Abstract: Automated camera-based optical assessment involves color assessment of a physical object using conventional and inexpensive computer hardware such as a smartphone. A specially-configured test card includes a body supporting a reagent pad configured to change to an expected color in response to an enzymatic reaction, and an imaging key adjacent the reagent pad. The imaging key includes color fields including at least one field of the expected color. The hardware captures an image of the test card, and processes the image to identify the reagent pad and color fields, to process a brightness calibration target, to determine color values for the reagent pad and color fields, to calibrate the color values as a function of brightness and/or color by comparison to the brightness and color calibration targets, and to identify a color field most closely matching the reagent pad's color to determine a corresponding test result.

Abstract: A non-invasive blood sensor includes a body configured to mate with a tissue surface; a blue light source disposed on the sensor body; and a photodetector disposed on the sensor body at a suitable position for capturing light emanating from the tissue surface after emission from the blue light source, e.g., by one of: transmission, reflection, and transflection. The sensor bodies may further include a green, a red and/or an infrared light source. The light source(s) and photodetector(s) may be supported on a support structure configured to register with a corresponding portion of human anatomy in a predetermined fashion, and support the light sources and photodetectors in a defined spatial relationship. The sensor or an integrated meter may include a controller programmed to receive signals from the photodetector and calculate blood glucose value as function of the signals received from the photodetector after emission by the light source(s).

Abstract: A non-invasive blood sensor includes a body configured to mate with a tissue surface; a blue light source disposed on the sensor body; and a photodetector disposed on the sensor body at a suitable position for capturing light emanating from the tissue surface after emission from the blue light source, e.g., by one of: transmission, reflection, and transflection. The sensor bodies may further include a green, a red and/or an infrared light source. The light source(s) and photodetector(s) may be supported on a support structure configured to register with a corresponding portion of human anatomy in a predetermined fashion, and support the light sources and photodetectors in a defined spatial relationship. The sensor or an integrated meter may include a controller programmed to receive signals from the photodetector and calculate blood glucose value as function of the signals received from the photodetector after emission by the light source(s).

Abstract: A system for detecting one or more conditions of a subject. The system comprises: a processor; a memory; an intensity mapping component comprising instructions to receive breath sound data for a subject and to determine at least one time-frequency representation of said breath sound data; and a condition identifier component comprising instructions stored in said memory and operable to cause said system to analyze said at least one time-frequency representation to detect one or more conditions as a function of predetermined characteristics of said at least one time-frequency representation, and to store said at least one or more conditions to said memory. Breath sound data may be analyzed to determine whether one or more of a wheeze, a crackle and/or a whooping sound. Detection of wheezes, crackles and/or whoops may be used by an automated diagnostic engine for the purpose of determining a diagnosis.

Abstract: One aspect of the invention provides a computer-implemented method for diagnosing a condition. The computer-implemented method includes: (a) receiving one or more inputs regarding a subject's symptoms; (b) updating a plurality of models in parallel based on the one or more inputs, each model generating a numerical score reflecting a likelihood of one of a plurality of conditions; (c) identifying one or more most-likely conditions as a function of the numerical scores produced by the models; (d) requesting additional input based on the most-likely conditions; (e) receiving the additional input; (f) updating the models in parallel based on the additional input; (g) comparing updated numerical scores or a difference between sequenced updated numerical scores to a stored confidence threshold; and (h) repeating steps (c)-(g) until the compared numerical scores or the difference between sequenced numerical scores exceeds the stored confidence threshold.

Abstract: Automated camera-based optical assessment involves color assessment of a physical object using conventional and inexpensive computer hardware such as a smartphone. A specially-configured test card includes a body supporting a reagent pad configured to change to an expected color in response to an enzymatic reaction, and an imaging key adjacent the reagent pad. The imaging key includes color fields including at least one field of the expected color. The hardware captures an image of the test card, and processes the image to identify the reagent pad and color fields, to process a brightness calibration target, to determine color values for the reagent pad and color fields, to calibrate the color values as a function of brightness and/or color by comparison to the brightness and color calibration targets, and to identify a color field most closely matching the reagent pad's color to determine a corresponding test result.

Abstract: A non-invasive blood sensor includes a sensor body configured to mate with a tissue surface, light sources disposed on the sensor body, and a photodetector disposed on the sensor body in position for capturing light emanating from the tissue surface after emission from the blue light source by transmission, reflection or transflection. A non-invasive hemoglobin sensor includes blue, green and red light sources. A non-invasive WBC sensor includes green, red and infrared light sources. The light source(s) and photodetector(s) may be supported on a support structure configured to register with a corresponding portion of human anatomy in a predetermined fashion, to arrange them in a defined spatial relationship. The sensor or an integrated meter may include a controller programmed to receive signals from the photodetector and calculate blood hemoglobin and/or white blood cell counts as a function of the signals received from the photodetector(s) after emission by the light source(s).

Abstract: A non-invasive blood pressure sensor comprises tissue-matable sensor bodies that include a first light-source-and-photodetector pair disposed on one of the sensor bodies in a pre-determined spatial relationship for a proximal anatomical location, and a second light-source-and-photodetector pair disposed on one of the sensor bodies in a pre-determined spatial relationship for a distal anatomical location. The sensor bodies may be mounted on a support structure acting as a jig for aligning and/or spacing them.