Chee Kiang Lam

A Review of Computer-Generated Simulation in the Pedagogy of Cataract Surgery Training and Assessment

Virtual reality simulation is no longer an unusual term due to its application in aviation, industry, medicine, and military. The limitation of animal model in wet-lab training has necessitated the discovery of new training tools. Criteria-based surgical training can be simulated in a protected environment virtually by using computer for medical assessment and evaluation. This article reviews the pedagogical value of various virtual reality cataract surgery simulators developed, in surgical skill education and evaluation. Literature searches were conducted in ACM, IEEE Xplore, PubMed, Taylor & Francis, SciVerse, and Springer Link, covering the period from 1990 to the present. The published literature that presents methodological approach in the creation of simulation and feasibility study on performance evaluation system were examined. Evidence from the study proves that high-fidelity simulation is capable of providing objective surgical training and distinguishing the level of competency between students, residents, and surgeons in cataract surgery. Standardization and classification of training module according to the proficiency of surgical skills are considered necessary in improving validity of simulators as part of curriculum in medical education.

Virtual Reality Simulator for Phacoemulsification Cataract Surgery Education and Training

Abstract Computer systems are taking an important role in the field of medicine with the introduction of electronic biomedical devices in diagnosis and treatment, where medical records obtained from the devices are documented and processed as reference to medical panels. The capability of latest computed tomography technology in generating three-dimensional patient model for graphical representation is very informative for surgeons to plan and make decision before the operation. This initiates the idea of implementing the model into computer-generated simulator for surgical education and training. This paper presents the development of virtual reality cataract surgery simulator. Three-dimensional eye model and surgical instruments are generated as the virtual surgical environment. The system is equipped with a pair of haptic devices to provide actual sensation. The results show that the simulator is capable of providing interactive training on the main procedures of cataract surgery. It has the potential to be incorporated as part of the curriculum of medical program when the proposed future work in the end of the paper is completed.

Computer-based virtual reality simulator for phacoemulsification cataract surgery training

Recent research in virtual reality indicates that computer-based simulators are an effective technology to use for surgeons learning to improve their surgical skills in a controlled environment. This article presents the development of a virtual reality simulator for phacoemulsification cataract surgery training, which is the most common surgical technique currently being used to remove cataracts from the patient’s eyes. The procedure requires emulsifying the cloudy natural lens of the eye and restoring vision by implanting an artificial lens through a small incision. The four main procedures of cataract surgery, namely corneal incision, capsulorhexis, phacoemulsification, and intraocular lens implantation, are incorporated in the simulator for virtual surgical training by implementing several surgical techniques. The surgical activity that are applied on the anatomy of the human eye, such as incision, grasping, tearing, emulsification, rotation, and implantation, are simulated in the system by using different types of mesh modifications. A virtual reality surgical simulator is developed, and the main procedures of phacoemulsification cataract surgery are successfully simulated in the system. The simulation results of the training system show that the developed simulator is capable of generating a virtual surgical environment with faithful force feedback for medical residents and trainees to conduct their training lessons via the computer using a pair of force-feedback haptic devices. In addition, the successful simulation of the mesh modifications on the human eyeball with visual realism and faithful force feedback throughout the surgical operation shows that the developed simulator is able to serve as a virtual surgical platform for surgeons to train their surgical skills.

A review on crosstalk in myographic signals

PurposeCrosstalk in myographic signals is a major hindrance to the understanding of local information related to individual muscle function. This review aims to analyse the problem of crosstalk in electromyography and mechanomyography.MethodsAn initial search of the SCOPUS database using an appropriate set of keywords yielded 290 studies, and 59 potential studies were selected after all the records were screened using the eligibility criteria. This review on crosstalk revealed that signal contamination due to crosstalk remains a major challenge in the application of surface myography techniques. Various methods have been employed in previous studies to identify, quantify and reduce crosstalk in surface myographic signals.ResultsAlthough correlation-based methods for crosstalk quantification are easy to use, there is a possibility that co-contraction could be interpreted as crosstalk. High-definition EMG has emerged as a new technique that has been successfully applied to reduce crosstalk.ConclusionsThe phenomenon of crosstalk needs to be investigated carefully because it depends on many factors related to muscle task and physiology. This review article not only provides a good summary of the literature on crosstalk in myographic signals but also discusses new directions related to techniques for crosstalk identification, quantification and reduction. The review also provides insights into muscle-related issues that impact crosstalk in myographic signals.

Classification of Respiratory Sounds in Smokers and Non-smokers using k-NN Classifier

Respiratory sounds contain significant information on physiology and pathology of the lung and the airways. Its analysis provides vital information of the present condition of the lungs. Pulmonary disease is a major cause of ill-health throughout the world. The frequency spectrum and the amplitude of sound, i.e. tracheal or lung sounds without adventitious sound components (wheeze), may reflect airway dimension and other their pathologic changes (airways obstruction). Wheezes may have acoustic features indicating not only the presence of abnormality in the respiratory system but also the severity and locations of airway obstruction most frequently found in asthma and also found in smoker but not all smokers have airway obstruction. The significance of this study is to develop a classification system to distinguish between normal and smoker from respiratory sounds. 15 smokers and 15 non-smokers are recruited to collect respiratory sounds using Wireless Digital Stethoscope. The performance analysis of the K-Nearest Neighbor (k-NN) classifier, which uses entropy as the suitable feature, revealed that the classification accuracy on non-smokers and smokers are 89.33% and 78.67% respectively.