A device and a method for identifying a motion pattern of a person that allow suitable feedback about an identified motion pattern to be produced in real time, to address the disadvantage that there is no provision for direct feedback to the person in the event of abnormal behavior being detected. This is achieved by virtue of a device for identifying a motion pattern of a person having at least one sensor for capturing motion parameters and at least one evaluation unit, which is couplable to the at least one sensor, for evaluating the motion parameters and for producing a motion pattern.

The invention relates to articles of footwear having traction elements, and systems and methods for manufacturing same. An example shoe includes an upper and a sole plate, the sole plate including a lower surface adapted for ground contact having a first sole portion including first traction elements, the first traction elements having a distal end and a side wall with extensions extending from a central core, and a second sole portion including second traction elements, the second traction elements having at least one geometrical feature differing in one or more aspects from a corresponding geometrical feature of the first traction elements.

A walking training system according to an embodiment includes: a treadmill; a foot sole load detection unit configured to detect load received from foot soles of a trainee aboard a belt of the treadmill; a first photographing device configured to photograph the trainee from a lateral side; a skeletal information acquisition unit configured to acquire first skeletal information that is skeletal information on the trainee in a sagittal plane from an image photographed by the first photographing device; and a specification unit configured to specify respective pieces of skeletal information on a right leg and a left leg included in the first skeletal information acquired by the skeletal information acquisition unit, based on the load received from the foot soles of the trainee detected by the foot sole load detection unit.

The invention relates to a system for analyzing (1) the use of footwear items (11) configured to determine an association index between use parameter values (101) and shoe parameter values (201), said system a calculation computing device (30) configured for: Obtaining or loading posture or mobility parameter values (301) calculated from raw data generated by at least one connected sole (10); Obtaining or loading geographic parameter values (401) corresponding to a location of the at least one connected sole (10); Obtaining or loading shoe parameter values (201) including values of structural parameters, geometric parameters and/or aesthetic parameters of the footwear item (11); Calculating one or more use parameter values (101); Determining an association index value between the use parameter value(s) (101) and the shoe parameter values (201).

A haptic system for providing a gait cadence to a subject comprising a portable telecommunication device with a control unit and a wireless transmission means; a vibrotactile device configured to be tightly worn on a portion of the subject's body, including at least one motor configured to generate vibrations that can be perceived by the subject and an actuation unit configured to actuate the motor. The actuation unit is configured to receive wireless signals from the wireless transmission means of the portable telecommunication device and to cause the motor to produce vibrations responsive to the wireless signals. In the control unit a generation program is resident configured to generate cadence signals and to transmit the wireless signals responsive to the cadence signals by the wireless transmission means to the actuation unit. The generation program is configured to provide corresponding cadence pulses to the motor.

An insole mapping apparatus (10C), including: at least one location sensor (20C) and potentially two or more location sensors such as (20A,20B) each for being attached to one organ of the user (19), for measuring locations (21A,21B,21C) of the organs in relation to at least one stationary object (26A); and a processor (29), for determining deformations (36A1) of a body of the user (19) according to the measurements (21A,21B,21C), and for determining an insole map (74) being opposite to the determined deformations (36A1).

A walking training system according to the present embodiment includes: a treadmill; a load distribution sensor that is provided on a lower side of a belt of the treadmill so as not to move together with the belt and that detects a distribution of a load received from a sole of a trainee riding on the belt of the treadmill; an extraction unit that extracts a load distribution in a region corresponding to a position of the sole of the trainee during walking training, out of a load distribution detected by the load distribution sensor; and a determination unit that determines a walking state of the trainee based on the load distribution extracted by the extraction unit.

A method of preventing a fall risk and an apparatus for performing the method includes receiving, by a fall prevention apparatus, gait data, generating, by the fall prevention apparatus, gait analysis data on the basis of analysis of the gait data, and generating, by the fall prevention apparatus, fall prevention data on the basis of the gait analysis data.

A computing system configured to perform operations that identify user movement(s) as upper-body exercise(s). The operations can include obtaining sensor data generated by one or more sensors of a footwear device worn by a user, the one or more sensors positioned in one or more positions of the footwear device, the sensor data associated with one or more movements performed by the user. The sensor data can be input into a machine-learned exercise identification model. Exercise identification data can be received as an output of the machine-learned exercise identification model. The exercise identification data can identify the one or more movements performed by the user as one or more upper-body exercises performed by the user, the exercise identification data comprising one or more exercise characteristics associated with each upper-body exercise of the one or more upper-body exercises performed by the user.

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.