The present invention relates to a physical performance assessment method including the steps of: collecting a patient's motion acceleration signals for the patient's motion analysis measured from a motion acceleration sensor attached to the patient's head through a motion measurement module; and deriving a plurality of motion parameters based on the collected motion acceleration signals through a motion analysis module.

A system, method and article of manufacture are presented for assisting the fields of health care, kinesiology, and sports medicine. More specifically the method of the system measures the dynamics of the biomechanics of motion of a human patient or athlete and quantitatively determining the presence or absence of biomechanical abnormalities, classifying abnormalities that are present, developing or critiquing one or more diagnoses in terms of the biomechanics evidence supporting the classification, recommending an appropriate training or treatment regimen based on the diagnoses, and monitoring progress while the individual is under the training or treatment regimen.

A system and/or method that uses a body posture of a user to determine and modulate a content mode of a virtual reality system. The content mode may define the manner in which virtual reality content is presented to the user and/or the manner in which the user interacts with the virtual reality content. The user's body posture and/or a change in body posture may cause the content mode and/or the virtual reality content to change accordingly. In some implementations, primary content may be presented to the user according to a first content mode in response to the user sitting. Secondary virtual reality content may be presented to the user according to the second content mode in response to the user standing. As such, a user may initiate a change in the virtual reality content and/or the content mode by standing from a sitting posture and/or sitting from a standing posture.

A method for prediction of a head impact event mechanism via an instrumented mouthguard device comprises receiving, as input, time series data representative of a head impact event, wherein the time series data is derived from the instrumented mouthguard device. The instrumented mouthguard device includes one or more accelerometers. The method further comprises generating an array of spatial coordinates representing points on a computer head model, and processing the time series data to determine a direction of impact and location of impact relative to the computer head model.

A System for Measuring Body Kinetics includes a wearable device configured to be wrapped around a joint. A microprocessor is attached to the wearable device, One or more Inertial Measurement. Units (IMUS) are connected to the microprocessor and arranged on the wearable device. The IMUS are arranged and configured to provide kinetic data concerning the joint to the microprocessor. A wireless transmission component is connected to the microprocessor. The microprocessor is configured to receive kinetic data from the IMUs, and to transmit the kinetic data by way of the wireless transmission component to a central processor or other device. An algorithm resides within the microprocessor or the central processor or other device, and is configured to determine the position of each IMU from the kinetic data. The wearable device may be constructed of fabric, strap, adhesive tape, or a combination thereof.

A posture measurement apparatus and method is described. The posture measurement system includes a wearable sensor leader node comprising a UWB transceiver coupled to at least two antennas and one or more wearable sensor follower nodes each comprising a UWB transceiver coupled to one antenna. A first UWB signal is transmitted from the wearable sensor leader node to the one or more wearable follower sensor nodes. A second UWB signal is received by the wearable sensor leader node from each follower sensor node in response to receiving the first UWB signal. A time-of-flight value of a signal transmitted between the wearable leader sensor node and the wearable follower sensor node is determined from the first UWB signal and the second UWB signal. An angle of arrival value is determined from the second UWB signal. The body posture can be determined from the time-of-flight and angle-of-arrival value.

The embodiment of the present disclosure provides a method and a system for identifying a user action. The method and system may obtain user action data collected from a plurality of measurement positions on a user, the user action data corresponding to an unknown user action, identify that the user action includes a target action when obtaining the user action data based on at least one set of target reference action data, the at least one set of target reference action data corresponding to the target action, and send information related to the target action to the user.

A multiple sensor-fusing based interactive training system, including a posture sensor, a sensing module, a computing module, and a display module, is provided. The posture sensor is configured to sense posture data and myoelectric data related to a training action. The sensing module is configured to output limb torque data according to the posture data, and output muscle group activation time data according to the myoelectric data. The computing module is configured to respectively convert the limb torque data and the muscle group activation time data into a moment-skeleton coordinate system and a muscle strength eigenvalue-skeleton coordinate system according to a skeleton coordinate system, perform fusion calculation, calculate evaluation data based on a result of the fusion calculation, and judge that the training action corresponds to a known exercise action according to the evaluation data. The display module is configured to display the evaluation data and the known exercise action.

This disclosure relates generally to real time analysis of range of motion (ROM), wherein ROM is a measurement of movement around a specific joint or body part. The existing techniques for ROM fail for measurements made in certain planes and are not very effective for ROM measurements for extremely slow and very fast movements. The disclosed provides a real time analysis of ROM based on computation of range of motion (ROM) of a joint and a set of ROM parameters using a gyroscope. The gyroscope collects data from a subject at pre-defined neutral position of the subject as well as a pre-defined rotation movement of a joint of the subject. The received data is corrected for bias and processed at real time to analyze the ROM by computing range of motion (ROM) of a joint and a set of ROM parameters.

Systems and methods for estimating anatomic alignment between two or more bones are described herein. An example method can include registering an anatomic reference frame. Additionally, the method can include establishing a respective rotational relationship between each of one or more bones and an orientation sensor attached to each of the one or more bones. The method can also include receiving, from each of the orientation sensors, orientation information, and then calculating an orientation of a bone relative to the anatomic reference frame. The method can further include calculating, using the respective orientations of the bones relative to the anatomic reference frame, an anatomic alignment parameter between first and second bones.