Abstract: A system for measuring pain of a person, the system for use with the tissue of the person. Various sensors and detectors on the tissue provide signals to a controller for determining and indicating a pain level of the person.

Abstract: A multimode biological sample inspection apparatus and method is provided. The apparatus includes an illumination hardware arrangement comprising transmission and sensing hardware configured to inspect a biological sample using at least two modes from a group comprising a fluorescence imaging mode, a reflectance imaging mode, a scattering imaging mode, and a Raman imaging mode, and processing hardware configured to operate the illumination hardware arrangement according to a protocol comprising inspection settings of the at least two modes. The processing hardware receives scan results from the illumination hardware arrangement and identifies attributes of the biological sample by constructing a multidimensional dataset comprising at least one spatial dimension and at least one spectral dimension from the scan results and analyzing the multidimensional dataset. The processing hardware is configured to employ the attributes of at least one biological sample and alter the protocol.

Abstract: A computer-implemented method is disclosed. The computer-implemented method comprises receiving, by a computer system, ingestible event marker (IEM) system information from a receiver worn by a subject, the IEM system information comprising information associated with ingestion of medication by the subject, wherein the receiver is configured to communicate with the computer system; receiving, by the computer system, contextual information associated with the subject; and calculating, by the computer system, a composite risk score based on the IEM system information and the contextual information associated with the subject.

Abstract: A system for assessing biological tissue is disclosed.

Abstract: A multimode biological sample inspection apparatus and method is provided. The apparatus includes an illumination hardware arrangement comprising transmission and sensing hardware configured to inspect a biological sample using at least two modes from a group comprising a fluorescence imaging mode, a reflectance imaging mode, a scattering imaging mode, and a Raman imaging mode, and processing hardware configured to operate the illumination hardware arrangement according to a protocol comprising inspection settings of the at least two modes. The processing hardware receives scan results from the illumination hardware arrangement and identifies attributes of the biological sample by constructing a multidimensional dataset comprising at least one spatial dimension and at least one spectral dimension from the scan results and analyzing the multidimensional dataset. The processing hardware is configured to employ the attributes of at least one biological sample and alter the protocol.

Abstract: A system for quantitatively measuring dyspnea experienced by a person includes a hemodynamic sensor system configured to be held in close proximity to, or in contact with, the person's head or neck, and measure hemodynamic parameters of the person. The system includes a respiratory sensor system to measure respiratory metrics of the person, and a data processor configured to communicate with the hemodynamic sensor system to receive the hemodynamic parameters and with the respiratory sensor system to receive the respiratory metrics. The data processor is configured to calculate, based on the hemodynamic parameters, a quantitative score to represent physical discomfort experienced by the person, and make a determination, based on the quantitative score and the respiratory metrics, that the physical discomfort is caused by dyspnea rather than physical pain. The determination includes a sub-determination that the respiratory metrics have changed by a particular amount within a particular period of time.

Abstract: A multimode biological sample inspection apparatus and method is provided. The apparatus includes illumination hardware arrangement including transmission and sensing hardware, the illumination hardware arrangement configured to inspect a biological sample using at least two modes from a fluorescence imaging mode, a reflectance imaging mode, a scattering imaging mode, and a Raman imaging mode, and processing hardware configured to operate the illumination hardware arrangement according to a protocol including inspection settings of the at least two modes. The processing hardware receives scan results from the illumination hardware arrangement and identifies attributes of the biological sample. The processing hardware is configured to employ the attributes of at least one biological sample to alter the protocol.

Abstract: A system for measuring pain of a person, the system for use with the tissue of the person. Various sensors and detectors on the tissue provide signals to a controller for determining and indicating a pain level of the person.

Abstract: A multimode biological sample inspection apparatus and method is provided. The apparatus includes illumination hardware arrangement including transmission and sensing hardware, the illumination hardware arrangement configured to inspect a biological sample using at least two modes from a fluorescence imaging mode, a reflectance imaging mode, a scattering imaging mode, and a Raman imaging mode, and processing hardware configured to operate the illumination hardware arrangement according to a protocol including inspection settings of the at least two modes. The processing hardware receives scan results from the illumination hardware arrangement and identifies attributes of the biological sample. The processing hardware is configured to employ the attributes of at least one biological sample to alter the protocol.

Abstract: The present invention provides a method for detection of different ontologies using advanced unsupervised machine learning which will be used to visualize factors not visible to the human observer, such as unknown characteristics between imaging datasets and other factors to provide insights into the structure of the data. This methodology is referred to herein as Contribution Scattergram. An example includes using radiological images to determine a relationship in dimension, structure, and distance between each parameter. This information can be used to determine if changes in the images have occurred and for treatment response.

Abstract: The present invention discloses a physiological monitoring device, comprising: a physiological signal acquisition block in the form of a capacitive touch panel for detecting user's physiological signals; a micro-processor block for capturing capacitance change in accordance with the user's physiological signal and estimating user's physiological data; and an application program for controlling the operation of physiological monitoring device.

Abstract: The present invention provides a method for detection of different ontologies using advanced unsupervised machine learning which will be used to visualize factors not visible to the human observer, such as unknown characteristics between imaging datasets and other factors to provide insights into the structure of the data. This methodology is referred to herein as Contribution Scattergram. An example includes using radiological images to determine a relationship in dimension, structure, and distance between each parameter. This information can be used to determine if changes in the images have occurred and for treatment response.

Abstract: The ability to identify anomalous behavior in video recordings is important for security and public safety. Current identification techniques, however, suffer from a number of limitations. The present invention describes a novel identification technique that permits unsupervised, automatic identification of moving objects and anomaly detection in real-time recordings (MovA). The present invention specifically utilizes a novel real-time manifold learning system (RML), which generates a semantic crowd behavior descriptor that the inventors call a Trackogram. The Trackogram can be used to identify anomalous crowd behavior collected from video recordings in a real-time manner. MovA can be used to detect anomaly in standard video datasets. Importantly, MovA is also able to identify anomalies in night-vision stereo sequences. Ultimately, MovA could be incorporated into a number of existing products, including video monitoring cameras or night-vision goggles.

Abstract: A computer-implemented method is disclosed. The computer-implemented method comprises receiving, by a computer system, ingestible event marker (IEM) system information from a receiver worn by a subject, the IEM system information comprising information associated with ingestion of medication by the subject, wherein the receiver is configured to communicate with the computer system; receiving, by the computer system, contextual information associated with the subject; and calculating, by the computer system, a composite risk score based on the IEM system information and the contextual information associated with the subject.

Abstract: Featured are methods and systems to multiparametric non-linear dimension reduction (NLDR) methods for segmentation and classification of radiological images. Such methods for segmentation and classification of radiological images, includes pre-processing of acquired image data; and reconstructing the acquired image data using a non-linear dimension reduction technique so as to yield an embedded image representing all of the acquired, where the acquired image data comprises a plurality of different sets of image data of the same region of interest. Such NLDR methods and systems are particularly suitable for the ability to combine multiple input images into a single unit for increased specificity of diagnosis.

Abstract: Featured are methods and systems for reslicing-based nonrigid registration of multiparametric and modality images or objects. In such registration methods, global motion is modeled by multiple affine transforms (rigid), while local motion and slices matching is estimated using non-uniform radial reslicing of RTV to search for best match between reference volume slices and resampled target volume (RTV), orthogonally re-sliced to higher spatial resolution compared to the spatial resolution of the reference volume. The reference and target volumes can be in any plane and the method presented in this invention transfers them to target plane which can be any of axial, coronal, or sagittal and there is no need for the original and target scanning planes to be the same.

Abstract: A system for measuring pain of a person, the system for use with the tissue of the person. Various sensors and detectors on the tissue provide signals to a controller for determining and indicating a pain level of the person.

Abstract: Featured are methods and systems to multiparametric non-linear dimension reduction (NLDR) methods for segmentation and classification of radiological images. Such methods for segmentation and classification of radiological images, includes pre-processing of acquired image data; and reconstructing the acquired image data using a non-linear dimension reduction technique so as to yield an embedded image representing all of the acquired, where the acquired image data comprises a plurality of different sets of image data of the same region of interest. Such NLDR methods and systems are particularly suitable for the ability to combine multiple input images into a single unit for increased specificity of diagnosis.

Abstract: Featured are methods and systems for reslicing-based nonrigid registration of multiparametric and modality images or objects. In such registration methods, global motion is modeled by multiple affine transforms (rigid), while local motion and slices matching is estimated using non-uniform radial reslicing of RTV to search for best match between reference volume slices and resampled target volume (RTV), orthogonally re-sliced to higher spatial resolution compared to the spatial resolution of the reference volume. The reference and target volumes can be in any plane and the method presented in this invention transfers them to target plane which can be any of axial, coronal, or sagittal and there is no need for the original and target scanning planes to be the same.