A medical capsule with a sensor device comprising a light emitting element and a light detecting element with the sensor device being adapted to detect the presence or non-presence of blood and/or Biliverdin based on the light absorption properties of blood and Biliverdin. The capsule is provided with a casing forming a gap at its outer surface. The light emitting element alternatively emits violet light of a wavelength of about 380-450 nm, green light of a wavelength of about 530-580 nm, and red light of a wavelength of about 620-750 nm, whereas the light detecting element generates a separate sensor signal associated with measured light intensities I.sub.violet, I.sub.green, and I.sub.red of at least each of the wavelength ranges of the light from the light emitting element. By evaluating a quotient I.sub.red/I.sub.green, false-positive detection of blood can be avoided. The present disclosure also relates to a calibration method for said medical capsule.

Some embodiments of a system or method for treating heart tissue can include a control system and catheter device operated in a manner to intermittently occlude a heart vessel for controlled periods of time that provide redistribution of blood flow. In particular embodiments, the system and methods may be configured to monitor at least one input signal detected at a coronary sinus and thereby execute a process for determining a satisfactory time period for the occlusion of the coronary sinus. In further embodiments, after the occlusion of the coronary sinus is released, the control system can be configured to select the duration of the release phase before the starting the next occlusion cycle.

Embodiments for crossing an occlusion by controlling a guide with the aid of optical coherence tomography (OCT) data are described. Embodiments include transmitting one or more beams of radiation via one or more waveguides on a flexible substrate within a guide wire. One or more beams of scattered or reflected radiation may be received from a sample via one or more waveguides. Depth-resolved optical data of the sample may be generated based on the received beams of scattered or reflected radiation. The depth-resolved data may be used for determining at least one of a distance between the guide wire and a wall of the artery and a distance between the guide wire and an occlusion within the artery. A position of the guide wire within the artery may then be controlled based on the determined distance or distances.

Disclosed is a medical data processing method for determining an indicator relating to an injury of an anatomical structure (1) of a patient, wherein the method comprises executing, on at least one processor (5) of at least one computer (3), steps of: a) acquiring (S1) acceleration data describing an energy of a set of one or more signals in dependence on both time and frequency, the set of signals acquired by measuring the acceleration of the anatomical structure (1) over time; b) acquiring (S2) analysis data describing an analysis rule for determining at least one of b1) an overall energy level of at least one signal of the set of signals, b2) a correlation between at least two signals of the set of signals in the frequency domain, the at least two signals respectively measured at at least two different respective regions of the anatomical structure (1), or b3) a relationship between energies given for at least two different frequency ranges of at least one signal of the set of signals; c) determining (S3) indicator data describing the indicator based on the acceleration data and the analysis data.

Disclosed is a medical data processing method for determining an indicator relating to an injury of an anatomical structure (1) of a patient, wherein the method comprises executing, on at least one processor (5) of at least one computer (3), steps of: a) acquiring (S1) acceleration data describing an energy of a set of one or more signals in dependence on both time and frequency, the set of signals acquired by measuring the acceleration of the anatomical structure (1) over time; b) acquiring (S2) analysis data describing an analysis rule for determining at least one of b1) an overall energy level of at least one signal of the set of signals, b2) a correlation between at least two signals of the set of signals in the frequency domain, the at least two signals respectively measured at at least two different respective regions of the anatomical structure (1), or b3) a relationship between energies given for at least two different frequency ranges of at least one signal of the set of signals; c) determining (S3) indicator data describing the indicator based on the acceleration data and the analysis data.

Embodiments described relate to techniques for identifying and characterizing biological structures using machine learning techniques. These techniques may be employed to enable a device to identify the particular type of tissue and/or cells (e.g., platelets, smooth muscle cells, or endothelial cells) in, for example, a biological structure, which may be a tissue or a lesion of a duct (e.g., vasculature) in an animal (e.g., a human or non-human animal), among other structures. The machine learning techniques may use raw impedance spectroscopy measurement data in addition to values derived from that raw data. In addition, the machine learning techniques may be used to select frequencies at which to measure impedance and select features to extract from the measured impedance at the selected frequencies to arrive at a small set of frequencies that allow for reliable differentiation.

Systems for determining fractional flow reserve are disclosed. An example system may include a pressure sensing guidewire for measuring a first pressure, a second pressure sensing medical device for measuring a second pressure, and a processor coupled to the pressure sensing guidewire and coupled to the second pressure sensing medical device. The processor may be designed to generate a plot of the magnitude of the second pressure over time, identify one or more time intervals of the plot that have a slope less than zero, determine a mean of the second pressure, and calculate the ratio of the first pressure to the second pressure when (a) the second pressure is less than or equal to the mean of the second pressure and (b) during the one or more time intervals when the slope of the plot is less than zero.

A system can include an aural computing system in communication with the ophthalmic device. In some embodiments, the aural computing system can include a wireless communication device in communication with the ophthalmic device. In some embodiments, the ophthalmic device comprises a contact lens, which can inserted into the user's eye. The wireless communication device can comprise wearable technology.

A system can include an aural computing system in communication with the ophthalmic device. In some embodiments, the aural computing system can include a wireless communication device in communication with the ophthalmic device. In some embodiments, the ophthalmic device comprises a contact lens, which can inserted into the user's eye. The wireless communication device can comprise wearable technology.

An exemplary method is disclosed that can be used in the diagnosis of hypertrophic cardiomyopathy (HCM) using a biophysical-sensor system configured to non-invasively and concurrently acquire electrocardiographic signals, seismographic signals, photoplethysmographic, and/or phonocardiographic signals, collectively referred to herein as biophysical signals, from at least the thoracic region of a subject. The acquired biophysical signals may be assessed for one or more conditions or indicators of hypertrophic cardiomyopathy and concurrently with other cardiac diseases, conditions, or indicators of either.