This article proposes a method for modeling and classification apply on the uterine contractions in the electromyogram (EMG) signal for the detection of preterm birth. The frequency content of the contraction changes from one woman to another and during pregnancy. Firstly we apply an AR model on the Uterine EMG signal for the calculation of the ai parameters. Wavelet decomposition is used to ex...

We propose a combination of blind source separation (BSS) and independent component analysis (ICA) (signal decomposition into artifacts and nonartifacts) with support vector machines (SVMs) (automatic classification) that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA) and one BSS algorithm (AMUSE) are evaluated to d...

The decomposition of surface electromyogram data sets (s-EMG) is studied using blind source separation techniques based on sparseness; namely independent component analysis, sparse nonnegative matrix factorization, and sparse component analysis. When applied to artificial signals we find noticeable differences of algorithm performance depending on the source assumptions. In particular, sparse n...

We used surface EMG signal decomposition technology to study the control properties of numerous simultaneously active motor units. Six healthy human subjects of comparable age (21 +/- 0.63 yr) and physical fitness were recruited to perform isometric contractions of the vastus lateralis (VL), first dorsal interosseous (FDI), and tibialis anterior (TA) muscles at the 20, 50, 80, and 100% maximum ...

Recent advances in high density surface electromyogram (EMG) decomposition have made it a feasible task to discriminate single motor unit activity from surface EMG interference patterns, thus providing a noninvasive approach for examination of motor unit control properties. In the current study we applied high density surface EMG recording and decomposition techniques to assess motor unit firin...

25 We employed a surface electromyographic (EMG) signal decomposition technology to study the 26 control properties of numerous simultaneously active motor units. Six healthy human subjects of 27 comparable age (21 ± 0.63 yr) and physical fitness were recruited to perform isometric 28 contractions of the vastus lateralis (VL), first dorsal interosseous (FDI), and tibialis anterior (TA) 29 muscl...

The study of burst electromyographic (EMG) activity periods during muscles contraction and relaxation is an important challenging problem. It can find several applications like movement patterns analysis, human locomotion analysis neuromuscular pathologies diagnosis such as Parkinson disease. This paper proposes a new frame work for detecting the onset (start) / offset (end) EMG by segmenting s...

It is known that at any given force level, the lower-threshold motor units generally fire at greater rates than the higher-threshold units during isometric tasks of extremity muscles. In addition to this hierarchical arrangement, firing rates of motor units fluctuate in unison with nearly no time delay; an observation that has led to the concept of common drive, a basic motoneuronal rule. Altho...