Real-Time In-Sensor Slope Level-Crossing Sampling for Key Sampling Points Selection for Wearable and IoT Devices

Abstract

This article presents a slope level-crossing sampling analog-to-digital converter (ADC) that selects key sampling points for quantization in real time during sensing. It only performs quantization for the turning points in the input analog waveform and provides quantization results of the selected sampling points and timestamps between the selected sampling points. When the input analog signal is sparse, the proposed method reduces digital output data throughput. The processing unit generates a dynamic prediction of the input signal as well as an upper threshold and a lower threshold to form a tracking window. A comparator compares the input signal with the upper and lower threshold to determine if the prediction is successful. Quantization is performed only on unsuccessful predicted sampling points, which are considered key sampling points. A counter records timestamps between the unsuccessful predictions, which are the selected key sampling points. The processing unit also includes a neighbor amplitude filter and a slope filter to further reduce the number of sampling points and data throughput when the input signal is associated with high-frequency, low-amplitude noise and high-amplitude, low-frequency baseline wandering. Reconstruction of the analog signal can be achieved using linear interpolation or polynomial interpolation. The system has been implemented and tested using off-the-shelf components. The simulation and experimental results show that the proposed system can reduce the data throughput and achieve a data compression ratio of 7.1 compared with a conventional successive approximation register (SAR) ADC with a 10-bit resolution when sampling an electrocardiogram (ECG) signal.