Abstract: An in vitro sensor point-of-care sensor including a substrate, a sensing system, and a reference system. The substrate can include a first cavity and a second cavity. The sensing system can be disposed within the first cavity and include an optode membrane, a selectively-permeable membrane, and a plurality of microbeads. The optode membrane can be sensitive to an analyte in the biological fluid. The selectively-permeable membrane can cover an opening of the first cavity. The plurality of microbeads can be associated with at least one of the optode membrane and the selectively-permeable membrane. The reference system can be disposed within the second cavity.

Abstract: An in vitro sensor for point-of-care detection of at least one analyte or reaction product includes an inert, impermeable substrate, a sensing system, and a reference system. The substrate includes a first transparent surface oppositely disposed from a second surface and first and second cavities. Each of the first and second cavities defines an opening at the second surface. The sensing system is disposed in at least a portion of the first cavity and includes an analyte-detection optode membrane, an analyte-permeable membrane, and a plurality of non-transparent microbeads associated with at least one of the analyte-detection optode membrane and the analyte-permeable membrane. The analyte-permeable membrane is layered upon the analyte-detection optode membrane and covers the opening of the first cavity. The reference system is disposed in at least a portion of the second cavity.

Abstract: An in vitro sensor for point-of-care detection of at least one analyte or reaction product includes an inert, impermeable substrate, a sensing system, and a reference system. The substrate includes a first transparent surface oppositely disposed from a second surface and first and second cavities. Each of the first and second cavities defines an opening at the second surface. The sensing system is disposed in at least a portion of the first cavity and includes an analyte-detection optode membrane, an analyte-permeable membrane, and a plurality of non-transparent microbeads associated with at least one of the analyte-detection optode membrane and the analyte-permeable membrane. The analyte-permeable membrane is layered upon the analyte-detection optode membrane and covers the opening of the first cavity. The reference system is disposed in at least a portion of the second cavity.

Abstract: A method for solving deconvolution problems where it is desired to reconstruct a signal over a time range or another variable of interest involves comparing shapes of measured and reconstructed plots. The optimization method is based on minimizing the error in shape (as opposed to the square errors in amplitude). A shape approach method characterizes similarity of two functions by computing the angle between the two when they are treated as two vectors in the n dimensional space where n is the number of data points it is desired to consider from both functions (the functions themselves may consist of more than n data points). A new approximation is then created by trying to decrease the disimilarity between the actual and predicted functions. This dissimilarity is measured as the angle between the two corresponding vectors, so the measure of dissimilarity is the size of the angle.

Abstract: A method for solving deconvolution problems where it is desired to reconstruct a signal over a time range or another variable of interest involves comparing shapes of measured and reconstructed plots. The optimization method is based on minimizing the error in shape (as opposed to the square errors in amplitude). A shape approach method characterizes similarity of two functions by computing the angle between the two when they are treated as two vectors in the n dimensional space where n is the number of data points it is desired to consider from both functions (the functions themselves may consist of more than n data points). A new approximation is then created by trying to decrease the disimilarity between the actual and predicted functions. This dissimilarity is measured as the angle between the two corresponding vectors, so the measure of dissimilarity is the size of the angle.