Immersion and haptic feedback impacts on dental anesthesia technical skills virtual reality training

Author(s):  
Elen Collaço ◽  
Elisabeti Kira ◽  
Lucas H Sallaberry ◽  
Anna C. M. Queiroz ◽  
Maria A. A. M. Machado ◽  
...  
2021 ◽  
Vol 108 (Supplement_1) ◽  
Author(s):  
R Yilmaz ◽  
A Winkler-Schwartz ◽  
N Mirchi ◽  
A Reich ◽  
R Del Maestro

Abstract Introduction Many surgical adverse events occur secondary to technical errors related to poor bimanual skills, fatigue and lack of the required expertise. We developed AI algorithms to continuously assess surgical bimanual technical performance during virtual reality simulated surgical tasks. To our knowledge, this is the first attempt in surgery to train AI algorithms to continuously monitor and evaluate bimanual skills comprehensively. Method Fifty individuals from four expertise levels (14 experts/neurosurgeons, 14 senior residents, 10 junior residents, 12 medical students) performed two virtual reality simulated surgical tasks with haptic feedback: a subpial tumor resection 5 times and a complex, realistically simulated brain tumor operation once. Each task required complete tumor removal while minimizing bleeding and damage to surrounding tissues using a simulated ultrasonic aspirator and a bipolar. A recurrent neural network continually tracked individual bimanual performance utilizing 16 performance metrics generated every 0.2 seconds. Result The recurrent neural network algorithm was successfully trained using neurosurgeons and medical students' data, learning the composites of expertise comparing high and lower skill levels. The trained algorithm outlined and monitored technical skills every 0.2 second continuously organizing performance of each surgical task into three levels: ‘excellent’, ‘average’ and ‘poor’. The percentage time spent on each level was calculated and significant differences found between all four groups for ‘excellent’ and ‘poor’ levels. Conclusion AI-powered surgical simulators provide an advanced assessment and training tool. AI's ability to continuous assess bimanual technical skills during surgery may further define the composites necessary to train surgical expertise. Abbrev AI: artificial intelligence Take-home message By advanced artificial intelligence algorithms surgeon's bi-manual technical skills can be assessed continuously, time periods of poor performance which increase the possibility of errors in performance can be identified.


2007 ◽  
Vol 30 (4) ◽  
pp. 59
Author(s):  
H. Carnahan ◽  
E. Hagemann ◽  
A. Dubrowski

A debate is emerging regarding the efficacy of proficiency based versus duration based training of technical skills. It is not clear whether the performance level attained at the end of practice (i.e., proficiency criteria), or the overall amount of practice performed during learning will best predict the retention of a technical clinical skill. The skill learned was the single-handed double square-knot. Forty two trainees learned the skill through video-based instruction and were divided into three groups (14 participants per group) each with a specific criterion time to tie the knot (10, 15, and 20 seconds). Practice continued until participants completed the knot within their criterion time. The total number of trials, and the overall practice time required to obtain each respective criterion were recorded during practice. Participants returned one-week later for a timed retention test consisting of one trial of the knot tying skill with no video instruction. A multiple regression analysis tested whether the amount of practice, the total practice time, or the criterion reached at the end of practice was the best predictor of the time taken to perform the skill during retention. This analysis showed that the number of practice trials was highly correlated with total practice time (r = .82, p = .01), therefore total practice time was withdrawn as a predictor variable from the subsequent analysis. The regression showed that the only significant predictor of retention performance was the criterion reached at the end of practice (p = .03). The number of practice trials was not found to significantly predict the retention performance (p = .87). The results support the notion that proficiency based training results in better retention of a technical clinical skill in comparison to duration based approaches. This provides evidence for the introduction of proficiency based educational approaches in technical skills curricula. Jowett N, LeBlanc V, Xeroulis G, MacRae H, Dubrowski A. Surgical skill acquisition with self-directed practice using computer-based video training. Am J Surg. 2007; 193(2):237-42. Gallagher AG, Ritter EM, Champion H, Higgins G, Fried MP, Moses G, Smith CD, Satava RM. Virtual reality simulation for the operating room: proficiency-based training as a paradigm shift in surgical skills training. Ann Surg. 2005; 241(2):364-72. Van Sickle KR, Ritter EM, McClusky DA, Lederman A, Baghai M, Gallagher AG, Smith CD. Attempted establishment of proficiency levels for laparoscopic performance on a national scale using simulation: the results from the 2004 SAGES Minimally Invasive Surgical Trainer-Virtual Reality (MIST-VR) learning center study. Surg Endosc. 2007; 21(1):5-10.


2021 ◽  
pp. 1357633X2110098
Author(s):  
Aya Sedky Adly ◽  
Afnan Sedky Adly ◽  
Mahmoud Sedky Adly ◽  
Mohammad F Ali

Introduction Rheumatoid arthritis (RA) disease is a systemic progressive inflammatory autoimmune disorder. Elderly-onset RA can be assumed as a benign form of RA. Until recently, face-to-face therapeutic sessions between health professionals and patients are usually the method of its treatment. However, during pandemics, including coronavirus disease 2019 (COVID-19), teletherapeutic sessions can extensively increase the patient safety especially in elderly patients who are more vulnerable to these infections. Thus, the aim of this study was to evaluate a novel teletherapy approach for management of elderly patients suffering from RA by utilizing laser acupuncture. Methods A teletherapy system was used for management of elderly patients suffering from RA. Sixty participants were allocated randomly into two groups and the ratio was 1:1. Patients in the first group were treated with laser acupuncture and telerehabilitation sessions, which consisted of aerobic exercise and virtual reality training. Patients in the second group received telerehabilitation sessions, which consisted of aerobic exercise and virtual reality training. Evaluation of patients was done by using the Health Assessment questionnaire (HAQ), the Rheumatoid Arthritis Quality of Life (RAQoL) questionnaire, and the analysis of interleukin-6 (IL-6), serum C-reactive protein (CRP), plasma adenosine triphosphate (ATP) concentration and plasma malondialdehyde (MDA). Results A statistically significant difference was found in CRP, RAQoL, IL-6 and MDA between the pre- and post-treatments in the first group ( p < 0.05) favouring the post-treatment group, while the HAQ showed a statistically significant difference between pre- and post-treatments ( p < 0.05) in both groups. Statistically significant post-treatment differences were also observed between the two groups ( p < 0.05) in RAQoL, CRP, ATP and MDA, favouring the first group. Discussion Laser acupuncture teletherapy could be suggested as a reliable treatment method for elderly patients suffering from RA, as it can provide a safe and effective therapeutic approach. Teletherapy provided safer access to health professionals and patients while giving a high patient satisfaction value with a relatively lower cost (ClinicalTrials.gov Identifier: NCT04684693).


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