基于ULP FPGA的基于MEMS的BCG可穿戴传感器的高效在线压缩

Uif Kulau, Abdelrahman Noshy, Abdelalim Ahmed
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引用次数: 0

摘要

BCG数据的压缩在可穿戴设备和超低功耗(ULP)应用中具有重要意义。本文提出了一种高效而简单的BCG数据压缩核心,可以集成到MEMS传感器或ULP fpga上。所提出的压缩技术是一种改进的增量编码算法,可以有效地压缩数据,从无损压缩到有损压缩,而设计是根据BCG的特定要求而派生的。该技术在压缩性能和信号失真方面提供了灵活性,压缩比可以换取无损压缩,反之亦然。对4个BCG数据集的评估显示,在适当的PRDN下,平均压缩比为3。该压缩核心在VHDL中进一步实现,利用了支持在线压缩的FPGA资源234个lut。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Online Compression for MEMS based BCG Wearable Sensors on ULP FPGA
Compression of Ballistocardiography (BCG) data is of a great importance specially in the context of wearables and ultra-low power (ULP) applications, respectively. This paper presents an efficient and yet simple compression core for BCG data that can be integrated to MEMS sensor or on ULP FPGAs. The proposed compression technique is a modified delta encoding algorithm that can compress data efficiently ranging from lossless to lossy compression, while the design was derived from BCG specific requirements. The technique offers flexibility with respect to compression performance and signal distortion where compression ratio can be traded for lossless compression and vice verse. Evaluations of 4 BCG data sets show an average compression ratio of 3 with adequate PRDN. This compression core is further implemented in VHDL and it utilizes 234 LUTs of FPGA resources supporting online compression.
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