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Nowadays, a computer-aided diagnosis system is required to monitor the cardiac patients continuously and detecting the heart diseases automatically. In this paper, a new field programmable gate array-based morphological feature extraction approach is proposed for electrocardiogram signal analysis. The proposed architecture is mainly based on the Generalized Synchrosqueezing transform but a detrended fluctuation analyzer is applied in the reconstruction stage for capturing the maximum information of QRS complexes and P-waves by eliminating a set of noisy intrinsic modes. Then, a correntropy envelope is determined from the QRS enhanced signal for localizing the QRS region accurately. Also, an adaptive heuristic framework is introduced to detect the true P-wave from the P-wave enhanced reconstructed signal by analyzing both the positive and negative amplitudes. In addition, a root mean square Error estimation-based adaptive thresholding approach is used to estimate the T-wave after removing the P-QRS complexes. The proposed architecture has been implemented on field programmable gate array using the Xilinx Vertex 7 platform. The performance of the proposed architecture is validated by performing a comparative study between the resultant performances and those attained with state-of-the-art feature descriptors, in terms of Sensitivity, accuracy, positive prediction, error rate and field programmable gate array resources estimation. The proposed sensitivity, accuracy and positive prediction are 99.84%, 99.85% and 99.86% for QRS detection approach. The proposed sensitivity, accuracy and positive prediction are 99.45%, 99.23% and 99.78% for P-wave detection approach. The proposed sensitivity, accuracy and positive prediction are 99.58%, 99.65% and 100% for T-wave detection approach. The simulation results show that the proposed architecture overtakes existing designs and minimizes hardware complexity, which proves the suitability of this approach on real-time applications of electrocardiogram signals.

Last few years have shown brisk intensification inInternet over the entire globe with heterogeneous networks. Hence the effectiveness of most important & inseparable part, TCP/IP protocol suite, plays a significant role. Wireless links involved in the formation of heterogeneous network is facing serious problems of random BER (Bit Error Rates) which causes random loss. The older TCP (Transmission Control Protocol) was designed for wired links, where the cause of packet loss was due to congestion only. The same protocol policies were incorporated in TCP/IP model with least changes initially. As this was unable to differentiate between losses due to congestion and due to corruption (BERs-random loss), it became the main cause of performance degradation of TCP on wireless links. This paper explores the way to add intelligence in TCP by modifying it to improve data rate in case of random losses which occur on wireless link frequently. Scenarios used to test algorithm are experiencing congestion and corruption loss individually as well as together. Standard BERs are used to measure performance. Modified protocol shows great performance improvement over unmodified in case of random loss as well as shows compatibility with an unmodified protocol in case of congestion loss only.