Error Correction Algorithm for High Accuracy Bio-Impedance Measurement in Wearable Healthcare Applications

Implantable and ambulatory measurement of physiological signals such as Bio-impedance using miniature biomedical devices needs careful tradeoff between limited power budget, measurement accuracy and complexity of implementation. This paper addresses this tradeoff through an extensive analysis of different stimulation and demodulation techniques for accurate Bio-impedance measurement. Three cases are considered for rigorous analysis of a generic impedance model, with multiple poles, which is stimulated using a square/sinusoidal current and demodulated using square/sinusoidal clock. For each case, the error in determining pole parameters (resistance and capacitance) is derived and compared. An error correction algorithm is proposed for square wave demodulation which reduces the peak estimation error from 9.3% to 1.3% for a simple tissue model. Simulation results in Matlab using ideal RC values show an average accuracy of for single pole and for two pole RC networks. Measurements using ideal components for a single pole model gives an overall and readings from saline phantom solution (primarily resistive) gives an . A Figure of Merit is derived based on ability to accurately resolve multiple poles in unknown impedance with minimal measurement points per decade, for given frequency range and supply current budget. This analysis is used to arrive at an optimal tradeoff between accuracy and power. Results indicate that the algorithm is generic and can be used for any application that involves resolving poles of an unknown impedance. It can be implemented as a post-processing technique for error correction or even incorporated into wearable signal monitoring ICs.