Abstract: A method of using a sensor platform of a garment of a wearer in order to interact with a remote networked device using a plurality of sensed biometric data, the method comprising: receiving from the sensors a set of the plurality of biometric data; comparing the set to a data model including a plurality of model data parameters; determining whether said comparing indicates a need for a command to be sent to the remote networked device in order to effect a change in an operational characteristic of the networked device; sending the command to the networked device; receiving a further set of the plurality of biometric data; further comparing the further set to the data model; and determining whether said further comparing indicates a need for a further command to be sent to the remote networked device in order to further effect a change in an operational characteristic of the networked device.

Abstract: A resilient fabric band providing a sensor platform for a wearer in order to sense a plurality of biometric data, the band comprising: a pair of ECG sensors coupled to an interior surface of a body of the band, each of the pair of ECG sensors located on either side of a front to back centerline of the body; a pair of bio impedance sensors coupled to the interior surface of the body of the band, each of the pair of bio impedance sensors located on either side of the front to back centerline; a strain gauge sensor coupled to the body of the band; a computer device mounted on the body of the band via a housing, the computer device including a power source, a computer processor, a memory for storing instructions for execution by the computer processor, and a network interface for transmitting data sensed by the sensors; and a plurality of communication pathways connecting the computer device to each of the sensors, the communication pathway for sending power from the power supply to the sensors as controlled by t

Abstract: A method of using a sensor platform of a garment of a wearer in order to interact with a remote networked device using a plurality of sensed biometric data, the method comprising: receiving from the sensors a set of the plurality of biometric data; comparing the set to a data model including a plurality of model data parameters; determining whether said comparing indicates a need for a command to be sent to the remote networked device in order to effect a change in an operational characteristic of the networked device; sending the command to the networked device; receiving a further set of the plurality of biometric data; further comparing the further set to the data model; and determining whether said further comparing indicates a need for a further command to be sent to the remote networked device in order to further effect a change in an operational characteristic of the networked device.

Abstract: A resilient fabric band providing a sensor platform for a wearer in order to sense a plurality of biometric data, the band comprising: a pair of ECG sensors coupled to an interior surface of a body of the band, each of the pair of ECG sensors located on either side of a front to back centerline of the body; a pair of bio impedance sensors coupled to the interior surface of the body of the band, each of the pair of bio impedance sensors located on either side of the front to back centerline; a strain gauge sensor coupled to the body of the band; a computer device mounted on the body of the band via a housing, the computer device including a power source, a computer processor, a memory for storing instructions for execution by the computer processor, and a network interface for transmitting data sensed by the sensors; and a plurality of communication pathways connecting the computer device to each of the sensors, the communication pathway for sending power from the power supply to the sensors as controlled by t

Abstract: Systems, methods and devices for recognizing user activity using data from accelerometer or other sensors. “Feature-based” approach and “model-based” approaches are described. In a feature-based approach, various values are extracted from input signals and projected onto a space that is selected to facilitate better segregation of data points. Classifiers identify the regions in this projected space in which the data points fall to distinguish between the different activity types. In a “model-based” approach, a generative model is trained for each activity type. Different activity types can be distinguished by identifying similarities between the input data with the generative models.

Abstract: Systems, methods and devices that facilitate determination of enhanced exercise or physical activity metrics by considering multiple types of data. Metrics are computable by pre-processing, and in some cases segmenting, a variety of input signals, such as acceleration signals, electromyography signals or other signals from a wearable device.

Abstract: A resilient fabric band providing a sensor platform for a wearer in order to sense a plurality of biometric data, the band comprising: a pair of ECG sensors coupled to an interior surface of a body of the band, each of the pair of ECG sensors located on either side of a front to back centerline of the body; a pair of bio impedance sensors coupled to the interior surface of the body of the band, each of the pair of bio impedance sensors located on either side of the front to back centerline; a strain gauge sensor coupled to the body of the band; a computer device mounted on the body of the band via a housing, the computer device including a power source, a computer processor, a memory for storing instructions for execution by the computer processor, and a network interface for transmitting data sensed by the sensors; and a plurality of communication pathways connecting the computer device to each of the sensors, the communication pathway for sending power from the power supply to the sensors as controlled by t

Abstract: A resilient fabric band providing a sensor platform for a wearer in order to sense, a plurality of biometric data, the band comprising: a pair of ECG sensors coupled to an interior surface of a body of the band, each of the pair of ECG sensors located on either side of a front to back centerline of the body; a pair of bio impedance sensors coupled to the interior surface of the body of the band, each of the pair of bio impedance sensors located on either side of the front to back centerline; a strain gauge sensor coupled to the body of the band; a computer device mounted on the body of the band via a housing, the computer device including a power source, a computer processor, a memory for storing instructions for execution by the computer processor, and a network interface for transmitting data sensed by the sensors; and a plurality of communication pathways connecting the computer device to each of the sensors, the communication pathway for sending power from the power supply to the sensors as controlled by

Abstract: A system, method and device are described for biometric analysis using a wearable device. The device can be removeably securable to a user's skin surface and can include a plurality of electrodes positioned to acquire electrical signals from the skin surface. The device can also include an electromyography acquisition module and skin impedance acquisition module. A processing unit can use the electrodes to capture a plurality of electrical signals including at least one electromyography signal. The processing unit can generate calibration data based on a subset of the captured electrical signals and process the electromyography signals using the calibration data to determine a biometric for the user.

Abstract: A system, method and device are described for detecting a heart rate. A sensing unit can have a skin-facing surface that is removably securable to a user's skin surface and include at least one sensor positioned to acquire a bio-signal from the skin surface. A controller can be configured to capture a bio-signal stream using the at least one sensor and generate a preprocessed bio-signal stream by band-pass filtering the captured bio-signal stream with a predetermined passband. The controller can also be configured to determine, in a moving window, heartbeat signal portions when the preprocessed bio-signal stream has heartbeat impulse characteristics and determine the time between adjacent heartbeat signal portions to compute the heart rate.

Abstract: A system, method and device are described for detecting a heart rate. A sensing unit can have a skin-facing surface that is removably securable to a user's skin surface and include at least one sensor positioned to acquire a bio-signal from the skin surface. A controller can be configured to capture a bio-signal stream using the at least one sensor and generate a preprocessed bio-signal stream by band-pass filtering the captured bio-signal stream with a predetermined passband. The controller can also be configured to determine, in a moving window, heartbeat signal portions when the preprocessed bio-signal stream has heartbeat impulse characteristics and determine the time between adjacent heartbeat signal portions to compute the heart rate.

Abstract: Systems, methods and devices for recognizing user activity using data from accelerometer or other sensors. “Feature-based” approach and “model-based” approaches are described. In a feature-based approach, various values are extracted from input signals and projected onto a space that is selected to facilitate better segregation of data points. Classifiers identify the regions in this projected space in which the data points fall to distinguish between the different activity types. In a “model-based” approach, a generative model is trained for each activity type. Different activity types can be distinguished by identifying similarities between the input data with the generative models.

Abstract: A system, method and device are described for biometric analysis using a wearable device. The device can be removeably securable to a user's skin surface and can include a plurality of electrodes positioned to acquire electrical signals from the skin surface. The device can also include an electromyography acquisition module and skin impedance acquisition module. A processing unit can use the electrodes to capture a plurality of electrical signals including at least one electromyography signal. The processing unit can generate calibration data based on a subset of the captured electrical signals and process the electromyography signals using the calibration data to determine a biometric for the user.

Abstract: Systems, methods and devices that facilitate determination of enhanced exercise or physical activity metrics by considering multiple types of data. Metrics are computable by pre-processing, and in some cases segmenting, a variety of input signals, such as acceleration signals, electromyography signals or other signals from a wearable device.