Validating Metrics for a Mastoidectomy Simulator

Abstract. One of the primary barriers to the acceptance of surgical simulators is that most simulators still require a significant amount of an instructing surgeon's time to evaluate and provide feedback to the students using them. Thus, an important area of research in this field is the development of metrics that can enable a simulator to be an essentially self-contained teaching tool, capable of identifying and explaining the user's weaknesses. However, it is essential that these metrics be validated in able to ensure that the evaluations provided by the "virtual instructor" match those that the real instructor would provide were he/she present. We have previously proposed a number of algorithms for providing automated feedback in the context of a mastoidectomy simulator. In this paper, we present the results of a user study in which we attempted to establish construct validity (with inter-rater reliability) for our simulator itself and to validate our metrics. Fifteen subjects (8 experts, 7 novices) were asked to perform two virtual mastoidectomies. Each virtual procedure was recorded, and two experienced instructing surgeons assigned global scores that were correlated with subjects' experience levels. We then validated our metrics by correlating the scores generated by our algorithms with the instructors' global ratings, as well as with metric-specific sub-scores assigned by one of the instructors

Comprehensive measures of sound exposures in cinemas using smart phones

OBJECTIVES Sensorineural hearing loss from sound overexposure has a considerable prevalence. Identification of sound hazards is crucial, as prevention, due to a lack of definitive therapies, is the sole alternative to hearing aids. One subjectively loud, yet little studied, potential sound hazard is movie theaters. This study uses smart phones to evaluate their applicability as a widely available, validated sound pressure level (SPL) meter. Therefore, this study measures sound levels in movie theaters to determine whether sound levels exceed safe occupational noise exposure limits and whether sound levels in movie theaters differ as a function of movie, movie theater, presentation time, and seat location within the theater. DESIGN Six smart phones with an SPL meter software application were calibrated with a precision SPL meter and validated as an SPL meter. Additionally, three different smart phone generations were measured in comparison to an integrating SPL meter. Two different movies, an action movie and a children's movie, were measured six times each in 10 different venues (n = 117). To maximize representativeness, movies were selected focusing on large release productions with probable high attendance. Movie theaters were selected in the San Francisco, CA, area based on whether they screened both chosen movies and to represent the largest variety of theater proprietors. Measurements were analyzed in regard to differences between theaters, location within the theater, movie, as well as presentation time and day as indirect indicator of film attendance. RESULTS The smart phone measurements demonstrated high accuracy and reliability. Overall, sound levels in movie theaters do not exceed safe exposure limits by occupational standards. Sound levels vary significantly across theaters and demonstrated statistically significant higher sound levels and exposures in the action movie compared to the children's movie. Sound levels decrease with distance from the screen. However, no influence on time of day or day of the week as indirect indicator of film attendance could be found. CONCLUSIONS Calibrated smart phones with an appropriate software application as used in this study can be utilized as a validated SPL meter. Because of the wide availability, smart phones in combination with the software application can provide high quantity recreational sound exposure measurements, which can facilitate the identification of potential noise hazards. Sound levels in movie theaters decrease with distance to the screen, but do not exceed safe occupational noise exposure limits. Additionally, there are significant differences in sound levels across movie theaters and movies, but not in presentation time

Otologic manifestations of relapsing polychondritis. Review of literature and report of nine cases

OBJECTIVE: Relapsing polychondritis (RP) is an episodic disease most likely of autoimmune etiology, characterized by recurrent inflammation of cartilaginous structures. METHODS: Retrospective case study at two tertiary referral centers with presentation of nine patients with otologic involvement of RP, review of the spectrum of otologic disorders seen, and treatment. RESULTS: The clinical course of otologic manifestations of RP was highly variable and ranged from mild to moderate. In 6/9 patients there was an association with other autoimmune disorders. In addition to recurrent auricular chondritis, which was present in 8/9 patients, our patients had otitis externa, chronic myringitis, Eustachian tube dysfunction, conductive hearing loss, sensorineural hearing loss, and tinnitus. All patients had their diagnosis of RP made on the basis of their otologic involvement and the response to systemic corticosteroids. CONCLUSION: The diagnosis of RP is primarily clinical, but laboratory studies and biopsy may contribute as well. Once the diagnosis is suspected, the otolaryngologist should consider consultation with a rheumatologist to assist in the management of additional systemic manifestations

Factors influencing classification of frequency following responses to speech and music stimuli

Successful mapping of meaningful labels to sound input requires accurate representation of that sound’s acoustic variances in time and spectrum. For some individuals, such as children or those with hearing loss, having an objective measure of the integrity of this representation could be useful. Classification is a promising machine learning approach which can be used to objectively predict a stimulus label from the brain response. This approach has been previously used with auditory evoked potentials (AEP) such as the frequency following response (FFR), but a number of key issues remain unresolved before classification can be translated into clinical practice. Specifically, past efforts at FFR classification have used data from a given subject for both training and testing the classifier. It is also unclear which components of the FFR elicit optimal classification accuracy. To address these issues, we recorded FFRs from 13 adults with normal hearing in response to speech and music stimuli. We compared labeling accuracy of two cross-validation classification approaches using FFR data: (1) a more traditional method combining subject data in both the training and testing set, and (2) a “leave-one-out” approach, in which subject data is classified based on a model built exclusively from the data of other individuals. We also examined classification accuracy on decomposed and time-segmented FFRs. Our results indicate that the accuracy of leave-one-subject-out cross validation approaches that obtained in the more conventional cross-validation classifications while allowing a subject’s results to be analysed with respect to normative data pooled from a separate population. In addition, we demonstrate that classification accuracy is highest when the entire FFR is used to train the classifier. Taken together, these efforts contribute key steps toward translation of classification-based machine learning approaches into clinical practice

Tinnitus suppression by low-rate electric stimulation and its electrophysiological mechanisms.

Tinnitus is a phantom sensation of sound in the absence of external stimulation. However, external stimulation, particularly electric stimulation via a cochlear implant, has been shown to suppress tinnitus. Different from traditional methods of delivering speech sounds or high-rate (>2000 Hz) stimulation, the present study found a unique unilaterally-deafened cochlear implant subject whose tinnitus was completely suppressed by a low-rate (<100 Hz) stimulus, delivered at a level softer than tinnitus to the apical part of the cochlea. Taking advantage of this novel finding, the present study compared both event-related and spontaneous cortical activities in the same subject between the tinnitus-present and tinnitus-suppressed states. Compared with the results obtained in the tinnitus-present state, the low-rate stimulus reduced cortical N100 potentials while increasing the spontaneous alpha power in the auditory cortex. These results are consistent with previous neurophysiological studies employing subjects with and without tinnitus and shed light on both tinnitus mechanism and treatment

The Effect of Virtual Haptic Training on Real Surgical Drilling Proficiency

This sketch presents the design and preliminary results of a study that investigates the transference of motor skills learned in a haptic-enabled virtual environment to performance on a surgically-relevant task in the real world. The chosen task, which requires skills similar to those needed in a number of surgical procedures, including stapedotomy and cochleostomy, is drilling holes through an eggshell using a surgical drill without penetrating the egg’s inner membrane. Results reflect a learning curve for task proficiency and indicate a benefit to haptic training, but a planned follow-up study will be required for this claim to be statistically conclusive. 1

Visuohaptic Simulation of Bone Surgery

Abstract—We present techniques for the visual and haptic simulation of bone surgery, with a specific focus on procedures involving the temporal bone and the mandible. We discuss our approaches to graphic and haptic rendering and interactive modification of volumetric data, specifically focusing on generating force-feedback effects that are relevant to bone drilling. We then discuss how our rendering primitives and simulation architecture can be used to build surgical training techniques that are not available in traditional cadaver-based training labs, offering new possibilities for surgical education. In particular, we discuss the automatic computation of performance metrics that can provide real-time feedback about a trainee’s performance in our simulator. We also present results from an experimental study evaluating the construct validity of our simulation and the validity of our performance metrics