Sleep states are used in resource-constrained systems to conserve power, but they necessitate a wake-up circuit for detecting unpredictable events. In such systems, all information preceding a wake-up event will be forfeited. In this paper, we present an analog memory system that adaptively samples and records an input signal while the rest of the system sleeps, thereby preserving the information that would otherwise be lost. This system does so while consuming less than 3.52 µW. We also show how the adaptive sampling rate can be utilized to approximate the original signal using a minimal number of samples.

Wearable medical devices, wireless sensor networks, and other energy-constrained sensing devices are often concerned with finding specific data within more-complex signals while maintaining low power consumption. Traditional analog-to-digital converters (ADCs) can capture the sensor information at a high resolution to enable a subsequent digital system to process for the desired data. However, traditional ADCs can be inefficient for applications that only require specific points of data. This work offers an alternative path to lower the energy expenditure in the quantization stage-asynchronous content-dependent sampling. This asynchronous sampling scheme is achieved by pairing a flexible analog front-end with an asynchronous successive-approximation ADC and a time-to-digital converter. The versatility and reprogrammability of this system allows a multitude of event-driven, asynchronous, or even purely data-driven quantization methods to be implemented for a variety of different applications. The system, fabricated in standard 0.5 µm and 0.35 µm processes, is demonstrated along with example applications with voice, EMG, and ECG signals.

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The limited power budgets of sensor networks necessitate in-network pre-processing to reduce communication overhead. The low power consumption of analog signal processing (ASP) is well-suited for this task. However, adoption of ASP is restrained by the longer design time relative to reconfigurable/reprogrammable digital processing. Our solution is to enable ASP reconfiguration through the use of a fieldprogrammable analog array (FPAA), which allows wireless sensor network developers to rapidly prototype and test ASP designs. In this paper, we present an FPAA designed for use in wireless sensor networks, and we describe its incorporation and use within a sensor node.

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