A fitness fatigue score for a user for a current day is provided. The fitness fatigue score can be determined based, at least in part, on first data obtained over a first period of time, second data obtained over a second period of time that is shorter in duration than the first period of time, and third data obtained over a third period of time that is longer in duration than the first period of time. The first data includes heart rate measurements for the user over the first period of time. The second data includes one or more sleep metrics for a plurality of sleep events for the user over the second period of time. The third data includes heart rate variability for the user over the third period of time. Additionally, a recommendation regarding exercise for the current day can be generated based on the fitness fatigue score.

Various aspects of the subject technology are designed to analyze a range of inputs (e.g., sound, light, color, words, media, etc.), determine the sub-conscious impact of those inputs on individuals, then recommend and/or augment content capable of improving their current mental health state. Embodiments of the subject technology receive inputs (e.g., data) from information sources or platforms (e.g., smart phones, applications, wearable devices, databases, entered values). Embodiments of the subject technology analyze the received data according to one or more programmed matrices. Embodiments of the subject technology score the subconscious impact. Embodiments of the subject technology compare user data with the content data to make one or more predictions. Embodiments of the subject technology output, display, or provide several solutions for a user to choose from.

The present disclosure provides a posture detection device and a necklace, which relates to a field of automatic control, the posture detection device is worn on a body of a user, and the posture detection device includes a sensing device, a processor, and a reminding device. The sensing device is connected to the processor, and the sensing device obtains information of back posture changes of the body of the user and sends the information to the processor. The processor is connected to the reminding device, the processor processes the information, generates a reminding signal, and sends the reminding signal to the reminding device, the reminding device starts a vibration mode according to the reminding signal.

Devices, systems, and methods can be used to suggest a discovery to an individual related to their health and wellness, including receiving data about the individual from a user interface regarding a goal for the individual, querying the individual regarding their perception of the goal, determining, a likely state of the individual (e.g., readiness to change), and selecting a subset of discoveries to display to the individual from a database that correspond to both the goal for the individual and the likely state of the individual. Displaying information may include receiving motion data including duration of motion, classifying a type of activity the individual is engaged in based on the motion data and likely intensity of the activity, and displaying a graphical user interface including a color spectrum, depending on one of the type of activity, intensity of the activity, or duration of the activity.

A subject's Default Mode Network is accessed through corresponding measurements of the Micro-Coherence Oximetry Network Strength (MCO-S). An associated MCO-S system (100) includes a wearable (102), a user device (112) and a processing platform (123). The wearable (102) collects subject information sufficient to enable monitoring and optimization of the subject's Default Mode Network include sensors such as pulse oximetry instrumentation and EEG electrodes to obtain brainwave data, oxygen saturation data, heart rate variability data, and galvanic skin conductance data. Information from the sensors may be communicated to a user device (112), such as a cell phone or VR headset. The user device (112) communicates with a remote processing platform (123) that may execute artificial intelligence functionality and other logic in connection with assessing the patient's micro-coherence network strength and optimizing behavior modification protocols in relation to attributes and objectives of the subject.

A system, method, and computer readable media are provided for obtaining a first set of skin data from an image capture system including at least one ultraviolet (UV) image of a user's skin. Performing a correction on the skin data using a second set of skin data associated with the user. Quantifying a plurality of skin parameters of the user's skin based on the first skin data, including quantifying a bacterial load. Quantifying the bacterial load by applying a brightness filter to isolate portions of the at least one UV image containing fluorescence, applying a dust filter, identifying portions of the at least one UV image that contain fluorescence due to bacteria, and determining a quantity of bacterial load in the users skin. Determining, using a machine learning model, an output associated with a normal skin state of the user and a current skin state of the user.

A biological information displaying apparatus according to an embodiment includes a picture obtaining apparatus and a processor. The picture obtaining apparatus obtains a picture signal of a predetermined site of a subject as a moving image. The processor generates a hue moving image by extracting a luminance or an image-based photoplethysmogram (iPPG) related to a pulse wave for each pixel of the moving image and assigning a hue in accordance with a value of luminance information or iPPG information. The processor displays the generated hue moving image such that the hue moving image is superimposed on an image of the subject.

A method of manufacturing an insert system for footwear includes assembling electronic components. The electronic components include a sensor array having physiological sensors. Each physiological sensor includes a first high resistance layer configured to be in contact with a second high resistance layer when no force is applied to the sensor. The method further includes positioning the sensor array between a first layer and a base layer. An insert system for footwear includes a first layer, a base layer, a sensor array between the first and base layers, and a circuit board. The sensor array includes physiological sensors. Each physiological sensor includes a first high resistance layer in contact with a second high resistance layer when no force is applied to the sensor. The circuit board can transmit signals external to the system to trigger an alert being issued to a user, based on an output of the sensor array.

A skin state determination method includes: acquiring a first measurement result including data obtained by a spectral camera measuring the skin of a user at a first time point, second time points before the first time point being different from each other; estimating, on the basis of the first measurement result, a first estimation result including at least one of a skin moisture content or hidden blemish conditions of the user at the first time point; and determining a skin state of the user on the basis of the first estimation result and second estimation results based on second measurement results, each of the second measurement results including data obtained by the spectral camera measuring the skin of the user at each of the second time points.

Adjustment of training protocols in virtual reality (VR) or augmented reality (AR) environments based on biofeedback are provided. In various embodiments, motion data is collected for a user while the user performs a training protocol in a virtual environment. A biometric measurement is collected for the user while the user performs the training protocol. The motion data and the biometric measurement are provided to a learning system at a remote server. The learning system determines an adjustment to the training protocol based on the motion data and the biometric measurement. The adjustment is provided by the learning system and is applied to the training protocol. In various embodiments, the adjustment, the motion data, and/or the biometric measurement may be logged in an electronic health record.