Abstract: A system for monitoring one or more physiological parameters includes a plurality of patches positionable at a plurality of locations on a surface of a body, wherein the plurality of patches are electrically isolated from each other, wherein a first patch of the plurality of patches includes a transmitter configured to inject an electrical signal into the body at a first location on the surface of the body, and wherein a second patch of the plurality of patches includes a sensor configured to detect a bio-impedance signal at a second location on the surface of the body that is spaced from the first location, and wherein the bio-impedance signal is induced within the body by the electrical signal injected from the first patch which is electrically isolated from the second patch.

Abstract: A movement recognition system includes a feature extraction circuit and a classification circuit that is orientation independent. The feature extraction circuit is configured to receive a plurality of acceleration or angular velocity measurements from a sensor or multiple sensors that include a three dimensional (3D) accelerometer and 3D gyroscope. Each of the measurements is taken at different times. The feature extraction circuit is also configured to determine a difference between a first of the measurements and each other of the measurements. The classification circuit is configured to classify a movement of an object attached to the sensor irrespective of an orientation of the sensor on the object utilizing a signal recognition technique based on the difference between the first of the measurements and each other of the measurements.

Abstract: A method of non-invasive, continuous, real-time measurement of blood pressure includes applying a wearable blood-pressure monitoring device to a bodily region of a wearer. The wearable blood-pressure monitoring device includes a plurality of pulse sensors or a sensor offering a plurality of observations. The wearable blood-pressure monitoring device is calibrated such that a subset of the plurality of pulse sensors or observations are selected. The selected subset of the plurality of pulse sensors measure a pulse wave velocity and other important physiological parameters of the wearer. The measured pulse wave velocity and other important physiological parameters are converted to a blood pressure of the wearer.

Abstract: A movement recognition system includes an inertial sensor, a depth sensor, and a processor. The inertial sensor is coupled to an object and configured to measure a first unit of inertia of the object. The depth sensor is configured to measure a three dimensional shape of the object using projected light patterns and a camera. The processor is configured to receive a signal representative of the measured first unit of inertia from the inertial sensor and a signal representative of the measured shape from the depth sensor and to determine a type of movement of the object based on the measured first unit of inertia and the measured shape utilizing a classification model.

Abstract: A method including obtaining a first motion signal segment sensed by a motion sensor worn on a user's wrist or forearm; detecting the user performed a first action based on the first motion signal segment; obtaining a second motion signal segment sensed by the motion sensor, wherein the second motion signal segment was sensed by the motion sensor after the first motion signal segment; detecting the user performed a second action based on the second motion signal segment and in response to the detection of the first action; determining that a first medication was taken by the user based on the detection of the second action; and, in response to the determination that the first medication was taken by the user, causing presentation of an indication to the user or transmitting an indication to an external device that the first medication was taken by the user.

Abstract: A movement recognition system includes a feature extraction circuit and a classification circuit that is orientation independent. The feature extraction circuit is configured to receive a plurality of acceleration or angular velocity measurements from a sensor or multiple sensors that include a three dimensional (3D) accelerometer and 3D gyroscope. Each of the measurements is taken at different times. The feature extraction circuit is also configured to determine a difference between a first of the measurements and each other of the measurements. The classification circuit is configured to classify a movement of an object attached to the sensor irrespective of an orientation of the sensor on the object utilizing a signal recognition technique based on the difference between the first of the measurements and each other of the measurements.

Abstract: A method including obtaining a first motion signal segment sensed by a motion sensor worn on a user's wrist or forearm; detecting the user performed a first action based on the first motion signal segment; obtaining a second motion signal segment sensed by the motion sensor, wherein the second motion signal segment was sensed by the motion sensor after the first motion signal segment; detecting the user performed a second action based on the second motion signal segment and in response to the detection of the first action; determining that a first medication was taken by the user based on the detection of the second action; and, in response to the determination that the first medication was taken by the user, causing presentation of an indication to the user or transmitting an indication to an external device that the first medication was taken by the user.

Abstract: Methods for classifying aggregated data in a distributed sensor system are provided and illustrated with a wearable motion sensor network. The classification is operated in a distributed fashion on individual sensor nodes and a base station computer. The method classifies actions using a set of training motion sequences as prior examples and may reject outlying actions that are not in the training categories. Acquired sensor data is processed at the node by taking projections of the data to reduce dimensionality, calculating sparse representations of features using training sequences; validating and classifying local measurements and then transmitting classified measurements to a network base station.

Abstract: The present invention relates to methods and apparatus for quantitative assessment of neuromotor disorders using sensors and analyzing the data collected from the sensors to determine if a patient suffers any neuromotor disorders. In one embodiment, the present invention is a system for assessing neuromotor disorders in a body including a plurality of pressure sensors adapted for attachment to the body and measuring pressure, a med node connected to the plurality of pressure sensors for generating data corresponding to the plurality of pressure sensors, and an analysis unit connected to the med node for analyzing the data generated by the med node to determine the existence of a neuromotor disorder in the body.

Abstract: An approach for determining motions of a body using distributed sensors is disclosed. In one embodiment, an apparatus can include: a plurality of sensors coupled to a body, where each sensor is positioned at about a designated location on the body, and where each sensor is configured to acquire motion data related to movement of the designated location on the body and at which the sensor is positioned, and to reduce the motion data into compressed and transmittable motion data; and a base station configured to receive the compressed motion data via wireless communication from at least one of the plurality of sensors, the base station being further configured to remove outlier information from the received motion data, and to match the received motion data to a predetermined action, where the predetermined action indicates a movement of the body.

Abstract: The present invention relates to methods and apparatus for quantitative assessment of neuromotor disorders using sensors and analyzing the data collected from the sensors to determine if a patient suffers any neuromotor disorders. In one embodiment, the present invention is a system for assessing neuromotor disorders in a body including a plurality of pressure sensors adapted for attachment to the body and measuring pressure, a med node connected to the plurality of pressure sensors for generating data corresponding to the plurality of pressure sensors, and an analysis unit connected to the med node for analyzing the data generated by the med node to determine the existence of a nueromotor disorder in the body.