This paper, the first in a two-part series, establishes the foundational theoretical principles required for designing effective electromyographic (EMG) acquisition systems for intuitive neuroprosthetic control. While advanced prosthetic technology holds immense promise, its widespread adoption is contingent on developing robust and cost-effective interfaces. This work begins by systematically exploring the biophysical basis of surface EMG signals, detailing their generation, propagation, and relationship to muscle activation. It then provides a critical analysis of the diverse physiological and technical noise sources that invariably accompany EMG acquisition, along with a short review of contemporary electrode technology and optimal signal conditioning. The paper concludes by elucidating the theoretical foundations of EMG signal processing, including essential feature extraction techniques and modelling approaches for translating raw biological signals into meaningful control commands. This comprehensive framework provides the indispensable theoretical blueprint for the design and experimental evaluation of practical EMG prototypes, which will be detailed in the second part of this research.