Browsing by Author "Serbes, G."

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An area efficient real time implementation of dual tree complex wavelet transform in field programmable gate arrays
(IEEE, 2015) Canbay, F.; Levent, Vecdi Emre; Serbes, G.; Uğurdağ, Hasan Fatih; Goren, S.; Aydin, N.; Electrical & Electronics Engineering; UĞURDAĞ, Hasan Fatih; Levent, Vecdi Emre
Biomedical signals (BSs), which give information about the normal condition and also the inherent irregularities of our body, are expected to have non-stationary character due to the time-varying behavior of physiological systems. The Fourier transform and the short time Fourier transform are the widely used frequency and time-frequency analysis methods for extracting information from BSs with fixed frequency and time-frequency resolution respectively. However, in order to derive relevant information from non-stationary BSs, an appropriate analysis method which exhibits adjustable time-frequency resolution is needed. The wavelet transform (WT) can be used as a mathematical microscope in which the time-frequency resolution can be adjusted according to the different parts of the signal. The discrete wavelet transform (DWT) is a fast and discretized implementation for classical WT. Due to the aliasing, lack of directionality and shift-variance disadvantages, the DWT exhibits limited performance in the process of BSs. In literature, an improved version of the DWT, which is named as Dual Tree Complex Wavelet Transform (DTCWT), is employed in the analysis of BSs with great success. In this study, considering the improvements in embedded system technology and the needs for wavelet based real-time feature extraction or de-noising systems in portable medical devices, the DTCWT is implemented as a sub-system in field programmable gate arrays. In proposed hardware architecture, for every data input-channel, DTCWT is implemented by using only one adder and one multiplier. Additionally, considering the multi-channel outputs of biomedical data acquisition systems, this architecture is designed with the capability of running in parallel for N channels.
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Field programmable gate arrays implementation of dual tree complex wavelet transform
(IEEE, 2015) Canbay, F.; Levent, Vecdi Emre; Serbes, G.; Goren, S.; Aydin, N.; Levent, Vecdi Emre
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.
Metadata only
A multi-channel real time implementation of dual tree complex wavelet Transform in field programmable gate arrays
(Springer International Publishing, 2016) Canbay, F.; Levent, Vecdi Emre; Serbes, G.; Uğurdağ, Hasan Fatih; Electrical & Electronics Engineering; UĞURDAĞ, Hasan Fatih; Levent, Vecdi Emre
In medical applications, biomedical acquisition systems (BASs) are frequently used in order to diagnose and monitor critical conditions such as stroke, epilepsy, Alzheimer disease, arrhythmias and etc. Biomedical signals (BSs), which produce valuable information about the condition of various physiological subsystems in our body, can be obtained by using multi-channel BASs. Due to the time-varying behavior of physiological sub-systems, most of the BSs are expected to have non-stationary character. In order to derive desired clinical information from these non-stationary BSs, an appropriate analysis method which exhibits adjustable time-frequency resolution is needed. The wavelet transform (WT), in which the time-frequency resolution can be adjusted according to the different parts of the signal, are widely used in the analysis of BSs. The discrete wavelet transform (DWT) is a fast and discretized implementation of classical WT and was employed as a feature extractor and de-noising operator for BSs in literature. However, due to the aliasing, lack of directionality and being shift-variance disadvantages, the DWT exhibits limited performance. A modified version of the DWT, which is named as Dual Tree Complex Wavelet Transform (DTCWT), is employed in the analysis of BSs and improved results are obtained. Therefore, in this study, considering the improvements in embedded system technology and the needs for wavelet based multi-channel real-time feature-extraction/de-noising operations in portable medical devices, the DTCWT is implemented as a multi-channel system-on-chip by using field programmable gate arrays. In proposed hardware architecture, for N input-channels, the DTCWT is implemented by using only one adder and one multiplier. The area efficiency and speed limits of proposed system are presented comparing with our previous approaches.