This paper presents a methodology for automatically detecting muscular activity by
denoising, extracting features, and classifying surface electromyography (sEMG) signals …

This paper presents a new method for classifying railway vehicle axle fatigue crack acoustic
emission (AE) signal. The method is developed by integrating self-adaptive empirical mode …

Background Continuous and discrete wavelet transforms have been established as valid
tools to analyze non-stationary and transient signals over Fourier domain methods …

In this paper, a new feature of surface electromyo-graphy (sEMG) by using discrete wavelet
transform (DWT) is proposed for motion recognition of upper limbs, and this method can be …

Due to the wide availability of WiFi devices in almost every modern building, activity and
gesture recognition systems using WiFi have recently been in the spotlight. Given the low …

Lower leg muscles are known to be activated during standing. On the other hand, standing
is known to induce orthostatic stress. Our recent work presented that the posture control and …

Previous studies have established the effects of orthostatic challenge on the cardiovascular
and postural control systems, but the interdependent behavior of the systems under such …

O objetivo deste documento é apresentar o estado da arte envolvendo sinais de
eletromiografia de superfície (sEMG) e o uso do LabVIEW TM em sistemas de aquisição de …

An improved time-domain analysis method combining with the sliding window and Local
Mean Decomposition (LMD) is proposed for a large amount of data volume when using …

This paper presents a self-adaptive data analysis method on acoustic emission (AE) signals
which are generated by the fracture test on the rotation shaft. When collecting AE signals …