A golf swing analysis apparatus detects a state of a shaft of a golf club by using an output from an inertial sensor, calculates a relative rotation angle of the shaft which changes about an axis of the shaft until the shaft transitions from a first state to a second state due to a swing of the shaft, and compares the calculated relative rotation angle with a reference relative rotation angle in a reference swing which is used as a reference, with respect to at least one of a change range of the relative rotation angle, the required time from the first state to a state in which the relative rotation angle becomes the maximum, and the maximum value of the relative rotation angle, and outputs a comparison result.

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 method includes collecting an original signal in a specified time interval, performing combined acceleration processing on the original signal to obtain a combined acceleration signal, combining n data points of the combined acceleration signal into one data segment, extracting a feature point of the data segment, transforming feature points of all data segments into a feature point signal, analyzing the feature point signal to obtain a stable stage and a fluctuation stage of the feature point signal, performing interference period elimination on the feature point signal with the stable stage and the fluctuation stage according to a specified motion rule to obtain a second feature point signal, and counting a quantity of wave crests of the second feature point signal, where the quantity of wave crests is a quantity of steps.

Apparatus, systems, and methods are provided for measuring and analyzing movements of a body and for communicating information related to such body movements over a network. In certain embodiments, a system gathers biometric and biomechanical data relating to positions, orientations, and movements of various body parts of a user performed during sports activities, physical rehabilitation, or military or law enforcement activities. The biometric and biomechanical data can be communicated to a local and/or remote interface, which uses digital performance assessment tools to provide a performance evaluation to the user. The performance evaluation may include a graphical representation (e.g., a video), statistical information, and/or a comparison to another user and/or instructor. In some embodiments, the biometric and biomechanical data is communicated wirelessly to one or more devices including a processor, display, and/or data storage medium for further analysis, archiving, and data mining. In some embodiments, the device includes a cellular telephone.

An adaptive training system can determine a finite work capacity and critical power and use those determinations to generate an adaptive training programs for workout parameters. To determining a finite work capacity and critical power, the adaptive training system can receive workout data; generate data points by determining, for each workout, a maximum amount of work done for each of multiple time window sizes; fit these workout data points to a function; and determine a critical power and finite work capacity based on the fitted function. Once the adaptive training system has determined a critical power and finite work capacity, the adaptive training system can use them to generate an adaptive training program by keeping a function defined by a set of workout parameters below an ability function that is based on the critical power and finite work capacity.

The present application is directed to a method for use in a system implementing a reference golf club, one or more sensors associated with the reference golf club, and a computing device. The method comprises receiving from the one or more sensors, by the computing device, swing data relating to a swing of the reference golf club, analyzing, by the computing device, the swing data to determine recommended shaft parameter values for each of a plurality of shaft parameters using an algorithm, accessing, by the computing device, a shaft database comprising actual shaft parameter values for each of the plurality of shaft parameters for each of a plurality of shafts, determining, by the computing device, at least one shaft from the plurality of shafts based, at least in part, on a comparison between the recommended shaft parameter values and the actual shaft parameter values, transmitting, by the computing device, information relating to the at least one shaft; and displaying, by the computing device, the information on a display of the computing device.

A system and method for analyzing and improving the performance of a body motion of an animal or human subject requires instrumenting a subject with inertial sensors, monitoring a body motion of interest, converting sensor data into motion data and animation, comparing the motion data with existing data for motion related performance parameters, providing a real-time, information rich, animation and data display of the results in color coded displays; and based on the results prescribing a training regime with exercises selected from a library of standardized exercises using standardized tools and training aids.

This disclosure relates to systems, media, and methods for quantifying and monitoring exercise parameters and/or motion parameters, including performing data acquisition, analysis, and providing scientifically valid, clinically relevant, and/or actionable diagnostic feedback. Disclosed embodiments may receive real-time sensor data from a motion sensor or sensors mounted on a user and/or equipment while a user performs a test motion. Disclosed embodiments may also calculate a test motion profile based on the real-time sensor data, the test motion profile describing a multi-dimensional representation of the test motion performed by the user or computed motion profiles. Disclosed embodiments may include comparing the test motion profile to a template motion profile to determine a deviation amount for the test motion profile indicating how the test motion deviated from the template motion profile. Still further embodiments may correlate test motion profiles over time with health indicators.

Systems and methods for creating personalized exercise programs are disclosed. An image capture device and a computer device are used to capture images of a user while the user performs athletic movements. The images may then be evaluated to create a human movement screen score. The human movement screen score, goal and time commitment information may then be used to create a personalized exercise program tailored to the specific user.

A living body guidance device includes: a measurement unit 1 that measures biometric information of a user; a stimulus unit 2 that is installed in contact with the user's body and presents a tactile stimulus to the user; a database unit 3 that has a relationship between the tactile stimulus presented by the stimulus unit and the biometric information according to the tactile stimulus recorded; an input unit 4 that sets target biometric information which is target biometric information that is desired of the user to realize; and a control unit 7 that, when there is a difference between current biometric information which is current biometric information of the user estimated based on the measurement result by the measurement unit and the target biometric information, controls the tactile stimulus presented by the stimulus unit so that the difference is reduced, so as to guide the user so that the current biometric information approaches the target biometric information, based on the relationship recorded in the database unit, by.