The present disclosure generally relates to navigating, viewing, and sharing activity and workout data and interacting with workout and/or activity applications. In some examples, scrolling of activity data is based on the content being displayed. In some examples, friends' activity data may be viewed. In some examples, a notification and workout data for a friend's completed workout is received and displayed. In some example, the activity data received from friends is viewed and managed. In some examples, workout data for a multi-segment workout is displayed in a three-dimensional stack on a map. In some examples, a workout application operates in a limited mode until a touch input is received with a characteristic intensity that is greater than a threshold intensity.

Provided are techniques for enhancing images with emotion information, comprising capturing a plurality of images; identifying an individual in the plurality of images; analyzing the plurality of images for emotional content; converting the emotional content into emotion metadata; correlating the emotional content with the individual to produce associated emotion metadata; and storing the associated emotion metadata in conjunction with the captured image in a computer-readable storage medium. The disclosed techniques may also include capturing physiological data corresponding to an individual that captures the image; analyzing the physiological data for a second emotional content; converting the second emotional content into a second emotion metadata; storing the second emotion metadata in conjunction with the captured image in the computer-readable storage medium.

A software configuration generates, with a processor, a graphical user interface that renders a menu of a plurality of selection indicia. The plurality of selection indicia includes a skincare rejuvenation area indicium, a skincare assessment indicium, and a skincare interactive cue indicium. Furthermore, the software configuration receives, with the processor, a first user input corresponding to a skincare rejuvenation area associated with the skincare rejuvenation area indicium. Moreover, the software configuration receives, with the processor, a second user input corresponding to the skincare assessment indicium to initiate a skincare assessment based on the skincare rejuvenation area. Furthermore, the software configuration performs, with an image capture device, an image capture of the skincare rejuvenation area. Additionally, the software configuration performs, with the processor, an image analysis of the image capture with one or more previous image captures captured by the image capture device.

Systems and methods for acquiring photoplethysmographic (PPG) signals for measuring blood pressure can include a computing device acquiring a sequence of images representing transdermal optical data of a subject, and generating a corresponding sequence of downsampled color frames. The computing device can identify, in each downsampled color frame, a respective central image block representing a central image region of the downsampled color frame and having a first size smaller than a second size of the downsampled color frame. The computing device can generate, for each downsampled color frame, a corresponding color intensity value based on the respective central image block. The computing device can generate, using color intensity values corresponding to the sequence of downsampled color frames, a PPG signal to determine a blood pressure value of the subject.

Systems and methods for analyzing and representing human gait using motion sensor data may include collecting raw motion sensor data from a mobile device held on or near the user's sternum. The mobile device (or another device) may be configured to generate an information structure representation based on the raw motion sensor data, determine a gait cycle based on the information structure representation, identify gait events in the gait cycle, extract gait biomarkers based on the identified gait events, and determine a diagnosis based on the extracted biomarkers.

A big data artificial intelligence computer system is used for medical care connecting to sensor-equipped smartphones of users of footwear. The footwear has smartphone-connected soles with sensors and configurable structures. The smartphone is also connected to sensors located on the users' body, including proximate to its center of gravity and/or on the head. The web and/or cloud-based computer system is configured to use the big data techniques of machine learning in a database compiled from millions of smartphones to perform operations on billions of data sets from the smartphones of the footwear users. The correlations found from the big data operations provide solutions to medical problems of the footwear users involving their body structure and/or function. The solutions are implemented by configuring the users' footwear soles, including active configuration, including during running and/or walking to optimize corrections to the structure and/or function of their bodies.

Estimates related to heart rate or blood oxygen levels from wearable PPG devices can be exchanged between the devices. Estimated heart rates can be combined at either of the PPG devices or another device using a weighted average to derive a more accurate heart rate or blood oxygen level. A single PPG device is susceptible to motion artifacts and other sources of noise creating inaccurate readings. A time variable weighted average of the two heart rate estimates from two wearable PPG devices provides a real-time heart rate which is more accurate and less susceptible to error. Further, derivative metrics, which analyze the underlying heart rate estimate signals or blood oxygen levels, can also be combined based on rules to create a more accurate derivative metric. Notifications related to the heart rate estimate and derivative metrics can be provided to a user on a user device.

A system, a method, and a computer program product may be provided for providing a remedial procedure. The system comprises a wearable device having sensors to measure health parameters of a user, and processors connected to the wearable device. The processors may receive the health parameters from the sensors, determine a physical wellness value for the user based on the health parameters and predefined physical wellness thresholds, and determine a mental wellness value for the user based on the health parameters and predefined mental wellness thresholds. The processors may identify a risk factor associated with a health of the user based on the physical wellness value and the mental wellness value. The processors may provide a remedial procedure in real-time designed to at least mitigate the identified risk factor.

The present disclosure relates to integrated systems, methods and apparatuses for assisting individuals in managing acute life-threatening conditions. A system in accordance with the current disclosure may comprise an electronic circuit configured to be attached to a container of a medication and one or more devices in communication with the electronic circuit in a private network. In an aspect, the one or more devices may work in concert to determine the safety level of an individual based on predetermined usage settings. In some aspects, the system may be configured to determine whether a medication would expire before its manufactured expiry date. In another aspect, the system may assist an individual in locating a medication. In a further aspect, the system may determine whether an individual is having an anaphylactic reaction. In some aspects, the system may detect a known allergen and alert the individual.

An apparatus for measuring bio-information may include: a pulse wave sensor comprising at least one pair of light emitters which are disposed apart from each other and a light receiver disposed between the at least one pair of light emitters, and configured to measure a plurality of pulse wave signals from an object by using the light receiver and the at least one pair of light emitters; a force sensor configured to measure a contact force that is applied to the pulse wave sensor by the object; and a processor configured to generate an integrated pulse wave signal by integrating the plurality of pulse wave signals based on the contact force and an area of a contact surface of the pulse wave sensor, and estimate bio-information of the object based on the integrated pulse wave signal.