An Ultra-Low-Power Non-Uniform Derivative-Based Sampling Scheme With Tunable Accuracy

• Published in: IEEE transactions on circuits and systems. I, Regular papers Regular papers, 2023-07, Vol.70 (7), p.1-14
• Main Authors: Elmi, Mohammad, Lee, Martin, Moez, Kambiz
• Format: Article
• Language: English
• Subjects: Algorithms; Analog signal processing; Complexity theory; Data acquisition; derivative-dependent sampling; Electrocardiography; Energy dissipation; low-power data acquisition; Maximum power; non-uniform sampling; Power consumption; Power demand; Quantization (signal); Sampling; Signal resolution; Signal to noise ratio
• ISSN: 1549-8328; 1558-0806
• DOI: 10.1109/TCSI.2023.3268611

This paper presents an ultra-low-power non-uniform sampling scheme using a derivative-based algorithm that can maintain a comparable accuracy to other non-uniform sampling schemes but with less complexity and lower power consumption. In this method, the change in the derivative of the signal above certain threshold values is used to identify high signal activity for retention of the significant points of the signal. The scheme is implemented using simple building blocks that calculate and compare the change in approximate real-time derivative to a tunable threshed value that can be adjusted to obtain the desired Compression Factor (CF) and Post-Reconstruction Signal-to-Noise plus Distortion Ratio (PR-SNDR) for different signal types. Fabricated in TSMC's 0.13 \mu m CMOS technology and tested with real-world biomedical signals, the proposed Derivative Dependent Sampling (DDS) system consumes a maximum power of 155 nW while achieving a CF of more than 6 for an Electrocardiography (ECG) signal. By adding the proposed DDS block to a data acquisition and processing system, the non-uniform sampling can reduce the power dissipation of the entire system.