An Approach to Noise Reduction in Human Skin Admittance Measurements

This paper presents the development of a signal averaging algorithm for recovering excitation responses contaminated by overwhelming amount of various types of interference in skin admittance measurements. The algorithm is designed to eliminate Gaussian-distributed noise by use of a recursive approach. The process of recovering low magnitude voltage responses from highly noise-contaminated waveforms is a CPU-intensive task. In real-time measurements, iterative reconstruction algorithm is inefficient and time consuming when slow varying input waveforms are present. To increase the quality of the reconstruction a considerably large number of recursions is required. Increasing the number of recursions is appropriate for batch processing of measurement data. However, the algorithm considers measurements in real-time, whereas required quality, of signal reconstruction should be kept independent from the number of recursions. Presented at Annual International Conference of the IEEE Engingeering in Medicine and Biology Society (23rd) held in Istanbul, Turkey on 25-28 Oct 2001. See also ADM001351 for entire conference on CD-ROM. The original document contains color images.