Range of motion in anterior femoroacetabular impingement

The range of motion of normal hips and hips with femoroacetabular impingement relative to some specific anatomic reference landmarks is unknown. We therefore described: (1) the range of motion pattern relative to landmarks; (2) the location of the impingement zones in normal and impinging hips; and (3) the influence of surgical débridement on the range of motion. We used a previously developed and validated noninvasive 3-D CT-based method for kinematic hip analysis to compare the range of motion pattern, the location of impingement, and the effect of virtual surgical reconstruction in 28 hips with anterior femoroacetabular impingement and a control group of 33 normal hips. Hips with femoroacetabular impingement had decreased flexion, internal rotation, and abduction. Internal rotation decreased with increasing flexion and adduction. The calculated impingement zones were localized in the anterosuperior quadrant of the acetabulum and were similar in the two groups and in impingement subgroups. The average improvement of internal rotation was 5.4 degrees for pincer hips, 8.5 degrees for cam hips, and 15.7 degrees for mixed impingement. This method helps the surgeon quantify the severity of impingement and choose the appropriate treatment option; it provides a basis for future image-guided surgical reconstruction in femoroacetabular impingement with less invasive techniques.

High precision range estimation techniques for multi-path wireless environments

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.