A three-dimensional (3D) printed simulator as a feasible assessment tool for evaluating hip arthroscopy skills.

PURPOSE: The aims of this study were (1) to develop a three-dimensional (3D) printed simulator that facilitates the simulation of surgical skills for portal placement, intra-articular identification of anatomical structures and arthroscope navigation for hip arthroscopy and (2) to concurrently examine the feasibility of using this simulator as an assessment tool to evaluate trainees' surgical competencies. METHODS: A simulator was developed using a combination of medical imaging, computer-aided design, and 3D printing. A cross-sectional study was conducted with 29 participants divided into 3 subgroups (novice, intermediate and experienced). All participants performed related skills on the simulator, and their performance was evaluated using different assessment parameters. The participants' qualitative feedback regarding the simulator was also collected. The data collated from each group of participants were subsequently compared. RESULTS: Significant differences were observed between the three subgroups of participants with regard to the total checklist score (F2,26 = 11.3), total Arthroscopic Surgical Skill Evaluation score (F2,26 = 92.1), overall final global rating scale score (F2,26 = 49), number of times the participants used fluoroscopy (F2,26 = 7.4), and task completion times (F2,26 = 23.5). The participants' performance in the simulated operation was correlated with their prior clinical experience. There was mainly positive feedback with regard to the fidelity and utility of the simulator in relation to the surgeons' prior clinical experience. CONCLUSIONS: This study demonstrated that a reliable hip arthroscopic simulator can be developed for use by orthopedic surgeons to evaluate their hip arthroscopic skills before performing actual surgical operations. LEVEL OF EVIDENCE: Level III.

Eye tracking metrics of orthopedic surgeons with different competency levels who practice simulation-based hip arthroscopic procedures.

Objective: This study aimed to investigate the feasibility of using eye tracking data to identify orthopedic trainees' technical proficiency in hip arthroscopic procedures during simulation-based training. Design: A cross sectional study. Setting: A simulation-based training session for hip arthroscopy was conducted. Eye tracking devices were used to record participants' eye movements while performing simulated operations. The NASA Task Load Index survey was then used to measure subjective opinions on the perceived workload of the training. Statistical analyses were performed to determine the significance of the eye metrics and survey data. Participants: A total of 12 arthroscopic trainees, including resident doctors, junior specialist surgeons, and consultant surgeons from the Department of Orthopedics in five hospitals, participated in this study. They were divided into three subgroups based on their prior clinical experience. Results: Significant differences, including those for dwell time, number of fixations, number of saccades, saccade duration, peak velocity of the saccade, and pupil entropy, were observed among the three subgroups. Additionally, there were clear trends in the perceived workload of the simulation-based training based on feedback from the participants. Conclusion: Based on this preliminary study, a correlation was identified between the eye tracking metrics and participants' experience levels. Hence, it is feasible to apply eye tracking data as a supplementary objective assessment tool to benchmark the technical proficiency of surgical trainees in hip arthroscopy, and enhance simulation-based training.

Training surgical skills on hip arthroscopy by simulation: a survey on surgeon's perspectives.

PURPOSE: The purpose of this study is to investigate the importance of general and specific surgical skills for hip arthroscopy from the perspective of surgeons in China. Concurrently, we intend to identify the preferred type of simulation that would facilitate competency of surgical trainees in performing arthroscopy and reinforce their preparation for carrying out the actual surgical procedure. METHODS: An online survey comprising 42 questions was developed by experts in hip arthroscopy and sent to 3 online communities whose members are arthroscopic surgeons in China. The responses collected were based on a 5-point Likert scale, with an open-ended comment section. Data were analyzed using one-way AVOVA and post hoc Tukey's test. RESULTS: A total of 159 valid responses from 66 junior specialist surgeons, 68 consultant surgeons, and 25 senior consultant surgeons (from 130 institutions in 27 out of 34 provincial administrative districts in China) were collected. Cognitive ability was identified as the overall most important attribute for hip arthroscopic trainees to possess, while skills relevant to the treatment of femoroacetabular impingement (FAI) were considered as the most important specific skills by the surgeons surveyed. In addition, simulation using cadaveric specimens was considered the most favorable method for surgeons to practice their surgical skills. CONCLUSION: In designing a training program for hip arthroscopy, it is essential to incorporate features that evaluate cognitive skills. It would be helpful for trainees to specifically practice skills that are often used in the treatment of some very common diseases of the hip joint, such as FAI. Using high-fidelity physical models for simulation to train skills of hip arthroscopy could be an ideal alternative and effective way to overcome problems arising from the lack of accessibility to cadaveric specimens.

Three-dimensional printed model of impacted third molar for surgical extraction training.

OBJECTIVES: Extraction of impacted mandibular third molars is one of the most common surgical procedures performed at dental clinics; however effective training models for teaching oral surgery to dental students are limited. This study aimed to use three-dimension (3D) printing technology to develop an effective training model for impacted third molar extraction. METHODS: The data for the 3D model were digitally processed using high-resolution computed tomography, and two common, but different patterns of impacted third molars were simulated using computer-aided design. Thereafter, the model was printed using the 3D-printing technology, and the efficiency of the 3D-printed model and an animal model (pig mandible) were compared using a five-point Likert scale by 35 oral surgeons in the oral surgery department and 208 students of stomatology in the internship stage. RESULTS: The 3D-printed model consisted of three parts: a non-replaceable part (i.e., the body of the mandible and the teeth from the left first molar to the right first molar) and two replaceable parts (i.e., the part of the ascending ramus of the mandible, as well as the second and third molars). It was covered with a layer of rubber-like material to simulate the gingiva. For the comparison between the 3D-printed and animal models, a total of 205 questionnaires were collected. Both oral surgeons and students agreed that the 3D-printed model was better than the animal model in terms of total value and the anatomy of the bone and teeth, simulating the surgical procedure (p < 0.05), while the two models achieved similar results for haptic feedback of the soft tissue (p > 0.05). CONCLUSIONS: The 3D-printed model is realistic and effective for learning impacted third molar extraction and received positive feedback from students and oral surgeons. This model can significantly improve the pre-clinical skill training of dental students.

Affective Voice Interaction and Artificial Intelligence: A Research Study on the Acoustic Features of Gender and the Emotional States of the PAD Model.

New types of artificial intelligence products are gradually transferring to voice interaction modes with the demand for intelligent products expanding from communication to recognizing users' emotions and instantaneous feedback. At present, affective acoustic models are constructed through deep learning and abstracted into a mathematical model, making computers learn from data and equipping them with prediction abilities. Although this method can result in accurate predictions, it has a limitation in that it lacks explanatory capability; there is an urgent need for an empirical study of the connection between acoustic features and psychology as the theoretical basis for the adjustment of model parameters. Accordingly, this study focuses on exploring the differences between seven major "acoustic features" and their physical characteristics during voice interaction with the recognition and expression of "gender" and "emotional states of the pleasure-arousal-dominance (PAD) model." In this study, 31 females and 31 males aged between 21 and 60 were invited using the stratified random sampling method for the audio recording of different emotions. Subsequently, parameter values of acoustic features were extracted using Praat voice software. Finally, parameter values were analyzed using a Two-way ANOVA, mixed-design analysis in SPSS software. Results show that gender and emotional states of the PAD model vary among seven major acoustic features. Moreover, their difference values and rankings also vary. The research conclusions lay a theoretical foundation for AI emotional voice interaction and solve deep learning's current dilemma in emotional recognition and parameter optimization of the emotional synthesis model due to the lack of explanatory power.