An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

Study of accelerometer assisted single key positioning user input systems

New designs of user input systems have resulted from the developing technologies and specialized user demands. Conventional keyboard and mouse input devices still dominate the input speed, but other input mechanisms are demanded in special application scenarios. Touch screen and stylus input methods have been widely adopted by PDAs and smartphones. Reduced keypads are necessary for mobile phones. A new design trend is exploring the design space in applications requiring single-handed input, even with eyes-free on small mobile devices. This requires as few keys on the input device to make it feasible to operate. But representing many characters with fewer keys can make the input ambiguous. Accelerometers embedded in mobile devices provide opportunities to combine device movements with keys for input signal disambiguation. Recent research has explored its design space for text input. In this dissertation an accelerometer assisted single key positioning input system is developed. It utilizes input device tilt directions as input signals and maps their sequences to output characters and functions. A generic positioning model is developed as guidelines for designing positioning input systems. A calculator prototype and a text input prototype on the 4+1 (5 positions) positioning input system and the 8+1 (9 positions) positioning input system are implemented using accelerometer readings on a smartphone. Users use one physical key to operate and feedbacks are audible. Controlled experiments are conducted to evaluate the feasibility, learnability, and design space of the accelerometer assisted single key positioning input system. This research can provide inspiration and innovational references for researchers and practitioners in the positioning user input designs, applications of accelerometer readings, and new development of standard machine readable sign languages.

Species mobility and frequency dynamics in a Swiss limestone grassland

Community dynamics in a calcareous grassland (Mesobrometum) in Egerkingen (Jura mountains, Switzerland) were investigated for 53 non-woody species in 25 1-m2 plots over 6 years. 50 0.0 1-m2 subplots per plot were recorded. The derived variables were spatial frequency, temporal frequency, frequency fluctuation, turnover, and cumulative frequency (each species), and cumulative species richness (all species). Spectra for 53 species of all variables were different for the two investigated spatial scales (0.0 1 m2, 1 m2). The comparison with other investigations of similar grass lands showed that the behaviour of some species is specific for this type of vegetation in general (e.g. Achillea millefolium, Arrhenatherum elatius, Bromus erectus ), but most species behaved in a stand-specific way, i.e. they may play another (similar or completely different) role in another grassland stand. Six spatio-temporal patterns were defined across species. To understand community dynamics, not only the dynamics of mobility but also of frequency fluctuations and spatial distribution of the species are fundamental. In addition, the understanding of temporal behaviour of all species present should be included. Averages always hide important information of vegetation dynamics, as was shown by the present investigation.