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| autore2= Gianni Frisardi | | autore2= Gianni Frisardi | ||
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This chapter explores the intricacies of surface electromyography (sEMG), covering its fundamental principles, noise characteristics, electrode mechanics, and amplifier design, as well as the intricacies of signal processing. sEMG is essential for understanding muscle function, but various factors, such as signal-to-noise ratio, distortion, and interference, can complicate the interpretation of its readings. | |||
By examining the nature of sEMG signals—random, Gaussian-distributed data affected by external noise sources—this section emphasizes the limitations of traditional Fourier analysis and the importance of precise filtering. Furthermore, the role of electrodes in enabling electrical charge transmission from biological tissues to recording devices is discussed in detail, including the chemical processes at play, the advantages and disadvantages of different electrode materials, and potential challenges with electrode degradation. | |||
The chapter also delves into the electrical characteristics of amplifiers, highlighting the importance of differential amplification and the critical common-mode rejection ratio (CMRR), as well as the design of active electrodes and filtering techniques. It stresses that achieving high input impedance is essential for minimizing noise and distortion while ensuring signal fidelity. Placement, geometry, and size of electrodes play a pivotal role in ensuring accurate and reproducible sEMG recordings, with a focus on minimizing signal contamination from other muscles and adjusting for the natural movement of the body. | |||
In terms of processing, the text introduces methods for rectifying and integrating sEMG signals to make them clinically useful, along with more modern techniques like root mean square (RMS) computation. Time-related measurements are also addressed, emphasizing the biomechanical and clinical applications of these methods. | |||
Ultimately, this chapter emphasizes the precision required in recording and interpreting sEMG signals, ensuring that they accurately reflect muscle activity without distortion or interference from external sources. | |||
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