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: 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: 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 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 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 posture feedback can include collecting kinematic data by an activity monitoring device coupled to a user; calibrating the kinematic data to a base walking orientation of the activity monitoring device, which comprises: detecting a walking activity state through the kinematic data, and when a walking activity state is detected, generating the base walking orientation from kinematic data; setting a posture correction factor; measuring user posture with the calibrated kinematic data; triggering posture feedback based on the user posture adjusted by the posture correction factor.

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 are described herein for detecting a user's transition between sitting and standing postures. Transitions between sitting and standing states are reliably detected using an accelerometer attached to the user. By modeling error introduced by the accelerometer, and correcting for this error, transitions between sitting and standing states are reliably detected. A microprocessor coupled to the accelerometer converts the captured accelerometer data to approximate vertical acceleration. Vertical velocity, which includes accelerometer error, is determined from the approximate vertical acceleration. The vertical velocity is corrected, and the corrected vertical velocity used to determine vertical displacement. Transitions between sitting and standing states are determined from the vertical displacement.

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 for customizing biomechanical wearable sensors can include a customizable biomechanical processing layer, activity model layer, and/or device communication and processing management. The system and method can include monitoring biomechanical signals at a first set of wearable sensors configured in an initial biomechanical processing configuration; selecting a configuration option for the first set of wearable sensors; delivering the configuration option to the at least one wearable sensor; and monitoring biomechanical signals according to an altered biomechanical processing configuration that is altered according to the configuration option.

Abstract: A system and method for tracking running activity that includes an activity monitor device with an inertial measurement system, a communication module, a processor configured to generate a set of biomechanical signals from kinematic data collected from the inertial measurement system, a housing that internally contains the inertial measurement system, the communication module, and the processor, and an electrical interface exposed on the external side of the housing; and a user application operable on a second computing device distinct from the activity monitor device; wherein communication and generation of biomechanical signals are operable in many modes.

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 detecting a user's transition between sitting and standing postures. Transitions between sitting and standing states are reliably detected using an accelerometer attached to the user. By modeling error introduced by the accelerometer, and correcting for this error, transitions between sitting and standing states are reliably detected. A microprocessor coupled to the accelerometer converts the captured accelerometer data to approximate vertical acceleration. Vertical velocity, which includes accelerometer error, is determined from the approximate vertical acceleration. The vertical velocity is corrected, and the corrected vertical velocity used to determine vertical displacement. Transitions between sitting and standing states are determined from the vertical displacement.

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.