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Real-time lossless ECG compression for low-power wearable medical devices based on adaptive region prediction

机译:基于自适应区域预测的低功耗可穿戴医疗设备实时无损ECG压缩

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摘要

A real-time lossless compression technique for ECG signals, which benefits wearable medical devices with stringent low-power requirements, is presented. The real-time ECG waveform is automatically classified into four regions according to its fluctuation features and the most suitable prediction method is adaptively selected from several linear prediction methods for different regions. Further proposed is the use of a modified variable length code to encode the prediction difference for a simpler transmit format. Experimental results based on three publically available test databases show that the proposed method achieves a better compression ratio with a lower prediction difference than existing state-of-the-art approaches. A very large-scale integration implementation is also demonstrated which can be used as an intellectual property core with a core area of 25 809 μm and which achieves a power consumption of 127 μW at 100 MHz in a 0.18 μm CMOS technology.
机译:提出了一种针对ECG信号的实时无损压缩技术,该技术有益于具有严格低功耗要求的可穿戴医疗设备。实时ECG波形会根据其波动特征自动分为四个区域,并从针对不同区域的几种线性预测方法中自适应选择最合适的预测方法。进一步提出了使用修改的可变长度码来对预测差异进行编码以得到更简单的发送格式。基于三个可公开获得的测试数据库的实验结果表明,与现有的最新方法相比,该方法可实现更好的压缩比,并且预测差异更低。还展示了一种非常大规模的集成实现,该实现可用作具有25 809μm核心面积的知识产权核心,并在0.18μmCMOS技术中在100 MHz时实现127μW的功耗。

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