An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes.
An Analog Circuit Approximation of the Discrete Wavelet Transform for Ultra Low Power Signal Processing in Wearable Sensor Nodes.
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DOI：
10.3390/s151229897
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发表时间：
2015-12-17
期刊：
影响因子：
--
通讯作者：
Casson AJ
中科院分区：
文献类型：
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作者：
Casson AJ
超低功耗信号处理是所有传感器节点的重要组成部分，尤其是在用于生物医学应用的新兴可穿戴传感器中。模拟信号处理在这些低功耗、低电压、低频率的应用中扮演着重要的角色，降低现有模拟域信号处理的功耗并将更多的信号处理方法映射到模拟域是一个关键驱动因素。提出了一种用于超低功耗可穿戴传感器的近似离散小波变换(DWT)输出的模拟域信号处理电路。模拟滤波器用于离散小波变换，并演示了如何产生类似于模拟域离散小波变换的信息，其中嵌入了来自Butterworth和Daubechies最大平坦母小波响应的信息。模拟离散小波变换通过C电路在硬件中实现，设计用1.3V硬币电池电池工作，在0.18μm cmos工艺中实现时，使用低于115NW的功率提供类似离散小波变换的信号处理。实例表明，新的模拟离散小波变换对人体记录的心电和脑电信号有较好的处理效果。
Ultra low power signal processing is an essential part of all sensor nodes, and particularly so in emerging wearable sensors for biomedical applications. Analog signal processing has an important role in these low power, low voltage, low frequency applications, and there is a key drive to decrease the power consumption of existing analog domain signal processing and to map more signal processing approaches into the analog domain. This paper presents an analog domain signal processing circuit which approximates the output of the Discrete Wavelet Transform (DWT) for use in ultra low power wearable sensors. Analog filters are used for the DWT filters and it is demonstrated how these generate analog domain DWT-like information that embeds information from Butterworth and Daubechies maximally flat mother wavelet responses. The Analog DWT is realised in hardware via C circuits, designed to operate from a 1.3 V coin cell battery, and provide DWT-like signal processing using under 115 nW of power when implemented in a 0.18 μm CMOS process. Practical examples demonstrate the effective use of the new Analog DWT on ECG (electrocardiogram) and EEG (electroencephalogram) signals recorded from humans.