Implementation and Performance Evaluation of Real-Time Audio Decomposition Using Fast EMD on a Commercial Microcontroller

Empirical mode decomposition (EMD) is an adaptive signal analysis method requiring no predefined basis functions, capable of handling nonlinear and non-stationary signals. However, its high computational cost has long prevented real-time operation on embedded systems, particularly at audio frequencies (8–96 kHz). To the best of our knowledge, this study presents the first real-time audio-frequency EMD system running entirely on a commercial microcontroller (ARM Cortex-M7, STM32H730). The system captures audio via a MEMS microphone, decomposes signals into intrinsic mode functions (IMFs) using fast EMD, applies independent gain to each IMF, and reconstructs the output in real time. Systematic evaluation shows that: (1) the maximum processing rate increases approximately in proportion to the MCU clock frequency, achieving 100 kHz (one IMF) or 40 kHz (four IMFs) at 300 MHz; (2) processing latency is only approximately 1.6 ms (16 kHz, 8 ms window, four IMFs + residual), increasing approximately in proportion to window length; and (3) each IMF corresponds to a distinct frequency range, enabling data-driven frequency-selective processing. Built entirely from commercial off-the-shelf components and powered by two 1.5 V batteries, the system provides initial evidence for transitioning fast EMD from offline analysis to real-time embedded signal processing.