The present disclosure generally relates to user interfaces for health applications. In some embodiments, exemplary user interfaces for managing health and safety features on an electronic device are described. In some embodiments, exemplary user interfaces for managing the setup of a health feature on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described. In some embodiments, exemplary user interfaces for managing a biometric measurement taken using an electronic device are described. In some embodiments, exemplary user interfaces for providing results for captured health information on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described.

Physiological signal processing systems include a photoplethysmograph (PPG) sensor that is configured to generate a physiological waveform, and an inertial sensor that is configured to generate a motion signal. A physiological metric extractor is configured to extract a physiological metric from the physiological waveform that is generated by the PPG sensor. The physiological metric extractor includes an averager that has an impulse response that is responsive to the strength of the motion signal. Related methods are also described.

Disclosed is an image compression method of a digital pathology system. The image compression method is a method of compressing digital slide images having first to nth original plane images (n is a natural number greater than or equal to 2). The image compression method includes selecting a block having an optimal focal point as an optimal block from each set of blocks positioned at identical positions of the first to nth original plane images; forming one plane image as a virtual optimal plane image by combining only the optimal blocks; generating block descriptors for forming the first to nth original plane images based on the virtual optimal plane image; generating first to nth predictive plane images from the virtual optimal plane image such that the first to nth predictive plane images are the least out of focus by using location information for the blocks and the block descriptors; generating first to nth differential plane images, the first differential plane image corresponding to a difference between the first original plane image and the first predictive plane image and the nth differential plane image corresponding to a difference between the nth original plane image and the nth predictive plane image; and compressing the first to nth differential plane images.

A detection device for detecting and characterizing biological energy fields emitted by biological specimens is configured to collect and analyze an electromagnetic signal that includes millimeter-length waves generated by the interaction of atmospheric plasma with torsion waves of the biological energy field. The device performs spectral analysis on the millimeter waves to determine characteristics of the corresponding torsion waves that generated them. An array of several hundred non-thermal plasma plumes are placed directly in front of a circular horn. A switchable circular polarizer is used to select left hand circular, linear or right hand circular polarization. A low noise frequency converter allows a noise temperature of less than 1150 K. A frequency scan and averaging algorithm is developed to characterize noise temperature versus frequency, comparing signal and noise levels between plasma on and plasma off, and switching polarization sense.

Techniques are disclosed for using a cardiac signal sensed via a plurality of electrodes disposed on one or more leads implanted within an epidural space of a patient to control spinal cord stimulation (SCS) therapy. In one example, an implantable medical device (IMD) senses an electrical signal via a plurality of electrodes disposed on one or more leads implanted within an epidural space of a patient. Processing circuitry determines, from the electrical signal, one or more cardiac features indicative of activity of a heart of the patient. The processing circuitry controls, based on the one or more cardiac features, delivery of SCS therapy to the patient.

A method of determining a fused sensor measurement is disclosed including: obtaining sensor measurements from sensors detecting a same type of physiological measurement; determining a signal quality index (SQI) of each sensor including determining an extent to which a sensor measurement differs from others among the sensor measurements obtained from each sensor; determining a weightage of each sensor based on the SQI of each sensor; and determining a fused sensor measurement from the plurality of sensors based on the weightage of each sensor and filtered sensor measurements of each sensor obtained from a Kalman filter operation. A vehicle safety system includes: a vehicle electronic control unit configured to: determine the sensor measurement extent, to determine the SQI of each sensor, determine the weightage of each sensor, determine the fused sensor measurement, determine the occupant's physiological condition, and if the physiological condition is abnormal, perform at least one vehicle operation.

There is provided a device for measuring fatigue of a person, the device comprising a frame configured to be worn within the mouth of the person, a microphone mounted within the frame and configured to measure sound data, and a cavity located within the frame and adjacent to the microphone, wherein the cavity does not communicate with the environment surrounding the frame. There is also provided a computer-implemented method for determining a fatigue metric representing a level of physical fatigue of a person

A sensor on an earpiece is used to attempt to detect a signal corresponding to a heartbeat. If a heartbeat is detected, it can be determined that the earpiece is being worn by a user. The sensor may be an acoustic transducer on a surface of the earpiece that is located within the wearer's ear canal, while the earpiece is being worn normally.

A motion monitoring method (500) is provided, which includes: obtaining a movement signal of a user during motion, wherein the movement signal includes at least an electromyographic signal or an attitude signal (510); and monitoring a movement of the user during motion based at least on feature information corresponding to the electromyographic signal or the feature information corresponding to the attitude signal (520).

According to an aspect, there is provided a computer-implemented method for determining a heart rate of a subject, the method comprising: receiving data representing a signal generated by a pressure sensor configured to be placed on a suprasternal notch of a subject, the data representing a first component of the signal comprising respiratory information associated with the subject and/or a second component of the signal comprising cardiac information associated with the subject; determining, by applying a first algorithm to the data, a respiration parameter of the subject; applying at least one filter to the data to obtain first filtered data, the at least one filter comprising a first filter to attenuate the first component of the signal in the data based on the determined respiration parameter; and determining a heart rate of the subject by applying a second algorithm to the first filtered data.