An Evaluation of Motion Trackers with Virtual Reality Sensor Technology in Comparison to a Marker-Based Motion Capture System Based on Joint Angles for Ergonomic Risk Assessment.

The reproduction and simulation of workplaces, and the analysis of body postures during work processes, are parts of ergonomic risk assessments. A commercial virtual reality (VR) system offers the possibility to model complex work scenarios as virtual mock-ups and to evaluate their ergonomic designs by analyzing motion behavior while performing work processes. In this study a VR tracking sensor system (HTC Vive tracker) combined with an inverse kinematic model (Final IK) was compared with a marker-based optical motion capture system (Qualisys). Marker-based optical motion capture systems are considered the gold standard for motion analysis. Therefore, Qualisys was used as the ground truth in this study. The research question to be answered was how accurately the HTC Vive System combined with Final IK can measure joint angles used for ergonomic evaluation. Twenty-six subjects were observed simultaneously with both tracking systems while performing 20 defined movements. Sixteen joint angles were analyzed. Joint angle deviations between ±6∘ and ±42∘ were identified. These high deviations must be considered in ergonomic risk assessments when using a VR system. The results show that commercial low-budget tracking systems have the potential to map joint angles. Nevertheless, substantial weaknesses and inaccuracies in some body regions must be taken into account. Recommendations are provided to improve tracking accuracy and avoid systematic errors.

Systems, Subjects, Sessions: To What Extent Do These Factors Influence EEG Data?

Lab-based electroencephalography (EEG) techniques have matured over decades of research and can produce high-quality scientific data. It is often assumed that the specific choice of EEG system has limited impact on the data and does not add variance to the results. However, many low cost and mobile EEG systems are now available, and there is some doubt as to the how EEG data vary across these newer systems. We sought to determine how variance across systems compares to variance across subjects or repeated sessions. We tested four EEG systems: two standard research-grade systems, one system designed for mobile use with dry electrodes, and an affordable mobile system with a lower channel count. We recorded four subjects three times with each of the four EEG systems. This setup allowed us to assess the influence of all three factors on the variance of data. Subjects performed a battery of six short standard EEG paradigms based on event-related potentials (ERPs) and steady-state visually evoked potential (SSVEP). Results demonstrated that subjects account for 32% of the variance, systems for 9% of the variance, and repeated sessions for each subject-system combination for 1% of the variance. In most lab-based EEG research, the number of subjects per study typically ranges from 10 to 20, and error of uncertainty in estimates of the mean (like ERP) will improve by the square root of the number of subjects. As a result, the variance due to EEG system (9%) is of the same order of magnitude as variance due to subjects (32%/sqrt(16) = 8%) with a pool of 16 subjects. The two standard research-grade EEG systems had no significantly different means from each other across all paradigms. However, the two other EEG systems demonstrated different mean values from one or both of the two standard research-grade EEG systems in at least half of the paradigms. In addition to providing specific estimates of the variability across EEG systems, subjects, and repeated sessions, we also propose a benchmark to evaluate new mobile EEG systems by means of ERP responses.

Laryngeal amyloidosis in 10 patients.

OBJECTIVES: Review the location, symptoms, treatment, and outcomes in 10 consecutive laryngeal amyloid (LA) patients. STUDY DESIGN: Pre and retrospective evaluation after treatment. METHODS: Analysis of visual and phonatory pathology and detailed description of surgery. RESULTS: Amyloid on the undersurface of both true vocal cords (TVCs) was found in two cases, uni- or bilaterally submucosally in the false vocal cords (FVCs) in eight cases, extending down into the lateral TVC in four cases, or on the undersurface of the TVCs as well in one case. The chief complaint was hoarseness and not shortness of breath. The amyloid was resected with a CO2 laser by way of microdirect laryngoscopy (MDL) on one side at a time to try to prevent anterior commissure scarring. Removal of most of the FVC improved the voice, but removal of the whole FVC to the inner thyroid perichondrium was found to be necessary to avoid recurrence from supraglottic deposits. Removal of at least 2 mm of the upper edge of a 3 to 4 mm thick submucosal deposit to the thyroarytenoid (TA) muscle along with the overlying mucosa on at least one side was necessary to improve hoarseness when amyloid was present on the undersurface of both TVCs. Partial regrowth occurred in a few months to years after partial removal. Seven patients had had one to seven prior removals. Any hard amyloid in the lateral TVC (floor of ventricle) as an inferior extension from FVC amyloid needed to be at least partially removed to avoid hoarseness from a convex vocal cord. The voice improved postoperatively in all patients. Follow-up after the first operation was 6 months to 16 years, with an average of 6.5 years. Four FVC patients required re-excision on the same side after the first operation, but none has required a third removal as of yet.

Muscle tension dysphonia in patients who use computerized speech recognition systems.

The use of speech recognition systems as a replacement for other types of transcription systems is increasing rapidly, partly because many people are unable to use conventional keyboards as a result of upper-extremity repetitive strain injury (RSI). However, the frequent or continuous use of such systems can cause muscle tension dysphonia in some patients. The scientific literature suggests that there is an association between upper-extremity RSI and muscle tension dysphonia. We present a retrospective case series of five patients with workplace upper-extremity RSI who developed muscle tension dysphonia soon after they began using discrete computerized speech recognition software. The diagnosis of dysphonia was based on laryngovideostroboscopy, acoustic analyses, and voice load testing. All patients had normal voice when using everyday speech, but speaking into the computer resulted in the rapid onset of aperiodicity, strain, and a decrease in fundamental frequency. In three of the five patients, laryngovideostroboscopy showed posterior glottic overapproximation, but no other abnormalities. Treatment was centered on voice therapy and avoidance of long periods of using computerized speech recognition systems. The condition of three of the five patients improved with therapy. We conclude that computer speech recognition programs can lead to the onset of muscle tension dysphonia in some patients. These patients can be successfully treated with voice therapy.