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Aksoy ME, Kocaoglu B, İzzetoglu K, Agrali A, Yoner SI, Polat MD, Kayaalp ME, Yozgatli TK, Kaya A, Becker R. Assessment of learning in simulator-based arthroscopy training with the diagnostic arthroscopy skill score (DASS) and neurophysiological measures. Knee Surg Sports Traumatol Arthrosc 2023; 31:5332-5345. [PMID: 37743389 DOI: 10.1007/s00167-023-07571-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/02/2023] [Indexed: 09/26/2023]
Abstract
PURPOSE Virtual arthroscopic training has become increasingly popular. However, there is a lack of efficiency-based tracking of the trainee, which may be critical for determining the specifics of training programs and adapting them for the needs of each trainee. This study aims to evaluate and compare the measures obtained with a non-invasive neurophysiological method with The Diagnostic Arthroscopy Skill Score (DASS), a commonly used assessment tool for evaluating arthroscopic skills. METHODS The study collected simulator performance scores, consisting of "Triangulation Right Hand", "Triangulation Left Hand", "Catch the Stars" and "Three Rings" and DASS scores from 22 participants (11 novices, 11 experts). These scores were obtained while participants underwent a structured program of exercises for the fundamentals of arthroscopic surgery training (FAST) and knee module using a simulator-based arthroscopy device. During the evaluation, data on oxy-hemoglobin and deoxy-hemoglobin levels in the prefrontal cortex were collected using the Functional Near-Infrared Spectroscopy (fNIRS) imaging system. Performance scores, DASS scores, and fNIRS data were subsequently analyzed to determine any correlation between performance and cortex activity. RESULTS The simulator performance scores and the DASSPart2 scores were significantly higher in the expert group compared to the novice group (200.1 ± 28.5 vs 172.5 ± 48.9, p = 0.04 and 9.4 ± 5.6 vs. 5.4 ± 5.6 p = 0.02). In the expert group, fNIRS data showed a significantly lower prefrontal cortex activation during fundamental tasks in the FAST module, indicating significantly more efficient mental resource use. CONCLUSION The analysis of cognitive workload changes during simulation-based arthroscopy training revealed a significant correlation between the trainees' DASS scores and fNIRS data. This correlation suggests the potential use of fNIRS data and DASS scores as additional metrics to create adaptive training protocols for each participant. By incorporating these metrics, the training process can be optimized, leading to more efficient arthroscopic training and better preparedness for clinical operations. LEVEL OF EVIDENCE III.
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Affiliation(s)
- Mehmet Emin Aksoy
- Department of Biomedical Device Technology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
- CASE (Center of Advanced Simulation and Education), Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Baris Kocaoglu
- Department of Orthopedics and Traumatology, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.
| | - Kurtulus İzzetoglu
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, 19104, USA
| | - Atahan Agrali
- Department of Biomedical Device Technology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Serhat Ilgaz Yoner
- Department of Biomedical Device Technology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Mert Deniz Polat
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, 19104, USA
| | - Mahmut Enes Kayaalp
- Center for Sports Medicine, University of Pittsburgh, Pittsburgh, PA, 15260, USA
- Orthopedics and Traumatology, Istanbul Kartal Research and Training Hospital, Istanbul, Turkey
- Center of Orthopedics and Traumatology, University of Brandenburg, Brandenburg/Havel, Germany
| | - Tahir Koray Yozgatli
- Department of Orthopedics and Traumatology, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Alper Kaya
- Department of Orthopedics and Traumatology, Faculty of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Roland Becker
- Center of Orthopedics and Traumatology, University of Brandenburg, Brandenburg/Havel, Germany
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Betts K, Reddy P, Galoyan T, Delaney B, McEachron DL, Izzetoglu K, Shewokis PA. An Examination of the Effects of Virtual Reality Training on Spatial Visualization and Transfer of Learning. Brain Sci 2023; 13:890. [PMID: 37371368 DOI: 10.3390/brainsci13060890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
Spatial visualization ability (SVA) has been identified as a potential key factor for academic achievement and student retention in Science, Technology, Engineering, and Mathematics (STEM) in higher education, especially for engineering and related disciplines. Prior studies have shown that training using virtual reality (VR) has the potential to enhance learning through the use of more realistic and/or immersive experiences. The aim of this study was to investigate the effect of VR-based training using spatial visualization tasks on participant performance and mental workload using behavioral (i.e., time spent) and functional near infrared spectroscopy (fNIRS) brain-imaging-technology-derived measures. Data were collected from 10 first-year biomedical engineering students, who engaged with a custom-designed spatial visualization gaming application over a six-week training protocol consisting of tasks and procedures that varied in task load and spatial characteristics. Findings revealed significant small (Cohen's d: 0.10) to large (Cohen's d: 2.40) effects of task load and changes in the spatial characteristics of the task, such as orientation or position changes, on time spent and oxygenated hemoglobin (HbO) measures from all the prefrontal cortex (PFC) areas. Transfer had a large (d = 1.37) significant effect on time spent and HbO measures from right anterior medial PFC (AMPFC); while training had a moderate (d = 0.48) significant effect on time spent and HbR measures from left AMPFC. The findings from this study have important implications for VR training, research, and instructional design focusing on enhancing the learning, retention, and transfer of spatial skills within and across various VR-based training scenarios.
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Affiliation(s)
- Kristen Betts
- School of Education, Drexel University, Philadelphia, PA 19104, USA
| | - Pratusha Reddy
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | - Tamara Galoyan
- School of Education, Drexel University, Philadelphia, PA 19104, USA
| | - Brian Delaney
- School of Communication and Journalism, Auburn University, Auburn, AL 36849, USA
| | - Donald L McEachron
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | - Kurtulus Izzetoglu
- School of Education, Drexel University, Philadelphia, PA 19104, USA
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | - Patricia A Shewokis
- School of Education, Drexel University, Philadelphia, PA 19104, USA
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA
- College of Nursing & Health Professions, Drexel University, Philadelphia, PA 19104, USA
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Reddy P, Shewokis PA, Izzetoglu K. Individual differences in skill acquisition and transfer assessed by dual task training performance and brain activity. Brain Inform 2022; 9:9. [PMID: 35366168 PMCID: PMC8976865 DOI: 10.1186/s40708-022-00157-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 03/08/2022] [Indexed: 11/23/2022] Open
Abstract
Assessment of expertise development during training program primarily consists of evaluating interactions between task characteristics, performance, and mental load. Such a traditional assessment framework may lack consideration of individual characteristics when evaluating training on complex tasks, such as driving and piloting, where operators are typically required to execute multiple tasks simultaneously. Studies have already identified individual characteristics arising from intrinsic, context, strategy, personality, and preference as common predictors of performance and mental load. Therefore, this study aims to investigate the effect of individual difference in skill acquisition and transfer using an ecologically valid dual task, behavioral, and brain activity measures. Specifically, we implemented a search and surveillance task (scanning and identifying targets) using a high-fidelity training simulator for the unmanned aircraft sensor operator, acquired behavioral measures (scan, not scan, over scan, and adaptive target find scores) using simulator-based analysis module, and measured brain activity changes (oxyhemoglobin and deoxyhemoglobin) from the prefrontal cortex (PFC) using a portable functional near-infrared spectroscopy (fNIRS) sensor array. The experimental protocol recruited 13 novice participants and had them undergo three easy and two hard sessions to investigate skill acquisition and transfer, respectively. Our results from skill acquisition sessions indicated that performance on both tasks did not change when individual differences were not accounted for. However inclusion of individual differences indicated that some individuals improved only their scan performance (Attention-focused group), while others improved only their target find performance (Accuracy-focused group). Brain activity changes during skill acquisition sessions showed that mental load decreased in the right anterior medial PFC (RAMPFC) in both groups regardless of individual differences. However, mental load increased in the left anterior medial PFC (LAMPFC) of Attention-focused group and decreased in the Accuracy-focused group only when individual differences were included. Transfer results showed no changes in performance regardless of grouping based on individual differences; however, mental load increased in RAMPFC of Attention-focused group and left dorsolateral PFC (LDLPFC) of Accuracy-focused group. Efficiency and involvement results suggest that the Attention-focused group prioritized the scan task, while the Accuracy-focused group prioritized the target find task. In conclusion, training on multitasks results in individual differences. These differences may potentially be due to individual preference. Future studies should incorporate individual differences while assessing skill acquisition and transfer during multitask training.
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Affiliation(s)
- Pratusha Reddy
- School of Biomedical Engineering, Science and Health Systems, Drexel University, 3508 Market St Suite 100, Philadelphia, PA, 19104, USA
| | - Patricia A Shewokis
- School of Biomedical Engineering, Science and Health Systems, Drexel University, 3508 Market St Suite 100, Philadelphia, PA, 19104, USA.,Nutrition Sciences Department-College of Nursing and Health Professions, Drexel University, 1601 Cherry St Free Parkway, Philadelphia, PA, 19102, USA.,School of Education, 3401 Market Street 3rd Floor Suite 3000, Philadelphia, PA, 19104, USA
| | - Kurtulus Izzetoglu
- School of Biomedical Engineering, Science and Health Systems, Drexel University, 3508 Market St Suite 100, Philadelphia, PA, 19104, USA. .,School of Education, 3401 Market Street 3rd Floor Suite 3000, Philadelphia, PA, 19104, USA.
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A Novel Application of Levenshtein Distance for Assessment of High-Level Motor Planning Underlying Performance During Learning of Complex Motor Sequences. JOURNAL OF MOTOR LEARNING AND DEVELOPMENT 2020. [DOI: 10.1123/jmld.2018-0060] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Few studies have examined high-level motor plans underlying cognitive-motor performance during practice of complex action sequences. These investigations have assessed performance through fairly simple metrics without examining how practice affects the structures of action sequences. By adapting the Levenshtein distance (LD) method to the motor domain, we propose a computational approach to accurately capture performance dynamics during practice of action sequences. Practice performance dynamics were assessed by computing the LD based on the number of insertions, deletions, and substitutions of actions needed to transform any sequence into a reference sequence (having a minimal number of actions to complete the task). Also, combining LD-based performance with mental workload metrics allowed assessment of cognitive-motor efficiency dynamics. This approach was tested on the Tower of Hanoi task. The findings revealed that throughout practice this method could capture: i) action sequence performance improvements as indexed by a reduced LD (decrease of insertions and substitutions), ii) structural modifications of the high-level plans, iii) an attenuation of mental workload, and iv) enhanced cognitive-motor efficiency. This effort complements prior work examining the practice of complex action sequences in healthy adults and has potential for probing cognitive-motor impairment in clinical populations as well as the development/assessment of cognitive robotic controllers.
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Jaquess KJ, Lo LC, Oh H, Lu C, Ginsberg A, Tan YY, Lohse KR, Miller MW, Hatfield BD, Gentili RJ. Changes in Mental Workload and Motor Performance Throughout Multiple Practice Sessions Under Various Levels of Task Difficulty. Neuroscience 2018; 393:305-318. [PMID: 30266685 DOI: 10.1016/j.neuroscience.2018.09.019] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 09/12/2018] [Accepted: 09/17/2018] [Indexed: 11/28/2022]
Abstract
The allocation of mental workload is critical to maintain cognitive-motor performance under various demands. While mental workload has been investigated during performance, limited efforts have examined it during cognitive-motor learning, while none have concurrently manipulated task difficulty. It is reasonable to surmise that the difficulty level at which a skill is practiced would impact the rate of skill acquisition and also the rate at which mental workload is reduced during learning (relatively slowed for challenging compared to easier tasks). This study aimed to monitor mental workload by assessing cortical dynamics during a task practiced under two difficulty levels over four days while perceived task demand, performance, and electroencephalography (EEG) were collected. As expected, self-reported mental workload was reduced, greater working memory engagement via EEG theta synchrony was observed, and reduced cortical activation, as indexed by progressive EEG alpha synchrony was detected during practice. Task difficulty was positively related to the magnitude of alpha desynchrony and accompanied by elevations in the theta-alpha ratio. Counter to expectation, the absence of an interaction between task difficulty and practice days for both theta and alpha power indicates that the refinement of mental processes throughout learning occurred at a comparable rate for both levels of difficulty. Thus, the assessment of brain dynamics was sensitive to the rate of change of cognitive workload with practice, but not to the degree of difficulty. Future work should consider a broader range of task demands and additional measures of brain processes to further assess this phenomenon.
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Affiliation(s)
- Kyle J Jaquess
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA
| | - Li-Chuan Lo
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA
| | - Hyuk Oh
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA
| | - Calvin Lu
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA
| | - Andrew Ginsberg
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA
| | - Ying Ying Tan
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA; Defense Science and Technology Agency, Singapore
| | - Keith R Lohse
- Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, UT, USA
| | | | - Bradley D Hatfield
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA
| | - Rodolphe J Gentili
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, MD, USA; Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA; Maryland Robotics Center, University of Maryland, College Park, MD, USA.
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Modi HN, Singh H, Yang GZ, Darzi A, Leff DR. A decade of imaging surgeons' brain function (part II): A systematic review of applications for technical and nontechnical skills assessment. Surgery 2017; 162:1130-1139. [PMID: 29079277 DOI: 10.1016/j.surg.2017.09.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/31/2017] [Indexed: 11/16/2022]
Abstract
BACKGROUND Functional neuroimaging technologies enable assessment of operator brain function and can deepen our understanding of skills learning, ergonomic optima, and cognitive processes in surgeons. Although there has been a critical mass of data detailing surgeons' brain function, this literature has not been reviewed systematically. METHODS A systematic search of original neuroimaging studies assessing surgeons' brain function and published up until November 2016 was conducted using Medline, Embase, and PsycINFO databases. RESULTS Twenty-seven studies fulfilled the inclusion criteria, including 3 feasibility studies, 14 studies exploring the neural correlates of technical skill acquisition, and the remainder investigating brain function in the context of intraoperative decision-making (n = 1), neurofeedback training (n = 1), robot-assisted technology (n = 5), and surgical teaching (n = 3). Early stages of learning open surgical tasks (knot-tying) are characterized by prefrontal cortical activation, which subsequently attenuates with deliberate practice. However, with complex laparoscopic skills (intracorporeal suturing), prefrontal cortical engagement requires substantial training, and attenuation occurs over a longer time course, after years of refinement. Neurofeedback and interventions that improve neural efficiency may enhance technical performance and skills learning. CONCLUSION Imaging surgeons' brain function has identified neural signatures of expertise that might help inform objective assessment and selection processes. Interventions that improve neural efficiency may target skill-specific brain regions and augment surgical performance.
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Affiliation(s)
- Hemel Narendra Modi
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Harsimrat Singh
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Guang-Zhong Yang
- Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom
| | - Ara Darzi
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom; Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom
| | - Daniel Richard Leff
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom; Hamlyn Centre for Robotic Surgery, Imperial College London, London, United Kingdom.
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Shuggi IM, Oh H, Shewokis PA, Gentili RJ. Mental workload and motor performance dynamics during practice of reaching movements under various levels of task difficulty. Neuroscience 2017; 360:166-179. [PMID: 28757242 DOI: 10.1016/j.neuroscience.2017.07.048] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Revised: 07/17/2017] [Accepted: 07/19/2017] [Indexed: 10/19/2022]
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Greenawald L, Uribe J, Shariff F, Syed M, Shaikh M, Mann B, Pezzi C, Damewood R, Shewokis PA, Castellanos A, Lind DS. Construct validity of a novel, objective evaluation tool for the basics of open laparotomy training using a simulated model. Am J Surg 2017; 214:152-157. [DOI: 10.1016/j.amjsurg.2015.12.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 12/01/2015] [Accepted: 12/08/2015] [Indexed: 11/25/2022]
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Liu Y, Ayaz H, Shewokis PA. Mental workload classification with concurrent electroencephalography and functional near-infrared spectroscopy. BRAIN-COMPUTER INTERFACES 2017. [DOI: 10.1080/2326263x.2017.1304020] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Yichuan Liu
- School of Biomedical Engineering, Science & Health Systems, Drexel University, Philadelphia, PA, USA
- Cognitive Neuroengineering and Quantitative Experimental Research (CONQUER) Collaborative, Drexel University, Philadelphia, PA, USA
| | - Hasan Ayaz
- School of Biomedical Engineering, Science & Health Systems, Drexel University, Philadelphia, PA, USA
- Cognitive Neuroengineering and Quantitative Experimental Research (CONQUER) Collaborative, Drexel University, Philadelphia, PA, USA
- Department of Family and Community Health, University of Pennsylvania, Philadelphia, PA, USA
- The Division of General Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Patricia A. Shewokis
- School of Biomedical Engineering, Science & Health Systems, Drexel University, Philadelphia, PA, USA
- Cognitive Neuroengineering and Quantitative Experimental Research (CONQUER) Collaborative, Drexel University, Philadelphia, PA, USA
- Nutrition Sciences Department, College of Nursing and Health Professions, Drexel University, Philadelphia, PA, USA
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