Multiple-Criteria Decision-Making Based on Probabilistic Estimation with Contextual Information for Physiological Signal Monitoring

We propose a multiple-criteria decision-making (MCDM) method based on Maximum A Posteriori (MAP) estimation to analyze users' physiological status either normal or abnormal. The decision-making problem is formulated using MAP estimation and is turned out to be MCDM problem given the assumption that all probability density functions (pdfs) follow exponential forms, especially Gaussian. It indicates that this MCDM equation is decomposed into direct sum of group's physiological status distribution. Group distribution is estimated by probabilistic approach using population from the same age or same sex. For verification, we applied the proposed method to public heart rate database. According to experimental results, the proposed method considering group context reduced overall classification errors by 20.42% compared to typical decision-making (TDM) method. This method is applicable to various personalized health monitoring applications, which estimates user's physiological status by referring other group distribution without prior knowledge about previous health records.

[1]  Melvin L. Moeschberger,et al.  Effect of Age and Other Factors on Maximal Heart Rate , 1982 .

[2]  Randolph A. Miller,et al.  Review: Medical Diagnostic Decision Support Systems - Past, Present, And Future: A Threaded Bibliography and Brief Commentary , 1994, J. Am. Medical Informatics Assoc..

[3]  George P. Huber,et al.  Multi-Attribute Utility Models: A Review of Field and Field-Like Studies , 1974 .

[4]  Dianne Hall,et al.  Engaging multiple perspectives: A value-based decision-making model , 2007, Decis. Support Syst..

[5]  R. Matthews,et al.  A Wearable Physiological Sensor Suite for Unobtrusive Monitoring of Physiological and Cognitive State , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  J P Wallace,et al.  Predicting max HR and the HR-VO2 relationship for exercise prescription in obesity. , 1993, Medicine and science in sports and exercise.

[7]  D. Feeny,et al.  Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. , 1996, Medical care.

[8]  Paul Lukowicz,et al.  AMON: a wearable multiparameter medical monitoring and alert system , 2004, IEEE Transactions on Information Technology in Biomedicine.

[9]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[10]  Salih O. Duffuaa,et al.  Determining Aggregate Criteria Weights from Criteria rankings by a Group of Decision Makers , 2008, Int. J. Inf. Technol. Decis. Mak..

[11]  T. Opthof,et al.  The normal range and determinants of the intrinsic heart rate in man. , 2000, Cardiovascular research.

[12]  Su-Shing Chen,et al.  Equilibrium and nonequilibrium Modeling of YinYang Wuxing for Diagnostic Decision Support in Traditional Chinese Medicine , 2009, Int. J. Inf. Technol. Decis. Mak..

[13]  Alexis Tsoukiàs,et al.  Modelling uncertain positive and negative reasons in decision aiding , 2007, Decis. Support Syst..

[14]  Jin Peng,et al.  Fuzzy Group Decision Making Model Based on Credibility Theory and Gray Relative Degree , 2009, Int. J. Inf. Technol. Decis. Mak..

[15]  Christer Carlsson,et al.  Fuzzy multiple criteria decision making: Recent developments , 1996, Fuzzy Sets Syst..

[16]  Zhengxin Chen,et al.  A Descriptive Framework for the Field of Data Mining and Knowledge Discovery , 2008, Int. J. Inf. Technol. Decis. Mak..

[17]  P. Gibbs,et al.  Active noise cancellation using MEMS accelerometers for motion-tolerant wearable bio-sensors , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  W.J. Kaiser,et al.  Context-aware Sensing of Physiological Signals , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  Hamidreza Eskandari,et al.  Handling Uncertainty in the Analytic Hierarchy Process: a Stochastic Approach , 2007, Int. J. Inf. Technol. Decis. Mak..