A fitness tracking system includes a shoe, a monitoring device, and a controller. The monitoring device is mounted on the shoe and includes an accelerometer configured to generate acceleration data corresponding to acceleration of a foot received by the shoe. The controller is operably connected to the accelerometer and is configured to collect sampled acceleration data by sampling the generated acceleration data, to identify foot strike data of the sampled acceleration data, to identify a local minimum of the sampled acceleration data collected prior to the foot strike data, and to determine foot strike characteristic data corresponding to the foot strike data based on an acceleration value at the local minimum.

A smartphone or other mobile computer device, general purpose or specialized, wherein the smartphone device is configured to actively control the configuration of one or more bladders, compartments, chambers or internal sipes and one or more sensors located in either one or both of a sole or a removable inner sole insert of the footwear of the user and/or located in an apparatus worn or carried by the user, glued unto the user, or implanted in the user. The one or more bladders, compartments, chambers, or sipes, and one or more sensors are configured for computer control. A sole and/or a removable inner sole insert for footwear, including one or more bladders, compartments, chambers, internal sipes and sensors in the sole and/or in a removable insert; or on an insole; all being configured for control by a smartphone or other mobile computer device, general purpose or specialized.

Systems and methods for detecting udder disease based on machine learning methods and complementary supporting techniques are presented. Included are methods for assembling time sequences of images of each animal of a herd or set for subsequent use in per-animal image analysis for disease detection. Methods presented also include image pre-processing methods used prior to image analysis, resulting in contrast and resolution optimization such as appropriate image intensity level adjustment and resolution downsampling for more rapid and more accurate disease detection. Combinatorial techniques for compositing whole-udder images or udder-quarter images from partial images captures are described. Methods are provided for power usage optimization in regard to computing resources used in the computing-intensive AI analysis methods. Location-based and animal history-based detection refinements are incorporated into described systems. Further presented are methods for multi-modal and multi-factor detection of udder disease, as well as methods for infection type classification.

The present subject matter discloses a system(s) and a method(s) for determining a health state of an individual. According to an embodiment, a method comprises measuring, by a heart rate sensor, a heart rate of the individual during operation within the environment. The method further comprises outputting, by a pressure sensing platform, pressure data of the individual. Further, the method comprises outputting, by an image capturing device, image data of the individual. The method further comprises inferring, by a processing unit, an amount of fat of the individual in the image data. The method further comprises updating, by the processing unit, the amount of fat of the individual using the pressure data. The method further comprises controlling, by the processing unit, a threshold for determining the health state of the individual, using the amount of fat and the heart rate of the individual.

The present disclosure generally relates to user interfaces and more specifically to techniques for displaying user interfaces associated with physical activities. Exemplary user interfaces related to activity competitions are described. Exemplary user interfaces related to a friends list for activity sharing are described. Exemplary user interfaces associated with alerts presented to a user in response to automatically determining a boundary of a workout are described. Exemplary user interfaces associated with configuring a pace alert for a workout application are described.

An implantable monitoring device includes first sensors to measure state information of one or both of a posture and an activity of a user and second sensors to measure bioinformation of two or more of an electrocardiogram (ECG) of a heart of the user, a pulmonary impedance of a lung of the user, a movement of the heart, a movement of a thorax including the lung, and a respiratory quotient (RQ) of the lung, two electrodes to detect bioinformation to measure one or both of the ECG and the pulmonary impedance, an analog circuit to process the detected bioinformation to measure the one or both of the ECG and the pulmonary impedance, and a processor to monitor an abnormal state of the heart and the lung of the user based on the state information and the bioinformation.

A smartphone or other mobile computer device, general purpose or specialized, wherein the smartphone device is configured to actively control the configuration of one or more bladders, compartments, chambers or internal sipes and one or more sensors located in either one or both of a sole or a removable inner sole insert of the footwear of the user and/or located in an apparatus worn or carried by the user, glued unto the user, or implanted in the user. The one or more bladders, compartments, chambers, or sipes, and one or more sensors are configured for computer control. A sole and/or a removable inner sole insert for footwear, including one or more bladders, compartments, chambers, internal sipes and sensors in the sole and/or in a removable insert; or on an insole; all being configured for control by a smartphone or other mobile computer device, general purpose or specialized.

Disclosed are methods and medical device systems for automated delivery of therapies for pain and determination of need for and safety of treatment. In one embodiment, such a medical device system may comprise a sensor configured to sense at least one body signal from a patient; and a medical device configured to receive a first sensed body signal from the sensor; determine a patient pain index based at least in part on said first sensed body signal; determine whether said patient pain index is above at least a first pain index threshold; determine a safety index based at least in part on a second sensed body signal; select a pain treatment regimen based on at least one of said safety index and or a determination that said pain index is above said first pain index threshold; and deliver said pain treatment regimen.

A system and a method are described for monitoring a medical care environment. In one or more implementations, a method includes identifying a first subset of pixels within a field of view of a camera as representing a bed. The method also includes identifying a second subset of pixels within the field of view of the camera as representing an object (e.g., a subject, such as a patient, medical personnel; bed; chair; patient tray; medical equipment; etc.) proximal to the bed. The method also includes determining an orientation of the object within the bed.

An apparatus for monitoring a person, including while sleeping, the apparatus including: a. a garment for a person to wear while sleeping; b. a rigid sensor device configured to detect a temperature and/or a motion of the rigid sensor device while the person is wearing the garment; and c. an elastic pocket configured to hold the rigid sensor device tightly inside the garment during the detection of the temperature and/or the motion.