Artifact removal in thoracic electrical bioimpedance signals using robust diffusion least power algorithm.

By using thoracic electrical bioimpedance (TEB) analysis stroke volume calculated for sudden cardiac arrests. In this paper proposed robust normalized diffusion least power algorithm (RNDLPA) is proposed to get high resolution components. In clinical scenarios, TEB components are contaminated with various artifact components, which interrupts the identification of several features in stroke intensity. The number of multiplications is also one of the key elements for monitoring in health care applications. Hence by proposed RNDLPA algorithm it reduces computational complexity, stability is improved and also steady state error rate is reduced. To eliminate noise components various adaptive cancelers are presented and they are compared with proposed algorithm. Further to show performance improvement signal to noise ratio (SNR) improvement is taken into consideration it gets better values 14.3594 dB and 12.3551 dB for respiratory noise and muscle noise respectively when compared to existed techniques. [ABSTRACT FROM AUTHOR]