On-line empirical mode decomposition biomedical microprocessor for Hilbert Huang transform

On-chip implementation of Hilbert-Huang transform (HHT) has great impact to analyze the non-linear and non-stationary biomedical signals on wearable or implantable sensors for the real-time applications. Empirical mode decomposition (EMD) is the key component for the HHT processor. In tradition, EMD is usually performed after the collection of a large window of signals, and the long latency may not be feasible for the real-time applications. In this work, the architecture of on-line EMD for biomedical signals is proposed. The on-line interpolation method with data reuse as well as component and iteration loop decomposition is applied to obtain low latency and low hardware cost. The first chip of EMD processor is fabricated in UMC 90nm LL process and consumes 57.3μW.