205 results about "Physical activity" patented technology

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

Systems and methods are provided for enabling quick interactions with a user's frequent contacts from a wrist-wearable device. The method includes displaying, at a wrist-wearable device, a user interface including a plurality of representations of contacts. The plurality of representations of contacts includes a first representation of a first contact that is associated with an image-sharing application, and a second representation of a second contact that is associated with a fitness application that allows a user of the wrist-wearable device to compare performance of a physical activity against at least the second contact. The method includes, responsive to an input selecting the first representation of the first contact, causing activation of an imaging device for capturing an image. The method includes responsive to another input, capturing an image using the imaging device and causing the image to be sent to the first contact via the image-sharing application.

Examples relate to a fatigue detection system to monitor and assess pilot fatigue levels during flight operations. An example system includes a wearable biometric sensor (WBS) integrated into a wristband that captures biometric data from the pilot. A processor analyzes the captured data to determine the pilot's fatigue level. When this level exceeds a predetermined threshold, the system provides an alert to the pilot through a haptic feedback mechanism in the wristband. Additionally, the system generates personalized fatigue mitigation advice, which is displayed on an electronic flight bag (EFB) application accessible to the pilot. The advice may include recommendations for taking a controlled rest, consuming caffeine, or engaging in physical activity. The system enhances flight safety by providing real-time alerts and actionable advice to combat pilot fatigue.

Mandibular repositioning devices have a maxillary piece with a right side backmost teeth mold and / or left side backmost teeth mold and a driver flange having an anterior side with a convex curvature protruding from one or both thereof. The devices have a mandibular piece with a protrusive flange extending cranially therefrom positioned to have a posterior side engaged with the anterior side of each driver flange and with a plateau of a preselected height between the base of the protrusive flange and the tooth covering. The posterior side of each protrusive flange has a concave-to-convex curvature from a base of the protrusive flange toward a most cranial point of the protrusive flange and a convex portion of the concave-to convex curvature engages the convex curvature of the driver flange in a rest position. The plateau prevents disconnect between each protrusive flange and a respective driver flange.

A computer-implemented method for treating a patient suffering from Type I Diabetes (T1D). The method can include quantifying physical activity (PA) of the patient; calculating an accumulated PA periodically based on the quantified PA, the accumulated PA indicating an aggregate of the PA; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with a previous activity component, wherein the previous activity component is based on the accumulated daily PA, an activity profile, and an activity factor of the patient. The method can include determining an additional glucose uptake within a time period, the additional glucose uptake being caused by a PA; translating the additional glucose uptake into a number of insulin units with a same BG lowering impact; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with the insulin units.

Systems and methods are provided for enabling quick interactions with a user's frequent contacts from a wrist-wearable device. The method includes displaying, at a wrist-wearable device, a user interface including a plurality of representations of contacts. The plurality of representations of contacts includes a first representation of a first contact that is associated with an image-sharing application, and a second representation of a second contact that is associated with a fitness application that allows a user of the wrist-wearable device to compare performance of a physical activity against at least the second contact. The method includes, responsive to an input selecting the first representation of the first contact, causing activation of an imaging device for capturing an image. The method includes responsive to another input, capturing an image using the imaging device and causing the image to be sent to the first contact via the image-sharing application.

The invention relates to a wearable fitness monitoring system that uses advanced sensor technology to track real-time muscle engagement, posture, and fatigue levels during physical activity. The system comprises a capacitive sensor system, incorporating elastic silver fiber cloth and medical-grade silicone, for precise muscle movement detection; a motion sensor for tracking movement along multiple axes; and an AI-powered processing unit to provide ergonomic feedback, prevent injuries, and optimize performance. It features dynamic self-calibrating sensors that adjust to user-specific movements using machine learning algorithms. The system offers personalized workout plans, adjusting in real-time based on biometric feedback, environmental conditions, and muscle fatigue. Additionally, it integrates Bluetooth Low Energy (BLE) for wireless communication, haptic feedback for posture correction, and AR / VR for immersive workout guidance. The system includes cloud-based data storage with encryption and supports blockchain for secure data management, offering a comprehensive, personalized fitness experience that improves workout efficiency and safety.

The disclosure relates generally to methods and systems for real time video driven human 3-dimensional (3-D) posture estimation during physical activities. Conventional techniques do not exploit temporal information, they do not give smooth transition of postures over time. Furthermore, the techniques that exploit the temporal information suffer from higher time requirements due to two state computations. The present disclosure solves the technical problems in the art with the methods and systems for real time video driven human 3-D posture estimation during physical activities. The present invention discloses a smart-phone camera based automatic posture monitoring system designed with an auto-encoder based architecture. The disclosed auto-encoder based cross-modal method uses monocular video (2-D image sequences) from a single low-end mobile device (for example, smart-phone camera) for estimating human 3-D posture in real time (˜5 fps) with high accuracy (less than 1 cm error per joint location).

Various systems and methods that enhance an exercise or other physical activity performed by a user are described. In some embodiments, a repetition counting systems can track, monitor, count, or determine a number of repetitions of movements performed by a user during an exercise activity or other activity. For example, the repetition counting system can utilize classification or matching techniques to determine that a certain number of repetitions of a given movement or exercise are performed by the user.

A method and system for motion tracking that integrates pose estimation and segmentation. The method includes accessing a first set of keypoints generated by processing at least one image of a body area of a person. The first set of keypoints can be generated via pose estimation. The method further includes processing the at least one image to generate a body mask subsequently filtered to identify a second set of body contour keypoints, executing a predetermined function to identify a new keypoint based on the first set of keypoint and the second set of keypoints, generating a third set of keypoints based on the first set of keypoints and the new keypoint, and tracking the third set of keypoints to generate motion tracking data. The method generates feedback for the person based on the motion tracking data. The new keypoint and / or feedback can be generated based on a physical activity.

An assessment of basal cardiac fitness uses noninvasively obtained physiological measures to determine the presence of a basal physiological state and cardiometric measures to determine cardiac fitness. In the presence of preload independence and cardiac vagal control, cardiometric signals are acquired that are sensitive to cardiac function and include information indicative of the opening and closing of the individual's aortic valve. The cardiometric signals are analyzed by a cardiac fitness assessment system for the determination of basal cardiac fitness. The invention assures preload independence through the assessment of observational physiological parameters or the use of physiological parameters obtained following alterations in venous return. The invention assures the presence of cardiac vagal control by assessment of measured parameters, including the presence of respiratory sinus arrhythmia. The resulting test is specific for cardiac function without dependencies on physical activities associated with heart rate elevation or respiratory capabilities.

Systems, methods, and media for a configurable training system are provided. The configurable training system can include a controller and one or more configurable training devices. The configurable training device can include a housing, a cover coupled to a front surface of the housing, a sensor located within the housing to detect an impact, an indicator located within the housing and configured to emit light, and communication circuitry coupled with the indicator and the sensor. The communication circuitry may be coupled with the controller. The configurable training system may be adapted to various athletic training equipment or other equipment for physical activity.

A wearable device for monitoring physical activity of a user, the wearable device being reversibly attachable to a chest strap and an arm strap. The wearable device comprises an ECG sensor arranged to collect ECG measurements of the user only when the wearable device is attached to the user's chest by the chest strap, and a PPG sensor arranged to collect PPG measurements of the user when the wearable device is attached to the user's arm or wrist by the arm strap. The wearable device also comprises control circuitry arranged to switch the wearable device between an ECG only mode and a PPG only mode. In the ECG only mode, the control circuitry is configured to control the ECG sensor to collect ECG measurements but prevent the PPG sensor from initiating PPG measurements. In the PPG only mode, the control circuitry is configured to control the PPG sensor to initiate PPG measurements but prevent the ECG sensor from collecting ECG measurements.

Systems and methods are provided for capturing image data using an imaging device of a head-wearable device and modifying the image data with captured sensor data. An example method includes receiving image data captured by an imaging device of a head-wearable device worn by a user during performance of a physical activity, and receiving, during performance of the physical activity, sensor data sensed from the user by one or more sensors. The sensor data includes, at least, biometric data. The method includes generating modified image data based on the sensor data and the image data. The modified image data includes the image data and an overlay including, at least, the biometric data. The method also includes providing the modified image data to an electronic device, and causing presentation of the modified image data at a user interface displayed at the electronic device.

Provided is a method for treating musculoskeletal atrophy in patients suffering from a neurological or neuromuscular disease or disorder by combining testosterone replacement therapy with neuromuscular electrical stimulation of multiple muscle groups and, optionally, physical activity.

The present disclosure provides a system for providing directional assistance and training in a physical activity. The system comprises a wearable device (101) including vibrating devices (202), and a processor (102) for controlling the vibrating devices (202), a monitoring system (103) for monitoring an activity containing the users, a cloud server (105) configured to: receive data of monitoring of the activity, from the monitoring system (103), store pre-defined patterns of movements of the body and pre-defined parameters of vibrations for the patterns, identify real-time patterns of movements of the user based on the data received from the monitoring system (103), determine upcoming pattern of movements based on the real-time patterns and the pre-defined patterns, and transmit a command to the processor (102) of the wearable device (101) for controlling the vibrating devices based on the pre-defined parameters of the determined pattern, thereby directing the user in performing the physical activity.

A device may receive physical activity data for a subject, wherein the physical activity data comprises raw acceleration data. A device may derive a plurality of metrics from the raw acceleration data, wherein the plurality of metrics comprise a plurality of pattern-related metrics. A device may input the plurality of metrics into a deployed machine learning model. A device may be configured to perform receiving, from the deployed machine learning model, a physical activity score. A device may calculate a risk score for at least one disease or condition based on the physical activity score.

The present disclosure provides system and method for monitoring of at least one physiological parameter of a person engaged in a physical activity, for example, an impact received by a player engaged in a contact sport such as football. The system includes a monitoring unit that actively monitors the physiological parameter of the person, wherein the monitoring unit generates an alert event when the monitored physiological parameter exceeds a threshold of the parameter. The monitoring unit determines whether the parameter exceeds an over-exposure threshold, wherein said threshold is based upon both a single incidence or cumulative incidences.

The present disclosure relates to compositions, nutraceutical compositions, and dietary supplements that improve gut health, enhance energy, improve focus and energy, reduce cravings, improve stress management, improve overall health, promote healthy aging, replenish nutrients, support immune health, promote healthy skin, promote hair and nail growth, and enhance recovery after physical activity. The compositions comprise one or more of each of seaweeds, enzymes, and protein; two or more of each of adaptogens, botanicals, extracts, fibers, microalgae, micronutrients, minerals, vitamins, and whole fruit or vegetable powders; and three or more probiotics.

A method of implanting a hip joint prosthesis into a patient can include obtaining image data of hip joint anatomy of the patient. Physical activities that the patient desires to participate in subsequent to implanting the hip prosthesis can be determined. A size and an initial placement of the hip joint prosthesis based on the image data can be determined. A desired range of motion of the hip joint prosthesis based on the determined physical activities can be determined. A plan can be created comprising a desired implanted location of the hip joint prosthesis and based on the desired range of motion. The plan can be incorporated onto a guide. The plan can be executed with the guide thereby implanting the hip joint prosthesis into the patient at the desired implanted position.

In one example, a method includes receiving an indication of a body characteristic of a user collected by a sensor and an identifier of an actual choice by the user; deriving a level of health of the user from at least the body characteristic; correlating the identifier to an amount of a nutrient of a food item, or an amount of energy used by a physical activity; deriving an actual reward for actual choice, wherein the actual reward comprises an amount of money, credit or redeemable tokens; implementing the actual reward by providing the user or taking from the user the amount of money, credit or redeemable tokens; and transmitting to a portable device of the user, an indication of the actual reward to enable its presentation to the user.

Introduced here are computer-implemented platforms (also referred to as "muscle activation platforms") that are able to determine activated muscles of individuals performing physical activities. By predicting activated muscles, the muscle activation platforms are able to more accurately determine whether the individuals are performing the physical activities correctly.

A personal health system, method and device that maintains a health knowledge base, inputs user characteristics, generates health scores based on the user characteristics and provides recommendations based on the user characteristics, health scores and knowledge base, wherein the recommendations are indicated by the knowledge base to be likely to improve the user's health.

A computer-implemented method for generating synthetic inertial measurement unit (IMU) data comprises: accessing a video dataset containing a multitude of video frames depicting at least one human performing a physical activity; using a pose estimation model, extracting three-dimensional (3D) body mesh data from the multitude of video frames, where the 3D body mesh data represents a human posture in each of the multiple video frames; generating an animation of the 3D body mesh data, where the animation comprises a sequence of 3D body meshes representing the human movement; defining a multitude of virtual sensor positions on the 3D body mesh; and generating synthetic inertial data for each virtual sensor.

An insulin delivery system for diabetes management includes a patch-based insulin pump configured to deliver insulin to a user, a user input button disposed on the patch-based insulin pump, a processor configured to execute a hybrid closed loop algorithm that automatically controls insulin delivery based on glucose levels. The user input button is configured to receive user input comprising a sequence of button presses that communicate contextual information about user activities to the hybrid closed loop algorithm, the contextual information being distinct from direct insulin bolus delivery commands. The contextual information may include meal intake, physical activity, and sleep status communicated through different sequences of button presses. The system includes confirmation mechanisms that provide feedback and allow cancellation of inputs, enabling discrete real-time communication of personalized data to enhance diabetes management.

Example embodiments relate to a computer-implemented method for determining endurance performance of a subject based on sensor measurements; the computer-implemented method comprising: obtaining (201) workload data measured by at least one workload sensor, comprising a time series (212) of the workload exerted by the subject during one or more physical activities; obtaining (202) heart rate data measured by at least one heart rate sensor, comprising a time series (211) of the heart rate of the subject during the one or more physical activities; selecting (203) time intervals (213 - 219) within the workload data and the heart rate data based on a set of selection criteria (204); for the respective time intervals (213 - 219), determining (205) an average workload (207) and, for a final portion of the respective time intervals (213 - 219), determining (205) an average heart rate (206); and determining (208) at least a portion of a workload-heart rate relationship (221), indicative for the endurance performance of the subject, by fitting a linear equation (224) to the average workloads and the average heart rates (230) of the respective time intervals (213 - 219).

The invention relates to the technical field of smart home and Internet of Things, in particular to a solitary elderly guard monitoring method and system based on an air source heat pump water heater, a storage medium and a computer program product. According to the method, multi-source data such as water flow switching pulse, compressor current and water tank temperature difference are collected, feature vectors are constructed, a lightweight neural network is executed at the edge end to infer the physical activity state of the elderly, a personalized water use base line is updated in combination with a cloud recurrent neural network, and accurate recognition and graded warning of behavior abnormity are achieved. The system has the functions of national standard alarm, remote communication, self-calibration and energy-saving control, has the advantages of accurate effect, timely response, energy conservation, high efficiency, low deployment cost and the like, and is suitable for smart old-age care and home security scenes.

Systems and method of providing personalized physical activity notifications are disclosed. An example method is performed by a system including one or more processors communicatively coupled with a head-wearable device and one or more sensors. The method includes, while a user wearing the head-wearable device is performing a physical activity, obtaining sensor data sensed from the user via the one or more sensors. The sensor data includes at least biometric data and physical activity data. The method includes, in response to a user input querying the physical activity, initiating an artificial intelligence (AI) agent, and generating, by the AI agent, an AI message responsive to the user input. The AI message is based on one or more of the sensor data and the physical activity data. The method also includes causing presentation of the AI message via the head-wearable device.

The invention develops a sarcopenia prediction system for an adult group. The sarcopenia prediction method comprises the following steps: determining a crowd range and a standard included in the prediction system; determining a sarcopenia diagnosis standard and collecting outcomes in the target population; selecting a tree-based machine learning model according to the data features; screening the features by using a Boruta algorithm to construct a first set of screening model with high recall rate; screening features by using a pre-SHAP analysis method to construct a second set of auxiliary models for balancing the recall rate and the accuracy rate; optimal models of the system are determined by comparing model performance parameters, and finally prediction is achieved by combining the models. Features used by the system only depend on basic demographic features and physical activity questionnaires without clinical indexes, meanwhile, high performance is achieved in a model parallel connection mode, and the system is suitable for early screening detection of sarcopenia.