Smart haptic gloves for virtual reality surgery simulation: a pilot study on external ventricular drain training.

Smart haptic gloves are a new technology emerging in Virtual Reality (VR) with a promise to enhance sensory feedback in VR. This paper presents one of the first attempts to explore its application to surgical training for neurosurgery trainees using VR-based surgery simulators. We develop and evaluate a surgical simulator for External Ventricular Drain Placement (EVD), a common procedure in the field of neurosurgery. Haptic gloves are used in combination with a VR environment to augment the experience of burr hole placement, and flexible catheter manipulation. The simulator was integrated into the training curriculum at the 2022 Canadian Neurosurgery Rookie Bootcamp. Thirty neurosurgery residents used the simulator where objective performance metrics and subjective experience scores were acquired. We provide the details of the simulator development, as well as the user study results and draw conclusions on the benefits added by the haptic gloves and future directions.

Three-Dimensional Biomechanical Modeling for Sitting Contact Stress Analysis.

This paper proposes a three-dimensional biomechanical model of the upper body and analyzes the interaction between the upper body and aircraft seat backrest for different sitting postures and backrest recline angles. The reclined sitting postures of the upper body are defined based on the available spine biomechanical data and the multibody inverse kinematics method. The contact loadings on each contacted spine segment are calculated based on the Newton-Euler dynamic formulation. The backrest contact pressure distribution is simulated using the contact stress theory based on the calculated forces on the backrest. The resultant force and pressure distribution show how the backrest inclination and lateral bending of the trunk affect the backrest loading and contact condition. The simulation results are compared to the experimental measurement for validation, and a good correspondence is found. The parameters, including the average and maximum pressure, and pressure standard deviation based on the pressure distribution, are also compared, and the maximum simulation error is 11.5% on the average pressure. Limitations of the model are discussed. The model proposed in this paper can analyze more posture cases than previous studies that focused on the two-dimensional scenarios. The loading and pressure prediction model can be applied for backrest design evaluation and facilitate seat design optimization.

Indoor Location Data for Tracking Human Behaviours: A Scoping Review.

Real-time location systems (RTLS) record locations of individuals over time and are valuable sources of spatiotemporal data that can be used to understand patterns of human behaviour. Location data are used in a wide breadth of applications, from locating individuals to contact tracing or monitoring health markers. To support the use of RTLS in many applications, the varied ways location data can describe patterns of human behaviour should be examined. The objective of this review is to investigate behaviours described using indoor location data, and particularly the types of features extracted from RTLS data to describe behaviours. Four major applications were identified: health status monitoring, consumer behaviours, developmental behaviour, and workplace safety/efficiency. RTLS data features used to analyse behaviours were categorized into four groups: dwell time, activity level, trajectory, and proximity. Passive sensors that provide non-uniform data streams and features with lower complexity were common. Few studies analysed social behaviours between more than one individual at once. Less than half the health status monitoring studies examined clinical validity against gold-standard measures. Overall, spatiotemporal data from RTLS technologies are useful to identify behaviour patterns, provided there is sufficient richness in location data, the behaviour of interest is well-characterized, and a detailed feature analysis is undertaken.