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Physiological signals as output of the human complex system are typically nonlinear and non-stationary, and much information is hidden in the dynamics of their fluctuations. By applying conventional analysis techniques based on averaged quantities and other features of histogram and classical power spectrum analysis, some important characteristic properties of the signal dynamics are neglected... |
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Objective 1: Test the hypothesis---based upon our preliminary findings---that essential medical information is hidden in the non-equilibrium dynamics of physiologic rhythms when recorded over long time periods, as well as in the synchronization properties of the various physiological-signals and their interactions. Objective 2: Collect and analyze long-term data from targeted groups of individuals with specific medical conditions. Initiate the concept of physiological network, which, in combination with suitable algorithms, provides novel, quantitative status indices for specific debilitating pathologies. Objective 3: Adapt an existing wearable personal monitoring system for the needs of simultaneous long-term recording of data from multiple physiological-sensors and its collection and transmission for offline analysis. Objective 4: Create a repository of signals and algorithms to serve the research community. The database will be addressable not only according to data records, but according to synchronization phenomena and network properties. |
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