Modeling human-bed interaction: the predictive value of anthropometric models in choosing the correct bed support.

The sleep system (i.e. the combination of mattress and bed base) is an important factor of the sleep environment since it allows physical recuperation during sleep by providing proper body support. However, various factors influence the interaction between the human body and the sleep system. Contributing factors include body dimensions, distribution of body weight and stiffness of the sleep system across the mattress surface. During the past decade, the rise of several new bedding technologies has made it increasingly difficult for the consumer to select a proper sleep system. Therefore, this study presents a method to model human-bed interaction in order to objectively predict the ideal sleep system for a particular individual. The proposed method combines a personalized anthropometric model with standardized load-deflection characteristics of mattress and bed base. Results for lateral sleep positions show a root mean square deviation of 11.9 ± 6.1 mm between modeled spine shapes and validation shapes, derived from 3D surface scans of the back surface. The method showed to be a reliable tool to individually identify the sleep system providing superior support from a variety of possible mattress-bed base combinations.

Image-based planning and validation of C1-C2 transarticular screw fixation using personalized drill guides.

OBJECTIVE: Posterior transarticular spine fusion is a surgical procedure used to stabilize the cervical bodies C1 and C2. Currently, spine screws are used most frequently, according to the procedure of Magerl. As the anatomy is rather complex and the view is limited, this procedure has a high risk factor. We present and validate a planning system for cervical screw insertion based on preoperative CT imaging. MATERIALS AND METHODS: The planning system discussed allowed a neurosurgeon to interactively determine the desired position of the cervical screws, based on appropriate and real-time reslices through the preoperative CT image volume. From the planning, a personalized mechanical drill guide was derived as a means of transferring the plan intraoperatively. Eight cadaver experiments were performed to validate this approach. Postoperative CT was applied, and screw locations were extracted from the postoperative images after registering them to preoperative images. In this way, the deviations of the axes of the planned and inserted screws were determined. RESULTS: From an initial cadaver series, it was observed that the drill guides were not stable enough to cope with the drilling forces, and tended to become displaced. Still, most of the inserted screws were reported to be placed adequately. No vascular compromise or invasion of the spinal canal was observed. For a second cadaver series, the design of the drill guide was altered. In this series, the displacement was no longer present, and all screws were optimally placed. CONCLUSIONS: The preoperative planning system allowed the neurosurgeon to rehearse screw insertion in a way that is closer to surgical reality. The image-based validation technique allowed verification and enhancement of the template design on a cadaver study, giving accuracies comparable to those obtained with transfer by navigation.