An Adaptively Tunable Model of the Cardiac Signal for the Bio-Impedance Signal Decomposer (BISD)

Abstract

The paper presents the further development of the bioimpedance signal decomposer (BISD) of the total bio-impedance (BI) signal to its cardiac and respiratory components. The Jacobi orthonormal polynomials based adaptively tunable model of the cardiac BI signal is proposed in the paper, which plays very important role in the decomposition task. The importance arises from the fact, that the BISD must be reliable and have to correct operate with signals taken from different persons, and in such cases, when the cardiac BI signal of a person is changing in time. For the proposed system the reliability significantly depends on the difference between the model of the cardiac signal and the real cardiac signal (the reference signal). The averaged through several periods version ofthe already separated cardiac BI signal is used as reference signal in the proposed algorithm for tuning the parameters ofthe cardiac BI signal model using a modified Newton adaptation algorithm. After the model is elaborated, the system separates the cardiac and the respiratory components more accurately by tracking the cardiac BI signal.

Bio-impedance signal decomposer: enhanced accuracy and reduced latency solution

“…The proposed improvements allowed to reduce the length of the FIR filters (Fig. 2) from 801 samples (in the previous version of the BISD [ [23][24][25][26][27]) to 401 samples. Thus the latency of the BISD is reduced from two to one second, taking into account that the whole BISD system sampling rate is 200 samples/s.…”

“…An adaptive bio-impedance signal decomposer, intended to solve the signals separation task and to overcome related difficulties, was proposed by the author in [ [23][24][25][26][27].…”

“…2. The module, which constructs the cardiac signal model by tracking its parameters synchronously with the estimated cardiac signal, is named signal-shape locked loop (SSLL), which is described in [25][26][27].…”

“…An amplitude estimator, which was used in the BISD before applying the proposed one, is described in [23][24][25][26][27]. In that correlation-based estimator, the input cardiac signal is multiplied by the in-phase reference signal, after that an absolute value of the result is passed through the IIR low-pass filter for smoothing the final amplitude estimate and then scaling it by a predefined constant factor.…”

Decomposition method of an electrical bio-impedance signal into cardiac and respiratory components

“…To compensate this insufficiency, more components of the ASOB can be introduced, e.g., using of five or six components can already solve the problem. A more perspective way is to use the signal model with adaptively tunable parameters A and B, which has recently been proposed by Krivoshei et al (2008).…”