Through wearable technology, several chronic diseases are diagnosed by long-term
monitoring of vital signs specifically ECG, EMG, EEG biosignals. Such prolonged monitoring …

Combination of interval and amplitude threshold-based algorithms have been tested
rigorously over the last few decades for detecting the QRS-complexes in electrocardiogram …

Psychophysiological computing can be utilized to analyze heterogeneous physiological
signals with psychological behaviors in the Internet of Medical Things (IoMT). Since IoMT …

The smart grid is a fully automatic delivery grid for electricity power with a two-way reliable
flow of electricity and information among different equipment on the grid. Smart meters and …

Electrocardiogram, electromyogram, electroencephalogram are the foremost required vital
signs for diagnosing chronic diseases like sleep disorder, mood disorder, epilepsy etc …

Objective: Extraction and analysis of various clinically significant features of
photoplethysmogram (PPG) signals for monitoring several physiological parameters, as well …

Singular value decomposition (SVD) is a central mathematical tool for several emerging
applications in embedded systems, such as multiple-input multiple-output (MIMO) systems …

This work presents an automatic and robust algorithm for surface electromyography signals
segmentation in dynamic experimental protocol. The signals are segmented based on the …

In recent years, vector-to-vector mapping-based raw waveform biosignal enhancement
methods have gained significant attention in remote health monitoring system. In this paper …

Objective: Assessing the respiratory and lung mechanics of the patients in intensive care
units is of utmost need in order to guide the management of ventilation support. The …