An electronic device for gesture recognition, includes a processor operably connected to a transceiver. The transceiver is configured to transmit and receive signals for measuring range and speed. The processor is configured to transmit the signals, via the transceiver. in response to a determination that a triggering event occurred, the processor is configured to track movement of an object relative to the electronic device within a region of interest based on reflections of the signals received by the transceiver to identify range measurements and speed measurements associated with the object. The processor is also configured to identify features from the reflected signals, based on at least one of the range measurements and the speed measurements. The processor is further configured to identify a gesture based in part on the features from the reflected signals. Additionally, the processor is configured to perform an action indicated by the gesture.

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.

Introduced here are health management platforms able to monitor changes in the health state of a subject based on the context of digital activities performed by, or involving, the subject. Initially, a health management platform can identify a physiological response by examining physiological data associated with a subject. Then, the health management platform can identify a stimulus presented by an electronic device that provoked the physiological response by examining contextual data associated with the subject. The contextual data may be in the form of a screenshot of a computer program in use by the subject during the physiological response. In some embodiments, the health management platform prompts the subject to specify whether the physiological response is a positive physiological response that resulted in an upward shift in health or a negative physiological response that resulted in a downward shift in health.

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.

Electronic devices and methods are disclosed. First and second electronic devices include processors, which implement one or more methods, including receiving sensor data, determining an exercise starting timepoint based on first sensor data, estimating an exercise posture of a user based on second sensor data, estimating a pattern of change in distance between each of the plurality of external electronic devices, indicated by changes in the relative position between each the plurality of external electronic devices over a time period of the determined exercise starting timepoint, based on third sensor data, and generating exercise information based on the estimated exercise posture and the estimated pattern of change in distance between the plurality of external electronic devices.

The present invention relates to a movement disorder monitor with high sensitivity, and a method of measuring the severity of a subject's movement disorder. The present invention additionally relates to a drug delivery system for dosing a subject in response to the increased severity of a subject's symptoms. The present invention provides for a system and method, which can accurately and repeatably quantify symptoms of movements disorders, accurately quantifies symptoms utilizing both kinetic information and/or electromyography (EMG) data, that can be worn continuously to provide continuous information to be analyzed as needed by the clinician, that can provide analysis in real-time, that allows for home monitoring of symptoms in subject's with these movement disorders to capture the complex fluctuation patterns of the disease over the course of days, weeks or months, that maximizes subject safety, and that provides substantially real-time remote access to data by the clinician or physician.

The present specification discloses systems and methods of patient monitoring in which multiple sensors are used to detect physiological parameters and the data from those sensors are correlated to determine if an alarm should, or should not, be issued, thereby resulting in more precise alarms and fewer false alarms. Electrocardiogram readings can be combined with invasive blood pressure, non-invasive blood pressure, and/or pulse oximetry measurements to provide a more accurate picture of pulse activity and patient respiration. In addition, the monitoring system can also use an accelerometer or heart valve auscultation to further improve accuracy.

Disclosed is an electronic device comprising a processor and at least one sensor circuit comprising at least a biometric sensor and a fatigue sensor. The processor may be configured so as to detect biometric data of an external object by means of the biometric sensor, detect fatigue data of the external object by means of the fatigue sensor if the biometric data exceeds a designated second range, and output, by means of a designated external device, a fatigue notification indicating a fatigued state if the fatigue data exceeds a designated third range. Other various embodiments identified in the description are possible.

Systems and methods are disclosed to objectively identify sub-second behavioral modules in the three-dimensional (3D) video data that represents the motion of a subject. Defining behavioral modules based upon structure in the 3D video data itself—rather than using a priori definitions for what should constitute a measurable unit of action—identifies a previously-unexplored sub-second regularity that defines a timescale upon which behavior is organized, yields important information about the components and structure of behavior, offers insight into the nature of behavioral change in the subject, and enables objective discovery of subtle alterations in patterned action. The systems and methods of the invention can be applied to drug or gene therapy classification, drug or gene therapy screening, disease study including early detection of the onset of a disease, toxicology research, side-effect study, learning and memory process study, anxiety study, and analysis in consumer behavior.

A personal impact monitoring system is described herein comprising a monitoring station that receives impact events sent from personal impact monitors using a monitoring station receiver. The impact events which specify impact parameters associated with the impact events are stored in a data storage location associated with the monitoring station. Software operating on the operating station is configured to receive the impact events from the data storage location and to perform calculations based on the impact events to identify notable impact events.