A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

A method for identifying and correcting muscular and skeletal disbalances through exercise includes recording, by a processor, using at least one sensor coupled to the processor, an exercise motion performed by a user, identifying, by the processor, a motion deficiency of the user based on the detected exercise motion, formulating, by the processor, a corrective motion based on the detected motion deficiency, and providing, by the processor, the corrective motion to the user, which also includes identifying motion deficiencies as far as range of motion, balance, symmetry, smoothness, strength, stamina and other motion characteristics, formulating corrective exercise program that involves multiple training machines, formulating exercises in terms of number of repetitions, cadence (frequency) or motion, range of motion, added resistance levels, communicating the corrective exercise program via the screen embedded on each machine, and guiding the user through each exercise, directing user to change exercise machines.

A non-limiting example training instrument comprises a hollow main body formed of an aluminum alloy. The main body is constituted by two gripping portions opposite to each other with a space therebetween and a coupling portion coupling the two gripping portions. A load sensor is arranged in the coupling portion inside the main body. The load sensor is a load cell, a strain gauge affixed to an interior of the main body, and a part of the main body to which the strain gauge is affixed functions as a strain body. Therefore, if a user applies a force so as to bring the two gripping portions close to each other or a force so as to move the two gripping portions away from each other, a load thereof is detected by the load sensor.

A data collection method, a device, and a system are provided for automatically obtaining a user's movement interests. The data collection method includes: a movement information collection device obtaining a user's movement data; analyzing said user's movement data and determining the user's movement preferences according to said movement data; sending the user's information of the movement preference to a server, so that the server determines according to the user's information of the movement preference other users corresponding to said movement preferences. It is thus possible to automatically obtain a user's movement preferences.

A smart soccer goal for tracking and communicating motion of objects includes a goal frame; a net coupled to the goal frame including a plurality of lights; and one or more sensors coupled to the goal frame. A first sensor of the one or more sensors is directed to detecting movement within and immediately near the smart soccer goal and a second sensor of the one or more sensors is directed to detecting movement outside of the smart soccer goal.

Disclosed herein are various systems and methods for tracking and improving workout. As disclosed herein, exercise data associated with a user is received from a user device. Based on various other characteristics disclosed herein, the system may identify one or more known exercises from within the exercise data and then analyze the data related to the one or more known exercises to determine workout metrics. In some embodiments, the system may further evaluate the workout metrics using various techniques disclosed herein, and based on the evaluation a label may be associated with the workout metrics. The label and/or workout metrics may then be saved and/or provided to a user or another individual, such as a personal trainer.

The present disclosure provides a sit-up motion information management system and detection method based on an Internet of things. The method includes: acquiring detection data of a sensor at present time; determining whether the detection data of the sensor at the present time meet a first counting condition, determining that a sit-up action is correct if yes, and incrementing a flag value by one; acquiring detection data of the sensor at next time; determining whether the detection data of the sensor at the next time meet a second counting condition, determining that a sit-up action is correct if yes, and incrementing a flag value by one; determining whether a flag value is greater than or equal to a preset value to obtain a third determination result; and determining, if the third determination result indicates yes, that one rep of sit-up actions is completed, and recording a number of sit-up reps.

Systems and methods for evaluating the efficacy of entertaining elements during physical and cognitive therapeutic sessions are disclosed. The system is comprised of a means for providing visual and auditory information, and prompting a patient to perform physical and cognitive tasks of varying difficulty. The system is further comprised of a means of tracking the patient's movements to provide feedback to the patient and assess the performance of the patient's movements. Prompted movements are designed to provide therapeutic mental, behavioral, and physical health benefits to the patient, and may increase or decrease in difficulty based on prior assessments of a patient's movements. Entertaining elements are introduced in the visual and auditory information and assessed for their impact on the patient's performance of the movements.

A gait assistance apparatus including at least one sensor configured to sense a step motion of a user, and an operator configured to determine assistance forces of a right step and a left step of the user based on step motion information of the user and adjust the assistance force for at least one of the right step or the left step of the user based on a result of proportionally adding together the assistance forces of the right step and the left step based on a variable ratio may be provided.

The present invention discloses a method and system for providing sports performance data and motion data to a user. The system comprises a wireless device with a memory unit, a communication unit, and a data processing unit. The memory unit comprises a database having a plurality of pre-programmed inputs. The communication unit comprises a location identifying device for determining the location of a user. The data processing unit comprises a sensing module with sensors to measure and determine the movement of the users in accordance with sports which is then compared with a competitor over the network. A comparing module, via a processor and communication unit, receives and compares sports performance data of the users. A ranking module, via the processor calculates and ranks a user performance in a single competition or a variety of competition and provides ranking based on the common inputs received and the calculated performance obtained.