Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system calibrates sensors of an athletic garment worn by an athlete while performing exercises. The sensors can record physiological data such as muscle activation. The system instructs the athlete to perform a calibration workout. The system generates a calibration value based on physiological data from the calibration workout and/or user information. The calibration value indicates, for example, the predicted maximum amplitude for the muscle activation of a particular muscle group (for example, glutes, hamstrings, or quadriceps) of the athlete. The system can update the calibration value over time as the system receives additional physiological data from subsequent exercises performed by the athlete. The system may determine a confidence level of the calibration value and may update the calibration value if the confidence level becomes too low. The system provides biofeedback to the athlete generated based on the calibration value.

Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system receives a first set of physiological data from a garment worn by a user and user information from a client device of the user, the first set of physiological data describing muscle activation of a plurality of muscles of the user while performing a calibration workout. The exercise feedback system determines a calibration value based at least in part on the first set of physiological data and the user information. When the exercise feedback system receives a second set of physiological data describing muscle activation of the plurality of muscles while performing a subsequent workout from the garment, the exercise feedback system modifies the calibration value based on the second set of physiological data. The exercise feedback system provides biofeedback generated based on the modified calibration value to the user via the client device.

Abstract: An electrode system for sensing biometric signals from a body region of a user and a method of manufacture thereof, the electrode system comprising: a substrate comprising a reference region and a signal communication region, the signal communication region including a set of conductive leads; a set of biosensing contacts coupled to the set of conductive leads; a non-conductive region ensheathing each of the set of biosensing contacts, the non-conductive region including: a set of openings that expose at least a portion of each of the set of biosensing contacts for interfacing with the body region of the user, upon coupling of the electrode system to the user; a first bonding layer that couples the substrate to a fabric base; and a second bonding layer coupled to the first bonding, wherein the substrate is hermetically sealed between the first bonding layer and the second bonding layer.

Abstract: The invention(s) described are configured to process sensor data in order to optimize or otherwise improve training of users for achievement of goals in relation to performing an activity. The invention(s) can also iteratively adapt training in a personalized manner, with assessment of training results and subsequent modification of training regimens, in order to provide improved alignment between users and their goals. Such iteration can drive interventions provided to users throughout the course of training, and allow the system to iteratively develop better and more precise interventions (e.g., through manual means, through machine learning models with generated training and test data). Such iteration, with large datasets applied to populations of users can also increase the breadth of user states that the can be addressed, with respect to provided interventions, and improve rates at which interventions are provided.

Abstract: An electrode system for sensing biometric signals from a body region of a user and a method of manufacture thereof, the electrode system comprising: a substrate comprising a reference region and a signal communication region, the signal communication region including a set of conductive leads; a set of biosensing contacts coupled to the set of conductive leads; a non-conductive region ensheathing each of the set of biosensing contacts, the non-conductive region including: a set of openings that expose at least a portion of each of the set of biosensing contacts for interfacing with the body region of the user, upon coupling of the electrode system to the user; a first bonding layer that couples the substrate to a fabric base; and a second bonding layer coupled to the first bonding, wherein the substrate is hermetically sealed between the first bonding layer and the second bonding layer.

Abstract: An exercise feedback system generates biofeedback based on physiological adaptations. The exercise feedback system processes physiological data from sensor-equipped garments worn by athletes while performing exercises. The exercise feedback system may use a trained model to determine classifications of segments of the physiological data. Classifications may represent a type of physiological adaptation, for example, power, strength, hypertrophy, endurance, or speed. Athletes can focus on one or more physiological adaptations, which may be based on a specific sport or training goal of an athlete. The exercise feedback system may also use other types of sensor data from the garments such as motion data or bioimpedance information. The exercise feedback system can generate biofeedback including metrics determined using the classifications. For example, the metrics indicate training load aggregated over multiple muscles or workouts, or the biofeedback may notify athletes regarding a risk of injury.

Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system calibrates sensors of an athletic garment worn by an athlete while performing exercises. The sensors can record physiological data such as muscle activation. The system instructs the athlete to perform a calibration workout. The system generates a calibration value based on physiological data from the calibration workout and/or user information. The calibration value indicates, for example, the predicted maximum amplitude for the muscle activation of a particular muscle group (for example, glutes, hamstrings, or quadriceps) of the athlete. The system can update the calibration value over time as the system receives additional physiological data from subsequent exercises performed by the athlete. The system may determine a confidence level of the calibration value and may update the calibration value if the confidence level becomes too low. The system provides biofeedback to the athlete generated based on the calibration value.

Abstract: An exercise feedback system determines muscle stress measurements using physiological data generated by a sensor-equipped athletic garment. A muscle stress measurement represents an accumulated normalized signal from one or more of the sensors corresponding to a given muscle over a period of time. The exercise feedback system may customize exercise programs, determine risks of injury, or generate biofeedback for presentation on graphical user interfaces using the muscle stress measurements. In an embodiment, the exercise feedback system accesses pre-determined muscle stress measurement models that define criteria for the aforementioned features. For instance, responsive to determining that an athlete is becoming fatigued and exercising with improper form based on a muscle stress measurement, the exercise feedback system modifies the athlete's exercise program to help target and improve the athlete's weaknesses.

Abstract: An exercise feedback system determines muscle stress measurements using physiological data generated by a sensor-equipped athletic garment. A muscle stress measurement represents an accumulated normalized signal from one or more of the sensors corresponding to a given muscle over a period of time. The exercise feedback system may customize exercise programs, determine risks of injury, or generate biofeedback for presentation on graphical user interfaces using the muscle stress measurements. In an embodiment, the exercise feedback system accesses pre-determined muscle stress measurement models that define criteria for the aforementioned features. For instance, responsive to determining that an athlete is becoming fatigued and exercising with improper form based on a muscle stress measurement, the exercise feedback system modifies the athlete's exercise program to help target and improve the athlete's weaknesses.

Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.

Abstract: An exercise feedback system calibrates sensors of an athletic garment worn by an athlete while performing exercises. The sensors can record physiological data such as muscle activation. The system instructs the athlete to perform a calibration workout. The system generates a calibration value based on physiological data from the calibration workout and/or user information. The calibration value indicates, for example, the predicted maximum amplitude for the muscle activation of a particular muscle group (for example, glutes, hamstrings, or quadriceps) of the athlete. The system can update the calibration value over time as the system receives additional physiological data from subsequent exercises performed by the athlete. The system may determine a confidence level of the calibration value and may update the calibration value if the confidence level becomes too low. The system provides biofeedback to the athlete generated based on the calibration value.