Analyzing surface EMG signals to determine relationship between jaw imbalance and arm strength loss

BACKGROUND: This study investigated the relationship between dental occlusion and arm strength; in particular, the imbalance in the jaw can cause loss in arm strength phenomenon. One of the goals of this study was to record the maximum forces that the subjects can resist against the pull-down force on their hands while biting a spacer of adjustable height on the right or left side of the jaw. Then EMG measurement was used to determine the EMG-Force relationship of the jaw, neck and arms muscles. This gave us useful insights on the arms strength loss due to the biomechanical effects of the imbalance in the jaw mechanism. METHODS: In this study to determine the effects of the imbalance in the jaw to the strength of the arms, we conducted experiments with a pool of 20 healthy subjects of both genders. The subjects were asked to resist a pull down force applied on the contralateral arm while biting on a firm spacer using one side of the jaw. Four different muscles – masseter muscles, deltoid muscles, bicep muscles and trapezoid muscles – were involved. Integrated EMG (iEMG) and Higuchi fractal dimension (HFD) were used to analyze the EMG signals. RESULTS: The results showed that (1) Imbalance in the jaw causes loss of arm strength contra-laterally; (2) The loss is approximately a linear function of the height of the spacers. Moreover, the iEMG showed the intensity of muscle activities decreased when the degrees of jaw imbalance increased (spacer thickness increased). In addition, the tendency of Higuchi fractal dimension decreased for all muscles. CONCLUSIONS: This finding indicates that muscle fatigue and the decrease in muscle contraction level leads to the loss of arm strength

Analysis of vibrations in a modeled ballasted track using measured rail defects

Vibrations caused by trains and transmitted to the ground and structures nearby are a known source of problems related to railways. Therefore this phenomenon should be studied in detail to avoid a negative impact in the environment. Within this framework, the article develops an improved version of a previously published analytical model capable of predicting ground vibrations caused by the passing of railway vehicles. The new features include a new formulation of the models with five layers of material and an enhanced load input process that takes into account actual rail defects data as well as the Hertz theory for the rail-wheel contact. The model is adapted to a conventional ballasted track in Solares (Spain) and calibrated and validated with data gathered on-site. Hence the model is proved to reproduce vibrations in rather different track typologies properly, constituting a useful research and design tool.Real Herráiz, JI.; Asensio Serrano, T.; Montalban Domingo, ML.; Zamorano, C. (2012). Analysis of vibrations in a modeled ballasted track using measured rail defects. Journal of Vibroengineering. 14(2):880-893. http://hdl.handle.net/10251/56929S88089314

Prediction of externally applied forces to human hands using frequency content of surface EMG signals

In this work, a new signal processing method was proposed in order to predict externally applied forces to human hands by deriving a relationship between the surface electromyographic (SEMG) signals and experimentally known forces. This relationship was investigated by analyzing the spectral features of the SEMG signals. SEMG signals were recorded from three subjects during isometric contraction and from another three subjects during anisometric contraction. In order to determine force-SEMG signal relationship, higher order frequency moments (HOFMs) of the signals were calculated and used as characterizing features of SEMG signals. Subsequently, artificial neural networks (ANN) with backpropagation algorithm were trained by using the HOFMs. Root mean square difference (RMSD) between the actual and predicted forces was calculated to evaluate force prediction performance of the ANN. In addition to RMSD, cross-correlation coefficients between actual and predicted force time histories were also calculated for anisometric experiment results. The RMSD values ranged from 0.34 and 0.02 in the isometric contraction experiments. In the anisometric contraction tests, RMSD results were between 0.23 and 0.09 and cross-correlation coefficients ranged from 0.91 to 0.98. In order to compare the performance of the HOFMs with a widely used EMG signal processing technique, root-mean-squared (RMS) values of the EMG signals were also calculated and used to train the ANN as another characterizing feature of the signal. Predicted forces using HOFMs technique were in general closer to the actual forces than those of obtained by using RMS values. The results indicated that the proposed signal processing method showed an encouraging performance for predicting the forces applied to the human hands, and the spectral features of the EMG signal might be used as input parameter for the myoelectric controlled prostheses. (C) 2009 Elsevier Ireland Ltd. All rights reserved

CONTRIBUTION TO THE MODELIZATION, ANALYTICAL AND NUMERICAL, OF GENERATION AND PROPAGATION OF VIBRATIONS ORIGINATED BY RAILWAY TRAFFIC. ANALYSIS OF MITIGATION PROPOSALS

Tesis por compendioReal Herráiz, JI. (2015). CONTRIBUTION TO THE MODELIZATION, ANALYTICAL AND NUMERICAL, OF GENERATION AND PROPAGATION OF VIBRATIONS ORIGINATED BY RAILWAY TRAFFIC. ANALYSIS OF MITIGATION PROPOSALS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/52247TESISCompendi

Zpracování povrchových elektromyografických signálů

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