Abstract: An example device includes a plurality of computational memory banks. Each computational memory bank of the plurality of computational memory banks includes an array of memory units and a plurality of processing elements connected to the array of memory units. The device further includes a plurality of single instruction, multiple data (SIMD) controllers. Each SIMD controller of the plurality of SIMD controllers is contained within at least one computational memory bank of the plurality of computational memory banks. Each SIMD controller is to provide instructions to the at least one computational memory bank.

Abstract: An example device includes a plurality of computational memory banks. Each computational memory bank of the plurality of computational memory banks includes an array of memory units and a plurality of processing elements connected to the array of memory units. The device further includes a plurality of single instruction, multiple data (SIMD) controllers. Each SIMD controller of the plurality of SIMD controllers is contained within at least one computational memory bank of the plurality of computational memory banks. Each SIMD controller is to provide instructions to the at least one computational memory bank.

Abstract: An example device includes a plurality of computational memory banks. Each computational memory bank of the plurality of computational memory banks includes an array of memory units and a plurality of processing elements connected to the array of memory units. The device further includes a plurality of single instruction, multiple data (SIMD) controllers. Each SIMD controller of the plurality of SIMD controllers is contained within at least one computational memory bank of the plurality of computational memory banks. Each SIMD controller is to provide instructions to the at least one computational memory bank.

Abstract: A processing device includes an array of processing elements, each processing element including an arithmetic logic unit to perform an operation. The processing device further includes interconnections among the array of processing elements to provide direct communication among neighboring processing elements of the array of processing elements. A processing element of the array of processing elements may be connected to a first neighbor processing element that is immediately adjacent the processing element. The processing element may be further connected to a second neighbor processing element that is immediately adjacent the first neighbor processing element. A processing element of the array of processing elements may be connected to a neighbor processing element via an input selector to selectively take output of the neighbor processing element as input to the processing element. A computing device may include such processing devices in an arrangement of banks.

Abstract: An exercise feedback system determines muscle fatigue measurements using physiological data generated by a sensor-equipped athletic garment. The muscle fatigue measurement is determined by analyzing the frequency spread of the physiological data. The exercise feedback system may customize exercise programs, determine risks of injury, or generate biofeedback for presentation on graphical user interfaces using the muscle fatigue measurements. The exercise feedback system accesses pre-determined muscle fatigue measurement models that define criteria for the aforementioned features. For instance, if an athlete is becoming fatigued and exercising with improper form based on a muscle fatigue measurement, the exercise feedback system modifies the athlete's exercise program to help target and improve the athlete's weaknesses as well as to prevent injury.

Abstract: An exercise feedback system determines sensor data quality of an athletic garment based on bioimpedance data. The athletic garment includes sensors that can generate physiological data and bioimpedance data. An athlete wears the athletic garment while exercising. If the sensors have a stable contact with the skin of the athlete, the sensors generate high quality physiological data. However, if the sensors have unstable or no contact with the skin of the athlete, the sensors generate low quality physiological data. The exercise feedback system uses the magnitude and/or variance of the bioimpedance data to determine whether the physiological data is high or low quality. If the physiological data is high quality, the exercise feedback system may generate and provide feedback based on the physiological data for display to the athlete. The exercise feedback system may also use the bioimpedance data to identify defects in the garment during quality assurance tests.

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: A technique provides sync capability as an independent backend service, which developers can include, at their option, in their cloud-based applications. In accordance with the improved technique, a sync service runs in a backend system in connection with a set of data. The sync service syncs changes in the set of data among application instances that have access to the set of data. Sync services may be specified selectively for different sets of data, e.g., by specifying syncing for one set of data but not for another set of data.

Abstract: A processing device includes an array of processing elements, each processing element including an arithmetic logic unit to perform an operation. The processing device further includes interconnections among the array of processing elements to provide direct communication among neighboring processing elements of the array of processing elements. A processing element of the array of processing elements may be connected to a first neighbor processing element that is immediately adjacent the processing element. The processing element may be further connected to a second neighbor processing element that is immediately adjacent the first neighbor processing element. A processing element of the array of processing elements may be connected to a neighbor processing element via an input selector to selectively take output of the neighbor processing element as input to the processing element. A computing device may include such processing devices in an arrangement of banks.

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: A technique provides sync capability as an independent backend service, which developers can include, at their option, in their cloud-based applications. In accordance with the improved technique, a sync service runs in a backend system in connection with a set of data. The sync service syncs changes in the set of data among application instances that have access to the set of data. Sync services may be specified selectively for different sets of data, e.g., by specifying syncing for one set of data but not for another set of data.

Abstract: An improved technique pushes change notifications to application instances running on frontend clients. In accordance with the improved technique, a backend system sends compact change notifications merely to inform the application instances that contents of the data storage container have changed. The application instances may then respond by requesting the changed content of the data storage container. In response to the request, the backend system provides the requested contents.

Abstract: An exercise feedback system determines muscle fatigue measurements using physiological data generated by a sensor-equipped athletic garment. The muscle fatigue measurement is determined by analyzing the frequency spread of the physiological data. The exercise feedback system may customize exercise programs, determine risks of injury, or generate biofeedback for presentation on graphical user interfaces using the muscle fatigue measurements. The exercise feedback system accesses pre-determined muscle fatigue measurement models that define criteria for the aforementioned features. For instance, if an athlete is becoming fatigued and exercising with improper form based on a muscle fatigue measurement, the exercise feedback system modifies the athlete's exercise program to help target and improve the athlete's weaknesses as well as to prevent injury.

Abstract: An exercise feedback system determines sensor data quality of an athletic garment based on bioimpedance data. The athletic garment includes sensors that can generate physiological data and bioimpedance data. An athlete wears the athletic garment while exercising. If the sensors have a stable contact with the skin of the athlete, the sensors generate high quality physiological data. However, if the sensors have unstable or no contact with the skin of the athlete, the sensors generate low quality physiological data. The exercise feedback system uses the magnitude and/or variance of the bioimpedance data to determine whether the physiological data is high or low quality. If the physiological data is high quality, the exercise feedback system may generate and provide feedback based on the physiological data for display to the athlete. The exercise feedback system may also use the bioimpedance data to identify defects in the garment during quality assurance tests.