Abstract: Systems and methods for monitoring posture of a user wearing an exosuit are discussed herein. Exosuits worn by users can monitor several movement factors that characterize the user's movements and posture. The user's posture is identified and analyzed, and feedback is provided to the user based on the analyzed posture.

Abstract: A system and method for utilizing an activity monitoring device that includes, during a set of initial activity sessions, collecting the kinematic data from an activity monitoring device and generating a temporal record of at least one biomechanical signal that is calculated from the kinematic data; analyzing temporal changes in the biomechanical signals during the initial activity sessions and characterizing a fatigue model; and, during a subsequent activity session collecting current kinematic data of a participant and generating at least one current biomechanical signal from the current kinematic data, monitoring the fatigue state through processing the at least one current biomechanical signal according to the fatigue model, and triggering feedback in a user interface based on the fatigue state.

Abstract: A system and method for collecting a set of kinematic data streams from an activity tracking system with at least one activity monitoring system that is attached to a user; segmenting at least a subset of the kinematic data streams into a set of segments according to actions of the user; generating a set of biomechanical signals from the kinematic data streams wherein a biomechanical signal characterize a biomechanical property during a segment and includes generating a first integration data set through data integration and baseline error correction across the set of segments of the normalized kinematic data stream and determining at least a first biomechanical signal that is at least partially based on the first integration data set; and applying the set of biomechanical signals.

Abstract: A system and method are described herein for a sensor device which biomechanically detects in real-time a user's movement state and posture and then provides real-time feedback to the user based on the user's real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates. The sensor device detects the user's movement state and posture by capturing data from a tri-axial accelerometer in the sensor device. Streamed data from the accelerometer is normalized to correct for sensor errors as well as variations in sensor placement and orientation. Normalization is based on accelerometer data collected while the user is wearing the device and performing specific actions.

Abstract: Systems and methods for monitoring posture of a user wearing an exosuit are discussed herein. Exosuits worn by users can monitor several movement factors that characterize the user's movements and posture. The user's posture is identified and analyzed, and feedback is provided to the user based on the analyzed posture.

Abstract: Systems and methods for detecting and analyzing lifting and bending motions performed by a user wearing an exosuit are discussed herein. Exosuits worn by users can monitor several movement factors that characterize the user's bending and lifting movements. The bend or lift is identified and analyzed, and feedback is provided to the user based on the analysis of the bend or lift.

Abstract: A system and method for using performance signatures can include generating a set of performance features during an activity of the first participant by collecting kinematic data from at least one inertial measurement unit and generating a set of biomechanical signals; combining the set of performance features into the performance signature; generating at least a second performance signature from a set of participants; comparing the performance signature of the first participant to at least the second performance signature; and applying a result of the comparison to an interaction with at least one participant.

Abstract: Systems and methods and media for managing biomechanical achievements are provided. An exosuit or any other suitable sensor assembly worn by a user can be utilized by a system to monitor several movement factors that may characterize the user's movement and any changes in the user's movement with a high degree of specificity that may enable various system algorithms and/or models to predict or otherwise determine one or more biomechanical achievements of the user, such as recovery from a particular type of event (e.g., surgery or therapy procedure) and/or distance traveled (e.g., without using any global positioning system capabilities). In addition, an exosuit can provide useful feedback in response to such determinations.

Abstract: Systems and methods and media for managing biomechanical achievements are provided. An exosuit or any other suitable sensor assembly worn by a user can be utilized by a system to monitor several movement factors that may characterize the user's movement and any changes in the user's movement with a high degree of specificity that may enable various system algorithms and/or models to predict or otherwise determine one or more biomechanical achievements of the user, such as recovery from a particular type of event (e.g., surgery or therapy procedure) and/or distance traveled (e.g., without using any global positioning system capabilities). In addition, an exosuit can provide useful feedback in response to such determinations.

Abstract: Exosuit systems and methods according to various embodiments are described herein. The exosuit can be used to monitor users for injury, perform injury prevention, and monitor works for productivity.

Abstract: A system and method for collecting a set of kinematic data streams from an activity tracking system with at least one activity monitoring system that is attached to a user; segmenting at least a subset of the kinematic data streams into a set of segments according to actions of the user; generating a set of biomechanical signals from the kinematic data streams wherein a biomechanical signal characterize a biomechanical property during a segment and includes generating a first integration data set through data integration and baseline error correction across the set of segments of the normalized kinematic data stream and determining at least a first biomechanical signal that is at least partially based on the first integration data set; and applying the set of biomechanical signals.

Abstract: A system and method are described herein for a sensor device which biomechanically detects in real-time a user's movement state and posture and then provides real-time feedback to the user based on the user's real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates.

Abstract: A system and method are described herein for a sensor device which biomechanically detects in real-time a user's movement state and posture and then provides real-time feedback to the user based on the user's real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates. The sensor device detects the user's movement state and posture by capturing data from a tri-axial accelerometer in the sensor device. Streamed data from the accelerometer is normalized to correct for sensor errors as well as variations in sensor placement and orientation. Normalization is based on accelerometer data collected while the user is wearing the device and performing specific actions.

Abstract: A system and method for automatic location detection for wearable sensors can include collecting kinematic data from at least one kinematic activity sensor coupled to a user; generating a set of base kinematic metrics; assessing a set of sensor state discriminators and identifying a kinematic monitoring mode; and activating the kinematic monitoring mode at a kinematic activity sensor.

Abstract: A system and method are described herein for a sensor device which biomechanically detects in real-time a user's movement state and posture and then provides real-time feedback to the user based on the user's real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates. The sensor device detects the user's movement state and posture by capturing data from a tri-axial accelerometer in the sensor device. Streamed data from the accelerometer is normalized to correct for sensor errors as well as variations in sensor placement and orientation. Normalization is based on accelerometer data collected while the user is wearing the device and performing specific actions.

Abstract: A system and method are described herein for a sensor device which biomechanically detects in real-time a user's movement state and posture and then provides real-time feedback to the user based on the user's real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates.

Abstract: A system and method for remote monitoring for elderly fall prediction, detection, and prevention that includes collecting sensor data at a biomechanical sensing device coupled to a user; performing biomechanical analysis on the sensor data and thereby generating mobility metrics of the user, wherein performing biomechanical analysis including quantifying a set of gait dynamics as a component of the mobility metrics and generating a user activity graph as a component of the mobility metrics; processing the mobility metrics in a risk assessment model and thereby generating a fall risk assessment; and detecting a trigger condition and triggering a response to the fall risk assessment.

Abstract: A system and method that includes collecting kinematic data at an activity monitoring system coupled to a user; selecting a training activity of the user, the training activity selected from a plurality of training activity options; and processing the kinematic data in a processing mode of the selected training activity and thereby generating a set of training metrics that comprises at least one training metric.

Abstract: A system and method for activity monitoring eyewear and head apparel can include collecting kinematic data from an activity monitoring system that is coupled to a user head region; generating a set of activity signals that comprises at least one head orientation signal that is at least partially generated from the kinematic data head orientation signal from the kinematic data; monitoring the set of activity signals for a response condition; and triggering an action response upon detection of the response condition.

Abstract: A system and method are described herein for a sensor device which biomechanically detects in real-time a user's movement state and posture and then provides real-time feedback to the user based on the user's real-time posture. The feedback is provided through immediate sensory feedback through the sensor device (e.g., a sound or vibration) as well as through an avatar within an associated application with which the sensor device communicates. The sensor device detects the user's movement state and posture by capturing data from a tri-axial accelerometer in the sensor device. Streamed data from the accelerometer is normalized to correct for sensor errors as well as variations in sensor placement and orientation. Normalization is based on accelerometer data collected while the user is wearing the device and performing specific actions.