Motor nerve conduction study parameters in healthy individuals: effect of limb dominance

Background: Nerve conduction study (NCS) is useful for evaluation of nerve, muscle, and/or neuromuscular function. Neurophysiologist interprets NCS with consideration of various anthropometric and technical parameters viz. age, gender, height, temperature etc. apart from the underlying pathology. Fewer studies have reported the effect of limb dominance on NCS. Moreover, the findings are controversial. Therefore, author aimed to investigate the effect of limb dominance on motor nerve conduction study parameters.Methods: This cross-sectional comparative study included sixty healthy individuals (44 right and 16 left handed) of either sex with age 18 to 30 years. The NCS parameters of median and ulnar nerves were assessed by stimulating it and recording from the muscle and skin overlying the nerve respectively using Digital Nihon Kohden machine. The obtained data were analyzed using independent sample t-test.Results: Right ulnar nerve onset latency was significantly longer in left-handed individuals (1.85±0.508 ms vs 1.62±0.195 ms, p=0.012). The left ulnar nerve F wave minimum latency (25.88±0.74 ms vs 24.46±2.64 ms, p=0.002) was significantly longer in left-handed individuals. Likewise, right ulnar nerve distal latency (2.45±0.76 ms vs 2.14±0.39 ms, p=0.044), and right ulnar nerve F wave minimum (25.9±1.21 ms vs 24.85 ms±1.74, p=0.030) were significantly high in left-handed individuals.Conclusions: NCS parameters in terms of latencies were longer in left-handed individuals. Therefore, limb dominance seems to be an important factor one should pay attention during bilateral comparison of obtained data in neurophysiological reporting of referred cases.

Lamb Wave-Minimum Sampling Variance Particle Filter-Based Fatigue Crack Prognosis

Fatigue cracks are one of the common failure types of key aircraft components, and they are the focus of prognostics and health management (PHM) systems. Monitoring and prediction of fatigue cracks show great application potential and economic benefit in shortening aircraft downtime, prolonging service life, and enhancing maintenance. However, the fatigue crack growth process is a non-linear non-Gaussian dynamic stochastic process, which involves a variety of uncertainties. Actual crack initiation and growth sometimes deviate from the results of fracture mechanics analysis. The Lamb wave-particle filter (LW-PF) fatigue-crack-life prediction based on piezoelectric transducer (PZT) sensors has the advantages of simple modeling and on-line prediction, making it suitable for engineering applications. Although the resampling algorithm of the standard particle filter (PF) can solve the degradation problem, the discretization error still exists. To alleviate the accuracy decrease caused by the discretization error, a Lamb wave-minimum sampling variance particle filter (LW-MSVPF)-based fatigue crack life prediction method is proposed and validated by fatigue test of the attachment lug in this paper. Sampling variance (SV) is used as a quantitative index to analyze the difference of particle distribution before and after resampling. Compared with the LW-PF method, LW-MSVPF can increase the prediction accuracy with the same computational cost. By using the minimum sampling variance (MSV) resampling method, the original particle distribution is retained to a maximum degree, and the discretization error is significantly reduced. Furthermore, LW-MSVPF maintains the characteristic of dimensional freedom, which means a broader application in on-line prognosis for more complex structures.