Removing the motion artifacts from measured photoplethysmography (PPG) signals is one of the important issues to be tackled for the accurate measurement of arterial oxygen saturation during movement. In this paper, the motion artifacts were reduced by exploiting the quasi-periodicity of the PPG signal and the independence between the PPG and the motion artifact signals. The combination of independent component analysis and block interleaving with low-pass filtering can reduce the motion artifacts under the condition of general dual-wavelength measurement. Experiments with synthetic and real data were performed to demonstrate the efficacy of the proposed algorithm.

In this paper, the three-dimensional geometry of the human cochlea is modeled by the helico-spiral seashell model. The 3-D helico-spiral model, the generalized representation of the Archimedian spiral model, provides a framework for measuring cochlear features based on consistent estimation of model parameters. Nonlinear least square minimization based algorithms are developed for the identification of rotation, center and intrinsic parameters of the helico-spiral representation. Two algorithms are designed for the rotation axis aligned to the modiolar axis: one is more susceptible in the presence of noise, while the other allows applicability to two-dimensional data sets. The estimated center and intrinsic parameters allow the calculation of length, height and angular positions needed for frequency mapping of multichannel cochlear implant electrodes. Model performance is evaluated with numerically synthesized curves with different levels of added random noise, histologic data and real human cochlear spiral computed tomography data.

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