title: Process techniques for human thoracic electrical bio-impedance signal in remote healthcare systems.
abstract: Analysis of thoracic electrical bio-impedance (TEB) facilitates heart stroke volume in sudden cardiac arrest. This Letter proposes several efficient and computationally simplified adaptive algorithms to display high-resolution TEB component. In a clinical environment, TEB signal encounters with various physiological and non-physiological phenomenon, which masks the tiny features that are important in identifying the intensity of the stroke. Moreover, computational complexity is an important parameter in a modern wearable healthcare monitoring tool. Hence, in this Letter, the authors propose a new signal conditioning technique for TEB enhancement in remote healthcare systems. For this, the authors have chosen higher order adaptive filter as a basic element in the process of TEB. To improve filtering capability, convergence speed, to reduce computational complexity of the signal conditioning technique, the authors apply data normalisation and clipping the data regressor. The proposed implementations are tested on real TEB signals. Finally, simulation results confirm that proposed regressor clipped normalised higher order filter is suitable for a practical healthcare system.
authors.affiliation: Department of Electronics and Communication Engineering , K. L. University , Green Fields, Guntur-522502 , India.
authors.forename: Muhammad Zia Ur
authors.initials: MZ
authors.lastname: Rahman
authors.affiliation: Department of Electronics and Communication Engineering , K. L. University , Green Fields, Guntur-522502 , India.
authors.forename: Shafi Shahsavar
authors.initials: SS
authors.lastname: Mirza
keywords: TEB enhancement; TEB signal; adaptive filter; adaptive filters; biomedical telemetry; cardiac arrest; data normalisation; data regressor; health care; heart stroke volume; high-resolution TEB component; human thoracic electrical bioimpedance signal; medical signal processing; patient monitoring; remote health care system; wearable health care monitoring tool