The measurement of human respiratory signals is crucial in cyberbiological systems. A
disordered breathing pattern can be the first symptom of different physiological, mechanical …

Respiratory disorder is a highly prevalent condition associated with many adverse health
problems. As the current means of diagnosis are obtrusive and ill-suited for real-time m …

This paper introduces a novel multi-classification technique, which improves two conflicting
main objectives of classification problems, ie, classification accuracy and worst case …

Abstract Approximately, 21,000 breaths per day and 10.5 million breaths per year are taken
by average people. Breathing functions depend on the actions of the respiratory muscles on …

Automated methods of real-time and un-obstructive patient's respiration and position
monitoring have been subjects of interests in e-health applications. The present study …

Falls are a major healthcare concern especially in the older population and tripping is a
primary cause. Tripping is defined biomechanically as an event at which the lowest part of …

This paper considers the problem of self-calibration of multi-sensor systems for health care
cyber-biological systems, such as closed-loop glucose control. The recalibration method is …

In order to prevent the lack of appropriate respiratory ventilation which causes brain damage
and critical problems, it is required to continuously monitor the breathing signal of a patient …

In this paper, we present a decentralized data fusion architecture to achieve Fault Diagnosis
(FD) and Fault Tolerant Control (FTC) of sensors, which is effective under circumstances as …

Sensor data fusion is a common approach to provide accurate and fault-tolerant sensor
readouts in a multisensor system. This paper proposes an efficient data fusion algorithm …