Validity and Reliability of an Inertial Device for Measuring Dynamic Weight-Bearing Ankle Dorsiflexion

A decrease in ankle dorsiflexion causes changes in biomechanics, and different instruments have been used for ankle dorsiflexion testing under static conditions. Consequently, the industry of inertial sensors has developed easy-to-use devices, which measure dynamic ankle dorsiflexion and provide additional parameters such as velocity, acceleration, or movement deviation. Therefore, the aims of this study were to analyze the concurrent validity and test-retest reliability of an inertial device for measuring dynamic weight-bearing ankle dorsiflexion. Sixteen participants were tested using an inertial device (WIMU) and a digital inclinometer. Ankle dorsiflexion from left and right ankle repetitions was used for validity analysis, whereas test-retest reliability was analyzed by comparing measurements from the first and second days. The standard error of the measurement (SEM) between the instruments was very low for both ankle measurements (SEM 0.05) even though a significant systematic bias (~1.77°) was found for the right ankle (d = 0.79). R2 was very close to 1 in the left and right ankles (R2 = 0.85–0.89) as well as the intraclass correlation coefficient (ICC > 0.95). Test-retest reliability analysis showed that systematic bias was below 1° for both instruments, even though a systematic bias (~1.50°) with small effect size was found in the right ankle (d = 0.49) with WIMU. The ICC was very close to 1 and the coefficient of variation (CV) was lower than 4% in both instruments. Thus, WIMU is a valid and reliable inertial device for measuring dynamic weight-bearing ankle dorsiflexion

Testing microelectronic biofluidic systems

According to the 2005 International Technology Roadmap for Semiconductors, the integration of emerging nondigital CMOS technologies will require radically different test methods, posing a major challenge for designers and test engineers. One such technology is microelectronic fluidic (MEF) arrays, which have rapidly gained importance in many biological, pharmaceutical, and industrial applications. The advantages of these systems, such as operation speed, use of very small amounts of liquid, on-board droplet detection, signal conditioning, and vast digital signal processing, make them very promising. However, testable design of these devices in a mass-production environment is still in its infancy, hampering their low-cost introduction to the market. This article describes analog and digital MEF design and testing method

Evolving concurrent Petri net models of epistasis

A genetic algorithm is used to learn a non-deterministic Petri netbased model of non-linear gene interactions, or statistical epistasis. Petri nets are computational models of concurrent processes. However, often certain global assumptions (e.g. transition priorities) are required in order to convert a non-deterministic Petri net into a simpler deterministic model for easier analysis and evaluation. We show, by converting a Petri net into a set of state trees, that it is possible to both retain Petri net non-determinism (i.e. allowing local interactions only, thereby making the model more realistic), whilst also learning useful Petri nets with practical applications. Our Petri nets produce predictions of genetic disease risk assessments derived from clinical data that match with over 92% accuracy

Measurements, Models, Systems and Design

531 s.

Optimizing construction of scheduled data flow graph for on-line testability

The objective of this work is to develop a new methodology for behavioural synthesis using a flow of synthesis, better suited to the scheduling of independent calculations and non-concurrent online testing. The traditional behavioural synthesis process can be defined as the compilation of an algorithmic specification into an architecture composed of a data path and a controller. This stream of synthesis generally involves scheduling, resource allocation, generation of the data path and controller synthesis. Experiments showed that optimization started at the high level synthesis improves the performance of the result, yet the current tools do not offer synthesis optimizations that from the RTL level. This justifies the development of an optimization methodology which takes effect from the behavioural specification and accompanying the synthesis process in its various stages. In this paper we propose the use of algebraic properties (commutativity, associativity and distributivity) to transform readable mathematical formulas of algorithmic specifications into mathematical formulas evaluated efficiently. This will effectively reduce the execution time of scheduling calculations and increase the possibilities of testability

Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization

© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a new technique that dynamically estimates and updates the coefficients of a digital predistorter (DPD) for power amplifier (PA) linearization. The proposed technique is dynamic in the sense of estimating, at every iteration of the coefficient's update, only the minimum necessary parameters according to a criterion based on the residual estimation error. At the first step, the original basis functions defining the DPD in the forward path are orthonormalized for DPD adaptation in the feedback path by means of a precalculated principal component analysis (PCA) transformation. The robustness and reliability of the precalculated PCA transformation (i.e., PCA transformation matrix obtained off line and only once) is tested and verified. Then, at the second step, a properly modified partial least squares (PLS) method, named dynamic partial least squares (DPLS), is applied to obtain the minimum and most relevant transformed components required for updating the coefficients of the DPD linearizer. The combination of the PCA transformation with the DPLS extraction of components is equivalent to a canonical correlation analysis (CCA) updating solution, which is optimum in the sense of generating components with maximum correlation (instead of maximum covariance as in the case of the DPLS extraction alone). The proposed dynamic extraction technique is evaluated and compared in terms of computational cost and performance with the commonly used QR decomposition approach for solving the least squares (LS) problem. Experimental results show that the proposed method (i.e., combining PCA with DPLS) drastically reduces the amount of DPD coefficients to be estimated while maintaining the same linearization performance.Peer ReviewedPostprint (author's final draft

Implementation and evaluation of simultaneous video-electroencephalography and functional magnetic resonance imaging

The objective of this study was to demonstrate that the addition of simultaneous and synchronised video to electroencephalography (EEG)-correlated functional magnetic resonance imaging (fMRI) could increase recorded information without data quality reduction. We investigated the effect of placing EEG, video equipment and their required power supplies inside the scanner room, on EEG, video and MRI data quality, and evaluated video-EEG-fMRI by modelling a hand motor task. Gradient-echo, echo-planner images (EPI) were acquired on a 3-T MRI scanner at variable camera positions in a test object [with and without radiofrequency (RF) excitation], and human subjects. EEG was recorded using a commercial MR-compatible 64-channel cap and amplifiers. Video recording was performed using a two-camera custom-made system with EEG synchronization. An in-house script was used to calculate signal to fluctuation noise ratio (SFNR) from EPI in test object with variable camera positions and in human subjects with and without concurrent video recording. Five subjects were investigated with video-EEG-fMRI while performing hand motor task. The fMRI time series data was analysed using statistical parametric mapping, by building block design general linear models which were paradigm prescribed and video based. Introduction of the cameras did not alter the SFNR significantly, nor did it show any signs of spike noise during RF off conditions. Video and EEG quality also did not show any significant artefact. The Statistical Parametric Mapping{T} maps from video based design revealed additional blood oxygen level-dependent responses in the expected locations for non-compliant subjects compared to the paradigm prescribed design. We conclude that video-EEG-fMRI set up can be implemented without affecting the data quality significantly and may provide valuable information on behaviour to enhance the analysis of fMRI data