A method includes: obtaining, at a server, a diagnosis key published by a tracing service, the diagnosis key associated with a source device; identifying one or more detected proximity identifiers associated with the diagnosis key; identifying one or more affected network detection devices associated with the one or more detected proximity identifiers; retrieving, from a repository, device data for the one or more affected network devices, the device data identifying a facility of the one or more affected network devices; and generating facility exposure data for the facility, the facility exposure data defining exposure associated with the source device at the facility.

A computer program product, apparatus, and method may include various operations. The operations may include calibrating a sensor device to identify a heading, wherein the sensor device includes an inertial measurement unit, receiving three-dimensional motion data from the sensor device secured to a body part of a person as the person performs an activity involving movement of the body part, and causing generation of output based on the three-dimensional motion data, wherein the output is based on the movement of the sensor device.

Disclosed are various embodiments of golf training device that helps a golfer learn and coordinate lower body positions and movements with upper body movements, using a series of feedback signals. In one embodiment, a system comprises a foot sensor that attaches to a Lead Foot of a user. The foot sensor is configured to detect a heel of the Lead Foot being raised. The system also comprises a leg sensor that attaches to a Trail Knee of the user, and the leg sensor detects a bend in a knee of a Trail Leg of the user after detecting the heel being raised. The foot sensor is configured to detect the heel being lowered at an instance after the detection of the bend in the knee of the Trail Leg and while the knee remains bent. The system further comprises a feedback device configured to activate feedback indicators.

The present invention relates to a method for estimating the relative orientation between a tibia (11a) and a femur (11b) of a lower limb (10) of a person (1), the method being characterised in that it comprises the steps of: (a) During at least one reference movement of said lower limb (10) from a reference position, acquiring by first inertial measuring means (20a) integral with the tibia (11a) and by second inertial measuring means (20b) integral with the femur (11b) reference accelerations and angular velocities; (b) Estimating a plurality of morphological parameters of said lower limb (10), as a function of said measured reference accelerations and angular velocities; (c) Determining a relative orientation in said initial position between said tibia (11a) and femur (11b), as a function of said estimated morphological parameters of said lower limb (10); (d) During a working movement of said lower limb (10) from an initial position, acquiring by the first inertial measuring means (20a) and the second inertial measuring means (20b) working angular velocities; (e) Estimating the relative orientation between said tibia (11a) and femur (11b) as a function of said measured working angular velocities, and of said relative orientation in said initial position.

Methods, systems and devices are provided for utilizing user movement data obtained from one or more wearable sensors during physical activity to compare individualized changes overtime, for example typical versus atypical movement patterns, with subgroup analyses for assessing changes between other users in order to develop an assessment of movement for, for example, tracking injury risk, performance, and/or rehabilitation. The movement information may comprise multi-sensor, high dimensional datasets. Techniques are provided for integrating human movement data from one or more wearable sensor with one or more additional data sources to define an individualized movement profile of a user's movements. The user or another individual may be notified when the user's movements deviate from this individualized movement profile.

Systems and methods are provided for planning placement of an acetabular implant for a patient based on pelvic tilt. The system includes one or more sensors to be placed on the patient to provide measurements of a pelvic tilt angle of the patient taken with the patient in various functional positions to produce patient-specific data based on pelvic tilt from which to plan an inclination angle and a version angle of the acetabular implant for the patient.

A haptic robotic training system includes a haptic robot arm, a position tracking system, a scanning surface, a monitor and a computer. The robotic arm includes a haptic feedback system and holds a custom syringe in place. The position tracking system includes a positon tracking probe shaped like an ultrasound probe and a motion tracker. The scanning surface is a soft pad made from a synthetic phantom tissue. A simulation software receives the positioning data for the syringe from the robotic arm, and for the virtual ultrasound probe from the position tracking system and generates a virtual environment which mimics an actual ultrasound image. The user receives a real time feedback in the form of a haptic feel through the robotic arm, a virtual ultrasound image on the screen, and a performance feedback on the simulation software.

The present disclosure relates to systems, computer programs, and methods employing oral cavity image capture for determining tooth displacement (e.g., for identifying patients with, or at risk for, periodontal disease). In certain embodiments, a medical imaging device or system (e.g., an intraoral scanner or other scanner) is employed to generate baseline and test scan images of at least one tooth, where the test scan is performed when the tooth in engaged with an opposing tooth in a chewing action, or is being pushed by an outside force, and the images are processed by a computer program to determine the amount of displacement of the tooth in at least one direction.

A cue processor uses one or more sensors to obtain motion data for a user performing a physical task in an environment. A cueing law is based on a model determined from the motion data, for example a movement and skill model where the collected motion data are parsed into one or more movement units used to accomplish a range of outcomes. The cue processor generates a movement phase estimation to predict a movement phase and associated movement feature, and applies the cueing law to generate a cue signal. The cue signal is communicated to the user as a visual, audio or haptic stimulus, selected to target the feature for the user to achieve or improve a desired outcome.

In order to easily and accurately determine a walk cycle, this walk cycle determination system is provided with: a reception unit for receiving sensor data including acceleration and angular velocity acquired by a sensor mounted to footwear; a detection unit which generates time-series data of the orientation angle of at least one foot using the acceleration and angular velocity included in the sensor data, and detects maximal values and minimal values from the time-series data of the orientation angle; and a determination unit for determining the walk cycle based on the sequence of the maximal values and the minimal values.