53 research outputs found
Toward personalized total knee arthroplasty:Pre-planning the patient's optimal joint function
Get PDFBiomechanical analysis of morphological knee joint phenotypes and their potential effects on the outcomes of total knee arthroplasty
No full textShould robotic-assisted total knee arthroplasty reconstruct premorbid stage? The effects of osteophytes on knee functionality
No full textMusculoskeletal simulation of cruciate-retaining total knee arthroplasty to predict the biomechanical effects of tibial polyethylene thickness
No full textPersonalized musculoskeletal modeling of premorbid knees towards an optimally planned total knee arthroplasty
No full textPredicting the effect of tibial polyethylene thickness on ligament and contact forces in cruciate-retaining total knee arthroplasty
No full textThe impact of posterior tibial slope on knee biomechanics as predictor of flexion contracture in total knee arthroplasty
No full textThe design of a high speed CMOS image sensor: featuring global shutter, high dynamic range and flexible exposure control in 110nm technology
No full textHigh speed imagers find applications in many fields such as scientific and medical imaging, automotive applications, machine vision and much more. In this thesis, the design of a high speed, high dynamic range (HDR) CMOS sensor with electronic global shutter (GS) and flexible exposure control is presented. The sensor is designed in the 0.11μm CIS process, features 1k(H) x 1k(V) pixels and achieves frame rates greater that 10.000 fps.A review of the architecture of the sensor is given, along with functional illustrations for each comprising block. The quadrant-based approach is described, along with the selectable region-of-interest capability. The pixel design is a eleven-transistor (11T) pinned photodiode global shutter pixel, implementing HDR by means of two in-pixel capacitors. The design of the pipelined Sample & Hold, column gain and column-level Correlated Double Sampling (CDS) circuits are shown.Electrical Engineerin
Pre-Planning the Surgical Target for Optimal Implant Positioning in Robotic-Assisted Total Knee Arthroplasty
Get PDFRobotic-assisted total knee arthroplasty can attain highly accurate implantation. However, the target for optimal positioning of the components remains debatable. One of the proposed targets is to recreate the functional status of the pre-diseased knee. The aim of this study was to demonstrate the feasibility of reproducing the pre-diseased kinematics and strains of the ligaments and, subsequently, use that information to optimize the position of the femoral and tibial components. For this purpose, we segmented the pre-operative computed tomography of one patient with knee osteoarthritis using an image-based statistical shape model and built a patient-specific musculoskeletal model of the pre-diseased knee. This model was initially implanted with a cruciate-retaining total knee system according to mechanical alignment principles; and an optimization algorithm was then configured seeking the optimal position of the components that minimized the root-mean-square deviation between the pre-diseased and post-operative kinematics and/or ligament strains. With concurrent optimization for kinematics and ligament strains, we managed to reduce the deviations from 2.4 ± 1.4 mm (translations) and 2.7 ± 0.7° (rotations) with mechanical alignment to 1.1 ± 0.5 mm and 1.1 ± 0.6°, and the strains from 6.5% to lower than 3.2% over all the ligaments. These findings confirm that adjusting the implant position from the initial plan allows for a closer match with the pre-diseased biomechanical situation, which can be utilized to optimize the pre-planning of robotic-assisted surgery
Width-parameterized SAT: time-space tradeoffs,
No full textAlekhnovich and Razborov (2002) presented an algorithm that solves SAT on instances ϕ of size n and tree-width TW(ϕ), using time and space bounded by 2O(TW(ϕ))nO(1). Although several follow-up works appeared over the last decade, the first open question of Alekhnovich and Razborov remained essentially unresolved: Can one check satisfiability of formulas with small tree-width in polynomial space and time as above? We essentially resolve this question, by (1) giving a polynomial space algorithm with a slightly worse run-time, (2) providing a complexity-theoretic characterization of bounded tree-width SAT, which strongly suggests that no polynomial-space algorithm can run significantly faster, and (3) presenting a spectrum of algorithms trading off time for space, between our PSPACE algorithm and the fastest known algorithm.
First, we give a simple algorithm that runs in polynomial space and achieves run-time 3TW(ϕ)lognnO(1), which approaches the run-time of Alekhnovich and Razborov (2002), but has an additional log n factor in the exponent. Then, we conjecture that this annoying log n factor is in general unavoidable.
Our negative results show our conjecture true if one believes a well-known complexity assumption, which is the SC ≠ NC conjecture and its scaled variants. Technically, we base our result on the following lemma. For arbitrary k, SAT of tree-width logkn is complete for the class of problems computed by circuits of logarithmic depth, semi-unbounded fan-in and size 2O(logkn) (SAC1 when k=1). Problems in this class can be solved simultaneously in time-space (2O(logk+1n),O(logk+1n)), and also in (2O(logkn), 2O(logkn)). Then, we show that our conjecture (for SAT instances with poly-log tree-width) is equivalent to the question of whether the small-space simulation of semi-unbounded circuit classes can be sped up without incurring a large space penalty. This is a recasting of the conjecture that SAC1 (and even its subclass NL) is not contained in SC.
Although we cannot hope for an improvement asymptotically in the exponent of time and space, we introduce a new algorithmic technique which trades constants in the exponents: for each ε with 0<ε<1, we give an algorithm in time-space
(31.441(1−ε)TW(ϕ)log|ϕ||ϕ|O(1),22εTW(ϕ)|ϕ|O(1)).
We systematically study the limitations of our technique for trading off time and space, and we show that our bounds are the best achievable using this technique.Licensed under a Creative Commons Attribution License (CC-BY) http://creativecommons.org/licenses/by/3.0/Peer reviewe
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