Assessment of Lower Limb Muscle Strength and Power Using Hand-Held and Fixed Dynamometry: A Reliability and Validity Study

Introduction

Hand-held dynamometry (HHD) has never previously been used to examine isometric muscle power. Rate of force development (RFD) is often used for muscle power assessment, however no consensus currently exists on the most appropriate method of calculation. The aim of this study was to examine the reliability of different algorithms for RFD calculation and to examine the intra-rater, inter-rater, and inter-device reliability of HHD as well as the concurrent validity of HHD for the assessment of isometric lower limb muscle strength and power.

Methods

30 healthy young adults (age: 23±5yrs, male: 15) were assessed on two sessions. Isometric muscle strength and power were measured using peak force and RFD respectively using two HHDs (Lafayette Model-01165 and Hoggan microFET2) and a criterion-reference KinCom dynamometer. Statistical analysis of reliability and validity comprised intraclass correlation coefficients (ICC), Pearson correlations, concordance correlations, standard error of measurement, and minimal detectable change.

Results

Comparison of RFD methods revealed that a peak 200ms moving window algorithm provided optimal reliability results. Intra-rater, inter-rater, and inter-device reliability analysis of peak force and RFD revealed mostly good to excellent reliability (coefficients ≥ 0.70) for all muscle groups. Concurrent validity analysis showed moderate to excellent relationships between HHD and fixed dynamometry for the hip and knee (ICCs ≥ 0.70) for both peak force and RFD, with mostly poor to good results shown for the ankle muscles (ICCs = 0.31–0.79).

Conclusions

Hand-held dynamometry has good to excellent reliability and validity for most measures of isometric lower limb strength and power in a healthy population, particularly for proximal muscle groups. To aid implementation we have created freely available software to extract these variables from data stored on the Lafayette device. Future research should examine the reliability and validity of these variables in clinical populations.     

Modeling <Emphasis Type="Italic">Neisseria meningitidis</Emphasis> metabolism: from genome to metabolic fluxes

Background  

Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years.     

Fish scale shape follows predictable patterns of variation based on water column position,body size,and phylogeny

Evolutionary Ecology - The influence of environment and phylogeny on morphological characteristics of organisms is well documented. However, little is known about how these factors influence scale...     

Functional traits,convergent evolution,and periodic tables of niches

Ecology is often said to lack general theories sufficiently predictive for applications. Here, we examine the concept of a periodic table of niches and feasibility of niche classification schemes from functional trait and performance data. Niche differences and their influence on ecological patterns and processes could be revealed effectively by first performing data reduction/ordination analyses separately on matrices of trait and performance data compiled according to logical associations with five basic niche ‘dimensions’, or aspects: habitat, life history, trophic, defence and metabolic. Resultant patterns then are integrated to produce interpretable niche gradients, ordinations and classifications. Degree of scheme periodicity would depend on degrees of niche conservatism and convergence causing species clustering across multiple niche dimensions. We analysed a sample data set containing trait and performance data to contrast two approaches for producing niche schemes: species ordination within niche gradient space, and niche categorisation according to trait‐value thresholds. Creation of niche schemes useful for advancing ecological knowledge and its applications will depend on research that produces functional trait and performance datasets directly related to niche dimensions along with criteria for data standardisation and quality. As larger databases are compiled, opportunities will emerge to explore new methods for data reduction, ordination and classification.     

Simulation of human atherosclerotic femoral plaque tissue: the influence of plaque material model on numerical results

Background

Due to the limited number of experimental studies that mechanically characterise human atherosclerotic plaque tissue from the femoral arteries, a recent trend has emerged in current literature whereby one set of material data based on aortic plaque tissue is employed to numerically represent diseased femoral artery tissue. This study aims to generate novel vessel-appropriate material models for femoral plaque tissue and assess the influence of using material models based on experimental data generated from aortic plaque testing to represent diseased femoral arterial tissue.

Methods

Novel material models based on experimental data generated from testing of atherosclerotic femoral artery tissue are developed and a computational analysis of the revascularisation of a quarter model idealised diseased femoral artery from a 90% diameter stenosis to a 10% diameter stenosis is performed using these novel material models. The simulation is also performed using material models based on experimental data obtained from aortic plaque testing in order to examine the effect of employing vessel appropriate material models versus those currently employed in literature to represent femoral plaque tissue.

Results

Simulations that employ material models based on atherosclerotic aortic tissue exhibit much higher maximum principal stresses within the plaque than simulations that employ material models based on atherosclerotic femoral tissue. Specifically, employing a material model based on calcified aortic tissue, instead of one based on heavily calcified femoral tissue, to represent diseased femoral arterial vessels results in a 487 fold increase in maximum principal stress within the plaque at a depth of 0.8 mm from the lumen.

Conclusions

Large differences are induced on numerical results as a consequence of employing material models based on aortic plaque, in place of material models based on femoral plaque, to represent a diseased femoral vessel. Due to these large discrepancies, future studies should seek to employ vessel-appropriate material models to simulate the response of diseased femoral tissue in order to obtain the most accurate numerical results.

     

Review and classification of variability analysis techniques with clinical applications

Background

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction.

Method

A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE.

Results

The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%.

Conclusions

The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.