Canbay Ferhat, Levent Vecdi Emre, Serbes Gorkem, Goren Sezer, Aydin Nizamettin
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:6026-9. doi: 10.1109/EMBC.2015.7319765.
Due to the inherent time-varying characteristics of physiological systems, most biomedical signals (BSs) are expected to have non-stationary character. Therefore, any appropriate analysis method for dealing with BSs should exhibit adjustable time-frequency (TF) resolution. The wavelet transform (WT) provides a TF representation of signals, which has good frequency resolution at low frequencies and good time resolution at high frequencies, resulting in an optimized TF resolution. Discrete wavelet transform (DWT), which is used in various medical signal processing applications such as denoising and feature extraction, is a fast and discretized algorithm for classical WT. However, the DWT has some very important drawbacks such as aliasing, lack of directionality, and shift-variance. To overcome these drawbacks, a new improved discrete transform named as Dual Tree Complex Wavelet Transform (DTCWT) can be used. Nowadays, with the improvements in embedded system technology, portable real-time medical devices are frequently used for rapid diagnosis in patients. In this study, in order to implement DTCWT algorithm in FPGAs, which can be used as real-time feature extraction or denoising operator for biomedical signals, a novel hardware architecture is proposed. In proposed architecture, DTCWT is implemented with only one adder and one multiplier. Additionally, considering the multi-channel outputs of biomedical data acquisition systems, this architecture is capable of running N channels in parallel.
由于生理系统固有的时变特性，大多数生物医学信号（BSs）预计具有非平稳特性。因此，任何处理生物医学信号的合适分析方法都应具有可调整的时频（TF）分辨率。小波变换（WT）提供了信号的时频表示，它在低频处具有良好的频率分辨率，在高频处具有良好的时间分辨率，从而实现了优化的时频分辨率。离散小波变换（DWT）是经典WT的一种快速离散算法，用于各种医学信号处理应用，如去噪和特征提取。然而，DWT存在一些非常重要的缺点，如混叠、缺乏方向性和移位方差。为了克服这些缺点，可以使用一种名为双树复小波变换（DTCWT）的新改进离散变换。如今，随着嵌入式系统技术的进步，便携式实时医疗设备经常用于对患者进行快速诊断。在本研究中，为了在FPGA中实现DTCWT算法，该算法可用作生物医学信号的实时特征提取或去噪算子，提出了一种新颖的硬件架构。在所提出的架构中，仅用一个加法器和一个乘法器就实现了DTCWT。此外，考虑到生物医学数据采集系统的多通道输出，该架构能够并行运行N个通道。
