BACKGROUND: Operating rooms are identified as being one of the noisiest of clinical environments, and intraoperative noise is associated with adverse effects on staff and patient safety. Simulation-based experiments would offer controllable and safe venues for investigating this noise problem. However, realistic simulation of the clinical auditory environment is rare in current simulators. Therefore, we retrofitted our operating room simulator to be able to produce immersive auditory simulations with the use of typical sound sources encountered during surgeries. Then, we tested the hypothesis that anesthesia residents would perceive greater task load and fatigue while giving simulated lunch breaks in noisy environments rather than in quiet ones. As a secondary objective, we proposed and tested the plausibility of a novel psychometric instrument for the assessment of stress. METHODS: In this simulation-based, randomized, repeated-measures, crossover study, 2 validated psychometric survey instruments, the NASA Task Load Index (NASA-TLX), composed of 6 items, and the Swedish Occupational Fatigue Inventory (SOFI), composed of 5 items, were used to assess perceived task load and fatigue, respectively, in first-year anesthesia residents. Residents completed the psychometric instruments after giving lunch breaks in quiet and noisy intraoperative environments (soundscapes). The effects of soundscape grouping on the psychometric instruments and their comprising items were analyzed with a split-plot analysis. A model for a new psychometric instrument for measuring stress that combines the NASA-TLX and SOFI instruments was proposed, and a factor analysis was performed on the collected data to determine the model’s plausibility. RESULTS: Twenty residents participated in this study. Multivariate analysis of variance showed an effect of soundscape grouping on the combined NASA-TLX and SOFI instrument items (P = 0.003) and the comparisons of univariate item reached significance for the NASA Temporal Demand item (P = 0.0004) and the SOFI Lack of Energy item (P = 0.001). Factor analysis extracted 4 factors, which were assigned the following construct names for model development: Psychological Task Load, Psychological Fatigue, Acute Physical Load, and Performance-Chronic Physical Load. Six of the 7 fit tests used in the partial confirmatory factor analysis were positive when we fitted the data to the proposed model, suggesting that further validation is warranted. CONCLUSIONS: This study provides evidence that noise during surgery can increase feelings of stress, as measured by perceived task load and fatigue levels, in anesthesiologists and adds to the growing literature pointing to an overall adverse impact of clinical noise on caregivers and patient safety. The psychometric model proposed in this study for assessing perceived stress is plausible based on factor analysis and will be useful for characterizing the impact of the clinical environment on subject stress levels in future investigations.

Objective: Using a custom mobile application to evaluate the reliability and validity of the Component Timed-Up-and-Go test to assess prosthetic mobility in people with lower limb amputation. Design: Cross-sectional design. Setting: National conference for people with limb loss. Subjects: A total of 118 people with non-vascular cause of lower limb amputation participated. Subjects had a mean age of 48 (±13.7) years and were an average of 10 years post amputation. Of them, 54% ( n = 64) of subjects were male. Intervention: None. Main measure: The Component Timed-Up-and-Go was administered using a mobile iPad application, generating a total time to complete the test and five component times capturing each subtask (sit to stand transitions, linear gait, turning) of the standard timed-up-and-go test. The outcome underwent test–retest reliability using intraclass correlation coefficients (ICCs) and convergent validity analyses through correlation with self-report measures of balance and mobility. Results: The Component Timed-Up-and-Go exhibited excellent test–retest reliability with ICCs ranging from .98 to .86 for total and component times. Evidence of discriminative validity resulted from significant differences in mean total times between people with transtibial (10.1 (SD: ±2.3)) and transfemoral (12.76 (SD: ±5.1) amputation, as well as significant differences in all five component times ( P < .05). Convergent validity of the Component Timed-Up-and-Go was demonstrated through moderate correlations with the PLUS-M ( r_s = −.56). Conclusion: The Component Timed-Up-and-Go is a reliable and valid clinical tool for detailed assessment of prosthetic mobility in people with non-vascular lower limb amputation. The iPad application provided a means to easily record data, contributing to clinical utility.

Background: Current standard audible medical alarms are difficult to learn and distinguish from one another. Auditory icons represent a new type of alarm that has been shown to be easier to learn and identify in laboratory settings by lay subjects. In this study, we test the hypothesis that icon alarms are easier to learn and identify than standard alarms by anesthesia providers in a simulated clinical setting. Methods: Twenty anesthesia providers were assigned to standard or icon groups. Experiments were conducted in a simulated intensive care unit. After a brief group-specific alarm orientation, subjects identified patient-associated alarm sounds during the simulation and logged responses via a tablet computer. Each subject participated in the simulation twice and was exposed to 32 alarm annunciations. Primary outcome measures were response accuracy and response times. Secondary outcomes included assessments of perceived fatigue and task load. Results: Overall accuracy rate in the standard alarm group was 43% (mean) and in the icon group was 88% (mean). Subjects in the icon group were 26.1 (odds ratio [98.75% CI, 8.4 to 81.5; P < 0.001]) times more likely to correctly identify an alarm. Response times in the icon group were shorter than in the standard alarm group (12 vs. 15 s, difference 3 s [98.75% CI ,1 to 5; P < 0.001]). Conclusions: Under our simulated conditions, anesthesia providers more correctly and quickly identified icon alarms than standard alarms. Subjects were more likely to perceive higher fatigue and task load when using current standard alarms than icon alarms.

Tele-rehabilitation of patients with gait abnormalities could benefit from continuous monitoring of knee joint angle in the home and community. Continuous monitoring with mobile devices can be restricted by the number of body-worn sensors, signal bandwidth, and the complexity of operating algorithms. Therefore, this paper proposes a novel algorithm for estimating knee joint angle using lower limb angular velocity, obtained with only two leg-mounted gyroscopes. This gyroscope only (GO) algorithm calculates knee angle by integrating gyroscope-derived knee angular velocity signal, and thus avoids reliance on noisy accelerometer data. To eliminate drift in gyroscope data, a zero-angle update derived from a characteristic point in the knee angular velocity is applied to every stride. The concurrent validity and construct convergent validity of the GO algorithm was determined with two existing IMU-based algorithms, complementary and Kalman filters, and an optical motion capture system, respectively. Bland–Altman analysis indicated a high-level of agreement between the GO algorithm and other measures of knee angle.