Marcel Henrique Trabuco

This work presents an automatic and robust algorithm for surface electromyography signals segmentation in dynamic experimental protocol. The signals are segmented based on the peak burst occurrence. The two-dimensional array is constructed and used as input of a 2D signal encoder. The two-dimensional matrix lines may be long enough to have several bursts. The algorithm includes, besides segmentation modules, several others to eliminate the occurrence of false positives. An encoder that combines… Exibir mais

This work presents an automatic and robust algorithm for surface electromyography signals segmentation in dynamic experimental protocol. The signals are segmented based on the peak burst occurrence. The two-dimensional array is constructed and used as input of a 2D signal encoder. The two-dimensional matrix lines may be long enough to have several bursts. The algorithm includes, besides segmentation modules, several others to eliminate the occurrence of false positives. An encoder that combines the AV1 and JPEG2000 toolset is used to compress data. Basically, depending on the target compression rate the encoder uses AV1 or JPEG2000. Examples of segmentation for electromyography signals digitalized from lower and upper limbs are shown. Data compression results for real electromyography signals data bank are presented. A performance comparison with other works reported in the literature is also included. Exibir menos

This work presents algorithms designed for 1D (one-dimensional) and 2D (two-dimensional) surface electromyographic (S-EMG) signal compression. The 1D approach is a wavelet transform-based encoder. An adaptive estimation of the spectral shape is used to carry out dynamic bit allocation for vector quantization of transformed coefficients. Thus, an entropy coding is applied to minimize redundancy in quantized coefficient vector and to pack the data. In the 2D approach algorithm, the isometric or… Exibir mais

This work presents algorithms designed for 1D (one-dimensional) and 2D (two-dimensional) surface electromyographic (S-EMG) signal compression. The 1D approach is a wavelet transform-based encoder. An adaptive estimation of the spectral shape is used to carry out dynamic bit allocation for vector quantization of transformed coefficients. Thus, an entropy coding is applied to minimize redundancy in quantized coefficient vector and to pack the data. In the 2D approach algorithm, the isometric or dynamic S-EMG signal is properly segmented and arranged to build a two-dimensional representation. The HEVC video codec is used to encode the signal, using 16 bit-depth precision, all possible Coding/Prediction Unit sizes and all Intra coding modes. The encoders are evaluated with objective metrics, and a real signal data bank is used. Furthermore, performance comparisons are also shown in this work, where the proposed methods have outperformed other efficient encoders reported in the literature. Exibir menos

This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack… Exibir mais

This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack all data. The bit allocation scheme is based on mathematical decreasing spectral shape models, which indicates a shorter digital word length to code high frequency wavelets transformed coefficients. Four bit allocation spectral shape methods were implemented and compared: decreasing exponential spectral shape, decreasing linear spectral shape, decreasing square-root spectral shape and rotated hyperbolic tangent spectral shape. Exibir menos