Observational study of anaesthesia workflow to evaluate physical workspace design and layout.

BACKGROUND: The safety and efficiency of anaesthesia care depend on the design of the physical workspace. However, little is known about the influence that workspace design has on the ability to perform complex operating theatre (OT) work. The aim of this study was to observe the relationship between task switching and physical layout, and then use the data collected to design and assess different anaesthesia workspace layouts. METHODS: In this observational study, six videos of anaesthesia providers were analysed from a single centre in the United States. A task analysis of workflow during the maintenance phase of anaesthesia was performed by categorising tasks. The data supported evaluations of alternative workspace designs. RESULTS: An anaesthesia provider's time was occupied primarily by three tasks: patient (mean: 30.0% of total maintenance duration), electronic medical record (26.6%), and visual display tasks (18.6%). The mean time between task switches was 6.39 s. With the current workspace layout, the anaesthesia provider was centred toward the patient for approximately half of the maintenance duration. Evaluating the alternative layout designs showed how equipment arrangements could improve task switching and increase the provider's focus towards the patient and visual displays. CONCLUSIONS: Our study showed that current operating theatre layouts do not fit work demands. We report a simple method that facilitates a quick layout design assessment and showed that the anaesthesia workspace can be improved to better suit workflow and patient care. Overall, this arrangement could reduce anaesthesia workload while improving task flow efficiency and potentially the safety of care.

Developing a 3D Gestural Interface for Anesthesia-Related Human-Computer Interaction Tasks Using Both Experts and Novices.

OBJECTIVE: The purpose of this research was to compare gesture-function mappings for experts and novices using a 3D, vision-based, gestural input system when exposed to the same context of anesthesia tasks in the operating room (OR). BACKGROUND: 3D, vision-based, gestural input systems can serve as a natural way to interact with computers and are potentially useful in sterile environments (e.g., ORs) to limit the spread of bacteria. Anesthesia providers' hands have been linked to bacterial transfer in the OR, but a gestural input system for anesthetic tasks has not been investigated. METHODS: A repeated-measures study was conducted with two cohorts: anesthesia providers (i.e., experts) ( N = 16) and students (i.e., novices) ( N = 30). Participants chose gestures for 10 anesthetic functions across three blocks to determine intuitive gesture-function mappings. Reaction time was collected as a complementary measure for understanding the mappings. RESULTS: The two gesture-function mapping sets showed some similarities and differences. The gesture mappings of the anesthesia providers showed a relationship to physical components in the anesthesia environment that were not seen in the students' gestures. The students also exhibited evidence related to longer reaction times compared to the anesthesia providers. CONCLUSION: Domain expertise is influential when creating gesture-function mappings. However, both experts and novices should be able to use a gesture system intuitively, so development methods need to be refined for considering the needs of different user groups. APPLICATION: The development of a touchless interface for perioperative anesthesia may reduce bacterial contamination and eventually offer a reduced risk of infection to patients.

A review on development approaches for 3D gestural embodied human-computer interaction systems.

The integration of 3D gestural embodied human-computer interaction (eHCI) has provided an avenue for contactless interaction with systems. The design of gestural systems employs two approaches: Technology-based approach and Human-based approach. This study reviews the existing literature on development approaches for 3D gestural eHCI to understand the current state of research in 3D gestural eHCI using these approaches and identify potential areas for future exploration. Articles were gathered from three databases: PsycInfo, Science Direct and IEEE Xplore. A total of 35 articles were identified, of which 18 used human-based methods, and 17 used technology-based methods. Findings shed light on inconsistencies between developers and users in preferred hand gesture poses and identify factors influencing users' gesture choice. Implementation of the consolidated findings has the potential to improve human readiness for 3D gestural eHCI technologies.

Redefining the human factors approach to 3D gestural HCI by exploring the usability-accuracy tradeoff in gestural computer systems.

3D gestural technology for HCI could transform the way people interact with computing systems. There are traditionally two approaches to developing gestural technology systems: a human-based approach where usability is maximized and a technology-based approach where system accuracy is maximized. The tradeoff between usability and accuracy may negatively affect the overall trust and reliability in the system. Therefore, this study seeks to redefine the human-based approach to gestural system development by introducing a bottom-up approach to identifying the lower-level features that produce a gesture, thus allowing the technology to accurately recognize features. A user elicitation study was performed, and gestures were classified according to a novel feature extraction gesture taxonomy and a traditional taxonomy of classifying gestures as a unit. The feature-extraction approach revealed several advantages because it fosters a bottom-up approach to identifying gesture features. Using this approach may mitigate the effects of the usability-accuracy tradeoff in gestural system development.