in the measurement of flow experience [32, 33, 34]. At present, there are few studies on evaluating flow experience in virtual reality based on physiological indicators . Flow experience can be expressed in physical and physiological characteristics, as an objective flow indicator . In terms of EEG, some studies indicate that the correlation between EEG and flow experience under peak performance conditions, and the induction of flow experience can improve the performance of workplaces, sports fields. Frederick  proposed EEG is an objective method of measuring the flow, it is more accurate than subjective behavioral measures.
With the rapid development of wearable devices, we could obtain different modality physiological data. The most easily acquired physiological data is the heart rate. Besides, we measure the cognitive load using EEG. Three hypotheses are designed as follows:
H1: Training on VRLS could improve the performance of medical students in some dimensions.
H2: Training on VRLS could improve the flow experience and lower the cognitive load for medical students in some dimensions.
H3: The performance is positively related to flow experience and negatively related to the cognitive load.
These hypotheses are validated through the following experiments and user studies. 41 Participants were recruited using a pool of medical students which contains both undergraduates and graduates. They conducted four pre and post experiments in the training box. In the middle of pre and post experiments, they were trained on VRLS. When conducting pre and post experiments, their operation process and physiological data (heart rate and electroencephalogram) are recorded. Their performance is graded by senior surgeons using newly designed hybrid standards for fundamental tasks and Global Operative Assessment of Laparoscopic Skills (GOALS) standards  for colon resection tasks. Finally, the participants were required to fill the questionnaires about their cognitive load and flow experience.
There are two main contributions provided by this work: (1) Using multimodal sensing data (EEG and heart rate), we design a physiological approach to quantitatively measure the influence of VRLS on medical students; (2) Our experiments reveal the negative correlation between the skill performance of trainees and their cognitive load, after correlation analysis. This research can identify the potential benefits of VRLS and its improvement opportunities in laparoscopic procedure training. The remainder of this paper is organized as follows. We introduce our experiments, including participants, platform and procedure in Sect. 2. The results are documented and analyzed in Sect. 3. Section 4 provides the discussion. Section 5 concludes the paper with future work.