Abstract: Disclosed embodiments include a complete system and platform which allows for continuous monitoring of movement disorders during normal daily activities in the clinic, home, and other normal daily environments. The system comprises: 1) a wearable apparatus for continuous monitoring of movement disorders, 2) a docking station, 3) a web server, and 4) methods for statistical analysis that generate movement impairment measures.

Abstract: Disclosed embodiments include a complete integrated system designed to support continuous monitoring and objective analysis of movement disorders. According to one embodiment the integrated system allows for continuous monitoring of movement disorders during normal daily activities in home and other normal daily environments, as well as in the clinic. The integrated system comprises: 1) wearable movement monitoring devices including a plurality of inertial sensors, 2) a docking station with wireless capabilities, 3) a secure web-enabled data server, and 4) statistical signal processing methods, all of which are integrated to enable monitoring and analysis of movement disorders.

Abstract: Disclosed embodiments include an apparatus for generating a plurality of movement impairment indices from one or more kinematic signals to characterize movement disorders. Additionally we disclose methods for generating a plurality of movement impairment indices from one or more kinematic signals obtained from one or more kinematic sensors, said methods implemented in a digital computer with one or more processors in order to characterize movement disorders based on spectral analysis, regularity metrics, and time-frequency analsysis.

Abstract: A lightweight portable probe or transducer containing a transmissive or reflective electro-optical emitter and receptor in the infrared spectrum is fitted on a subject's finger or toe. Associated electronics energize and monitor the probe, detect cardio-rhythmic fluctuations therefrom, and process digital data over a prescribed window to produce a non-invasive, qualitative or quantitative measure of the subject's circulation. In accordance with one embodiment of the invention, a simple tri-color LED array is used to indicate the subject's circulation as being normal, reduced, or borderline.

Abstract: An integrated collaborative platform which allows for data sharing, data analysis, knowledge creation and sharing, problem solving, trading, and accelerated scientific discovery by collaborating teams which may be formed on an ad-hoc basis among users of the system is disclosed. The platform is designed to accelerate research and improve clinical care of chronic conditions. It provides a central place to facilitate interactions between the many different groups that participate in these activities. The central features of the system can be tailored to best suit each chronic condition.

Abstract: The invented non-invasive vital signs monitor is in a flexible, nominally flat planar form having integral gel electrodes, a sticky-back rear surface, an internal flex circuit capable of sensing, recording and playing out several minutes of the most recently acquired ECG waveform data and a front surface that includes an outplay port. The invented non-invasive body composition ‘risk’ monitor includes a measurement device for monitoring one or more variables including body fluid mass, dehydration, respiratory rate, blood pressure, bio-impedance, cardiography such as cardiac output, and body conformation parameters. The risk monitor may be provided in a lightweight carrying case into which the vital signs monitor plugs. Finally, a lightweight portable probe or transducer containing a transmissive or reflective electro-optical emitter and receptor in the infrared spectrum is fitted on a subject's finger or toe.

Abstract: A lightweight portable probe or transducer containing a transmissive or reflective electro-optical emitter and receptor in the infrared spectrum is fitted on a subject's finger or toe. Associated electronics energize and monitor the probe, detect cardio-rhythmic fluctuations therefrom, and process digital data over a prescribed window to produce a non-invasive, qualitative or quantitative measure of the subject's circulation. In accordance with one embodiment of the invention, a simple tri-color LED array is used to indicate the subject's circulation as being normal, reduced, or borderline.

Abstract: The present invention provides a method, system, and apparatus to monitor cardiovascular signals such as arterial blood pressure (ABP), pulse oximetry (POX), and intracranial pressure (ICP). The system can be used to calculate and monitor useful clinical information such as heart rate, respiratory rate, pulse pressure variation (PPV), harmonic phases, pulse morphology, and for artifact removal. The method uses a statistical state-space model of cardiovascular signals and a generalized Kalman filter (EKF) to simultaneously estimate and track the cardiovascular parameters of interest such as the cardiac fundamental frequency and higher harmonics, respiratory fundamental frequency and higher harmonics, cardiac component harmonic amplitudes and phases, respiratory component harmonic amplitudes and phases, and PPV.

Abstract: A method of isolating sources of variance in parametric data includes steps of: (a) cleaning a data set of measurements for a plurality of parameters; (b) generating a principal component analysis basis from the cleaned data set; (c) estimating an independent component analysis model from the principal component analysis basis; (d) calculating percentages of variance for the plurality of parameters explained by each component in the estimated independent component analysis model; (e) if the calculated percentages of variance indicate that a component is a minor component, then transferring control to step (f), else transferring control to step (g); (f) removing the minor component from the principal component analysis basis and transferring control to step (c); and (g) generating as output the estimated independent component analysis model wherein no component of the independent component analysis model is a minor component.

Abstract: Methods of processing neuronal signals include processing microelectrode recordings (MERs) or portions of MERs to provide arrays of associated values, such as estimates of power spectral density, or a marginal probability distribution, or a rate of change of a spike rate. Such arrays of values can be displayed, and a classifier can be applied to, for example, aid in associating a MER with a particular brain feature.

Abstract: A method for selecting test site locations on a substrate, by a) specifying a subset of all test site locations on the substrate, and b) selecting a desired number of candidate test site locations from within the subset of test site locations on the substrate. c) While selecting one of the candidate test site locations and holding all others of the candidate test site locations as fixed, determining a new location for the selected one of the candidate test site locations, which new location increases a test sensitivity, as estimated by a trace of a variance-covariance matrix. d) Repeating step (c) for each candidate test site location in the subset of test site locations, to produce a finalized set of candidate test site locations, until a desired end point is attained.

Abstract: A method for determining component patterns of a raw substrate map. A subset of substrate patterns is selected from a set of substrate patterns, and combined into a composite substrate map. The substrate patterns are weighted. The composite substrate map is compared to the raw substrate map, and a degree of correlation between the composite substrate map and the raw substrate map is determined. The steps are iteratively repeated until the degree of correlation is at least a desired degree, and the weighted subset of substrate patterns is output as the component patterns of the raw substrate map.

Abstract: A method for determining outlier data points in an ordered dataset of values. a) A subset of dataset patterns is selected from a set of mathematical dataset patterns, and b) the subset of dataset patterns is combined into a composite dataset. c) The composite dataset is compared to the ordered dataset of values, and d) a degree of correlation between the composite dataset and the ordered dataset of values is determined. e) Data points within the composite dataset are selectively weighted to improve the degree of correlation, and f) steps a through e are selectively iteratively repeated until the degree of correlation is at least a desired value. g) Residuals for the data points within the composite dataset are selectively determined. h) At least one of (1) the weighted data points within the composite dataset that are weighted within a first specified range, and (2) data points within the composite dataset that have a residual within a second specified range, are selectively output as outlier data points.

Abstract: A method of isolating sources of variance in parametric data includes steps of: (a) cleaning a data set of measurements for a plurality of parameters; (b) generating a principal component analysis basis from the cleaned data set; (c) estimating an independent component analysis model from the principal component analysis basis; (d) calculating percentages of variance for the plurality of parameters explained by each component in the estimated independent component analysis model; (e) if the calculated percentages of variance indicate that a component is a minor component, then transferring control to step (f), else transferring control to step (g); (f) removing the minor component from the principal component analysis basis and transferring control to step (c); and (g) generating as output the estimated independent component analysis model wherein no component of the independent component analysis model is a minor component.