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 walking training system includes a treadmill, a center-of-gravity position detection unit that detects a center-of-gravity position of a trainee from a load received from a sole of the trainee on a belt of the treadmill, a posture detection unit that detects a posture of the trainee, a center-of-gravity position estimation unit that estimates the center-of-gravity position of the trainee from the detected posture of the trainee, a determination unit that determines whether a difference between the detected center-of-gravity position and the estimated center-of-gravity position exceeds a predetermined value, and a notification unit that sends, when the determination unit determines that the difference exceeds the predetermined value, a notification notifying that whether the difference exceeds the predetermined value.

A walking state measurement system includes: an endless belt that defines a walking surface on which a subject walks and that travels along a walking front-rear direction; a marker provided on at least the walking surface along a circumferential direction of the belt; a first camera for taking an image of the subject from front, the first camera taking an image of the marker on the walking surface from above to generate a first image; a second camera for taking an image of the subject from front, the second camera taking an image of the marker on the walking surface from above to generate a second image; and a correction processing unit that corrects an image generated by at least either the first camera or the second camera based on a position of an image area of the marker included in each of the first image and the second image.

A soft, flexible microtube sensor and associated method of sensing force are described. A liquid metallic alloy is sealed within a microtube as thin as a strand of human hair to form the physical force sensing mechanism. The sensor is hardly distinguishable with the naked eye, and can be used for the continuous biomonitoring of physiological signals, such as unobtrusive pulse monitoring. Also described is a method of fabricating the microtube sensor and wearable devices incorporating one or more microtube sensors.

A method and system for activity classification. A pressure sensor receives input data resulting from physical activity of a subject performing an activity. The input data includes pressure data from at least one pressure sensor, and may include other data acquired through other types of sensors. A deep learning neural network is applied to the input data for identifying the activity. The neural network is trained with reference to training data from a training database. The training data may include empirical data from a database of previous data of corresponding activities, synthesized data prepared from the empirical data or simulated data. The training data may include data from physical activity of the subject being monitored by the system. Different aspects of the neural network may be trained with reference to the training data, and some aspects may be locked or opened depending on the application and the circumstances.

A fatigue relief method using smart footwear and an operation method for a user terminal are provided. The fatigue relief method using smart footwear comprises: receiving the provision of pressure data or acceleration data measured while a user wears smart footwear and performs an exercise, wherein the smart footwear has at least one pressure sensor or acceleration sensor and a tactile element, which are installed therein; estimating the fatigue of the user by using the provided pressured data or acceleration data; selecting one of a plurality of vibration solutions on the basis of the estimated fatigue; and allowing the tactile element of the smart footwear to vibrate according to the selected vibration solution.

A low power force detection system includes variable capacitors, a drive sense module, and a processing module. A drive sense circuit of the drive sense module is operable to provide an analog and frequency domain signal to a variable capacitor. The drive sense circuit is further operable to detect a characteristic of the variable capacitor based on the analog and frequency domain signal and to generate a representative signal of the characteristic. The processing module is operable to generate a digital value based on the representative and to write the digital value to memory.

Systems, devices, and methods are disclosed for the purpose of quantitatively determining the susceptibility of a human subject to injure their Anterior Cruciate Ligament (ACL). A method for determining injury susceptibility scores or risk categories includes determining hip extension angles and knee varus angles during the performance of a stork test and determining hip abduction angles during a squat test. Determination of angles during certain movements may be achieved using various systems and devices, including wearable devices.

This disclosure relates generally to a Parkinson's disease detection system. Parkinson's disease is a neuro-degenerative disorder affecting motor and cognitive functions of subjects. Since symptom manifestation is limited in Parkinson's disease, identifying Parkinson's disease in the early stage is a challenging task. The present disclosure overcomes the limitations of the conventional methods for detecting Parkinson's disease by utilizing a graph theory approach. Here, each pressure sensor attached to an insole corresponding to a plurality of pressure points associated with a foot of the subject is considered as a node of a connectivity graph. The foot dynamics analysis is performed based on a metric known as mediolateral stability index and the mediolateral stability index is calculated by utilizing a betweenness centrality associated with each node of the connectivity graph. Further, the mediolateral stability index is compared with standard values to detect the intensity of the Parkinson's disease.

A system for estimating a three dimensional pose of one or more persons in a scene is disclosed herein. The system includes one or more cameras and a data processor configured to execute computer executable instructions. The computer executable instructions include: (i) receiving one or more images of the scene from the one or more cameras; (ii) extracting features from the one or more images of the scene for providing inputs to a first branch pose estimation neural network and second branch pose estimation neural network; (iii) generating a first training signal from the second branch pose estimation neural network using a three dimensional reconstruction module for input into the first branch pose estimation neural network; (iv) generating one or more volumetric heatmaps; and (v) applying a maximization function to the one or more volumetric heatmaps to obtain a 3D pose of one or more persons in the scene.