Dumett M, Rosen G, Sabat J, Shaman A, Tempelman L, Wang C, Swift Rm
University of Southern California, Department of Mathematics, Kaprielian Hall, Room 108, 3620 Vermont Avenue, Los Angeles, CA 90089-2532.
Appl Math Comput. 2008 Mar 1;196(2):724-743. doi: 10.1016/j.amc.2007.07.026.
Biosensor measurement of transdermal alcohol oncentration in perspiration exhibits significant variance from subject to subject and device to device. Short duration data collected in a controlled clinical setting is used to calibrate a forward model for ethanol transport from the blood to the sensor. The calibrated model is then used to invert transdermal signals collected in the field (short or long duration) to obtain an estimate for breath measured blood alcohol concentration. A distributed parameter model for the forward transport of ethanol from the blood through the skin and its processing by the sensor is developed. Model calibration is formulated as a nonlinear least squares fit to data. The fit model is then used as part of a spline based scheme in the form of a regularized, non-negatively constrained linear deconvolution. Fully discrete, steepest descent based schemes for solving the resulting optimization problems are developed. The adjoint method is used to accurately and efficiently compute requisite gradients. Efficacy is demonstrated on subject field data.
生物传感器对汗液中经皮酒精浓度的测量在不同受试者和不同设备之间存在显著差异。在受控临床环境中收集的短期数据用于校准乙醇从血液到传感器传输的正向模型。然后，使用校准后的模型对在现场收集的经皮信号（短期或长期）进行反演，以获得对呼气测量的血液酒精浓度的估计。开发了一个用于乙醇从血液通过皮肤正向传输及其被传感器处理的分布参数模型。模型校准被表述为对数据的非线性最小二乘拟合。然后，拟合模型被用作基于样条的方案的一部分，该方案采用正则化、非负约束线性反卷积的形式。开发了用于求解由此产生的优化问题的完全离散、基于最速下降的方案。伴随方法用于准确有效地计算所需梯度。在受试者现场数据上证明了其有效性。
