Effect of the amount of sub-bands in the performance of discrete wavelet transform based dynamic S-EMG signals encoder

Abstract

Keywords -- Resumo --

Effective Low-Power Wearable Wireless Surface EMG Sensor Design Based on Analog-Compressed Sensing

“…Table 5 depicts a comparison on the analog-CS and the digital-CS in terms of sensitivity (SEN) and specificity (SPE). The SEN and SPE are calculated by the following equations [ 35 ]: where T P is true positive, T N true negative, F P is false positive, and F N is false negative.…”

“…It can be seen from Figure 12 that all RMSE values decrease with decrease of CR or the increase of sub-sampling ratio. The MCS is a method for obtaining numerical results, which relies on many simulations by varying parameters within statistical constraints [ 35 ].…”

“…Compression Factor (CF) for three types of sEMG bio-signals sampled at 8 kHz and digitized with 4 bytes/sample. The PRD are defined as [ 35 ]: where D [ i ] is the original sEMG bio-signal, D̂ [ i ] is the reconstructed sEMG bio-signal, and N is the total number of samples. The CF is calculated by: where D b is the number of bits for the original sEMG bio-signal and C b is the amount of bits necessary for processing the compressed sEMG bio-signal.…”

“…The ℓ 1 -ℓ 1 -optimization is applied to the received sEMG-neuropathy signals, which are sparse in the frequency domain as [ 34 ]: where λ is a positive constant and F is a N x N Fourier transform matrix. The ℓ 1 -ℓ 1 -optimization idea comes from multi-ℓ 1 -optimization, which can expressed as [ 34 , 35 ]: where λ i is a positive constant. In the frequency domain Ψ is changed to F , which is an N x N Fourier transform matrix.…”

“…In another scenario, if the transmitter receives sEMG-healthy or sEMG-myopathy signals that are sparse in the time domain, the ℓ 1 -optimization is applied to the received bio-signal in order to reconstruct the original bio-signal. The ℓ 1 -optimization is defined as [ 35 ]: …”