Titlebook: Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders; M. Murugappan,Yuvaraj Rajamanickam Book 2022 The Editor(s) (

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A Novel Parametric Nonstationary Signal Model for EEG Signals and Its Application in Epileptic Seiz extracting the low-frequency average component, while the three-peak cluster in the frequency domain has been used for segmenting the EEG signals in order to capture its instantaneous parameters. The study has been done on the publicly available EEG database of the University of Bonn. Our study sug

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Catalogic Systematic Literature Review of Hardware-Accelerated Neurodiagnostic Systems,te array (FPGA), allowing rapid testing and deployment of hardware systems. Moreover, the novel neuromorphic platform has the potential to efficiently accelerate neural networks as well, which was not possible with the FPGA..In this chapter, we conduct a systematic review of hardware-accelerated neu

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Wearable Real-Time Epileptic Seizure Detection and Warning System,body were sent continuously to the detection and warning subsystem, where it was continuously processed and analyzed. The later block can also automatically alert the parent/caregiver of the patient over the cellular network in case of a seizure event. Among the various machine learning algorithms,

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Analysis of Intramuscular Coherence of Lower Limb Muscle Activities Using Magnitude Squared Coherent 1000?Hz, and it was recorded from six sites bilaterally: tibialis anterior (TA), medial gastrocnemius (MG), vastus lateralis (VL), rectus femoris (RF), semitendinosus (ST), and biceps femoris longus (BFL). In this study, we have analyzed different lower limb muscle pairs such as TA-MG, TA-VL, and

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