In various embodiments, a device may test the health of race participants in order to ensure the fairness of a bet on an order of finish.

A detection device that includes an extraction unit that extracts waveform data based on a gait of a walker using sensor data acquired from a sensor installed on a foot of the walker and a detection unit that detects a gait event from the waveform data extracted by the extraction unit.

A mobility augmentation system assists a user's movement by determining a corresponding electrical stimulation for the movement. A wearable stimulation array includes sensors, electrodes, an electrode multiplexer, and a controller that executes the mobility augmentation system. The sensors measure movement data, and the mobility augmentation system applies a movement model to the measured movement data. The model can determine different electrical actuation instructions depending on the movement stimulated. For example, to stimulate a knee flexion, the movement model output enables a first set of the electrodes to operate as cathodes and a second set of electrodes to operate as anodes. To stimulate a knee extension, the first set of electrodes can be enabled to operate as anodes and a third set of electrodes as cathodes. The user can provide feedback of the applied stimulation, which the system can use to retrain the model and optimize the stimulation to the user.

Systems and methods for electronically creating and modifying a fitness plan are disclosed. The method may include receiving electronic user data, collecting electronic fitness data, and displaying a suggestion for a fitness activity based on the electronic user data and the electronic fitness data.

A structured 3D model of a real-world object is generated from a series of 2D photographs of the object, using photogrammetry, a keypoint detection deep learning network (DLN), and retopology. In addition, object parameters of the object are received. A pressure map of the object is then generated by a pressure estimation DLN based on the structured 3D model and the object parameters. The pressure estimation DLN was trained on structured 3D models, object parameters, and pressure maps of a plurality of objects belonging to a given object category. The pressure map of the real-world object can be used in downstream processes, such as custom manufacturing.

Systems, methods and computer readable media comprising a virtual exercise board, which is represented by images on the screen of a pad device; wearable devices configured to attach to each shoe of a user and to collect and transmit touch data to the pad device; cameras for tracking movement and calibrating with the data collected by the wearable devices; and computer programs for collecting user data, processing user data, and generating outputs. In embodiments, features include augmented reality; ratings of performance; automated workouts/protocols; real-time progress bar; multi-location database capabilities; and reports.

Sensing devices including sensors such as flexible and stretchable fabric-based pressure sensors, may be associated with or incorporated in garments, such as socks, intended to be worn against a body surface (directly or indirectly). Specific manifestations of a sensing system incorporated in a sock substrate are described in detail. Dedicated electronic devices interface electrically with sensors through intermediate conductive traces, optional conductive bridges, conductive contacts provided in a mounting tab.

A directional force sensor and sensing system are described. The directional force sensor includes a leaf spring and one or more load sensors disposed about the leaf spring such that in response to a force applied to the leaf spring, the one or more load sensors provide a signal. A controller is coupled to receive signals from the one or more directional force sensors and determines characteristics of forces applied to the directional force sensors.

A shoe has a sensor system operably connected to a communication port. Performance data is collected by the system and can be transferred for further use via the communication port. The shoe may contain an electronic module configured to gather data from the sensors. The module may also transmit the data to an external device for further processing. Users can use the collected data for a variety of different uses or applications.

A quantitative gait training and/or analysis system includes one or more footwear modules that may include a piezoresistive sensor, an inertial sensor and an independent logic unit. The footwear module functions to permit the extraction of gait kinematics and evaluation thereof in real time, or data may be stored for later reduction and analysis. Embodiments relating to calibration-based estimation of kinematic gait parameters are described.