Abstract: Systems and methods for gesture-based control are provided. A system may include a wearable device configured to be worn on a wrist of a person and comprising one or more sensors and a display. The wearable device being configured to obtain at least physiological data being configured to indicate a state of a person's hand and wrist location data comprising information relating to a position of the person's wrist. The system may be configured to transition between states in response to gestures detected based on the physiological data and/or the wrist location data.

Abstract: Systems and methods for gesture-based control are provided. In some embodiments, a system may include a wearable device configured to be worn on a person's wrist. The wearable device may include a plurality of biopotential channels, a location sensor, and a processor. The system may be configured to generate a data stream based on the outputs from the biopotential channels and/or the location sensor. The system may be configured to enter a first state in which the output from the location sensor is processed according to a first set of logical rules. The system may be configured to classify a gesture, and, based on the gesture classification, transition to a second state in which the output from the location sensor is processed according to a second set of logical rules that is different than the first set of logical rules.

Abstract: Systems and methods for gesture-based control are provided. A system may include a wearable device comprising a plurality of biopotential channels and a location sensor. The system may be configured to generate a data stream and classify a gesture based on an analysis of an analytical segment. The gesture classification may include (a) determining that a first portion of the analytical segment shows a signal parameter at a baseline; (b) determining that a second portion of the analytical segment shows the signal parameter satisfying a first threshold condition; (c) determining that a third portion of the analytical segment shows the signal parameter satisfying a second threshold condition; (d) determining that a time between the second portion and the third portion is greater than a threshold; and (e) while the signal parameter satisfies the first and/or second threshold condition, detecting a change in location of the wearable device.

Abstract: Systems and methods for gesture-based control are disclosed. In some embodiments, a system may include a wearable device configured to obtain physiological data and wrist location data. The system may be configured to detect a first gesture and transition to an object control state in which changes in the wrist location data and/or the physiological data are configured to control a movement of the object. In the object control state, the system may be configured to detect a first motion of a body part, generate a first command to move the object in a first command direction, detect a second motion of the body part, and generate a command to move the object in a second command direction. The system may detect a second gesture indicating an intention to cease control of the object, and transition out of the object control state.

Abstract: System and methods for gesture-based control are described. In some embodiments, a system may include a wearable device having a biopotential sensor and a wrist motion sensor. The biopotential sensor may be configured to output a first data stream indicating actions of a person's hand. The system may further include a second device configured to output a second data stream, which may also indicate the actions of the person's hand. The system may be configured to analyze the first and second data streams to train a machine learning interpreter to classify actions of a person's hand based on at least biopotential data.

Abstract: Systems and methods for gesture control are disclosed. In some embodiments, a system may include a plurality of electrode pairs, a motion sensor, a controller, and a classifier. The system may be configured to: enter a monitoring state in which the system is configured to receive data; receive a first set of data; determine that the first set of data does not satisfy one or more action criteria; return to the monitoring state without transmitting the first set of data to the classifier; receive a second set of data; determine that the second set of data satisfies the one or more action criteria; transmit the second set of data to the classifier; using the classifier, analyze the second set of data to generate an interpreted output indicating a gesture performed by the person; and based on the interpreted output, generate a machine instruction.

Abstract: Systems and methods for position-based gesture control are described. In some embodiments, a system may include a wearable device including a biopotential sensor and a location sensor. The system may be configured to determine that a body part is in a first position relative to a person's body, detect a first gesture, and, in response, direct a first instruction to a first destination. The system may be further configured to determine that a body part is in a second position relative to the person's body, detect a second gesture, and, in response, direct a second instruction to a second destination different than the first destination.

Abstract: Systems and methods for gesture-based control are disclosed. In some embodiments, a system may include a wearable device configured to obtain physiological data and wrist location data. The system may be configured to detect a first gesture and transition to an object control state in which changes in the wrist location data and/or the physiological data are configured to control a movement of the object. In the object control state, the system may be configured to detect a first motion of a body part, generate a first command to move the object in a first command direction, detect a second motion of the body part, and generate a command to move the object in a second command direction. The system may detect a second gesture indicating an intention to cease control of the object, and transition out of the object control state.

Abstract: Among other things, a user interface device has a sensor configured to detect, at a wrist of a human, nerve or other tissue electrical signals associated with an intended contraction of a muscle to cause a rapid motion of a finger. An output provides information representative of the nerve or other tissue electrical signals associated with the intended contraction of the muscle to an interpreter of the information.

Abstract: Systems and methods for gesture-based control are provided. A system may include a wearable device comprising a plurality of biopotential channels and a location sensor. The system may be configured to generate a data stream and classify a gesture based on an analysis of an analytical segment. The gesture classification may include (a) determining that a first portion of the analytical segment shows a signal parameter at a baseline; (b) determining that a second portion of the analytical segment shows the signal parameter satisfying a first threshold condition; (c) determining that a third portion of the analytical segment shows the signal parameter satisfying a second threshold condition; (d) determining that a time between the second portion and the third portion is greater than a threshold; and (e) while the signal parameter satisfies the first and/or second threshold condition, detecting a change in location of the wearable device.

Abstract: Bio-potentials are sensed on the skin of a subject. The bio-potentials include muscle bio-potentials, and nerve bio-potentials. Skin sensors are positioned to enable the sensing circuitry to emphasize the nerve bio-potentials and deemphasize the muscle bio-potentials in processed bio-potential signals generated by the sensing circuitry. A machine learning component identifies control sequences or tracks body motions based on the processed bio-potential signals.

Abstract: System and methods for gesture-based control are described. In some embodiments, a system may include a wearable device configured to be worn at a person's wrist. The wearable device may include a biopotential sensor and a wrist motion sensor. The system may be configured to determine that the person performed an initial gesture based on biopotentials detected by the biopotential sensor. The system may be configured to determine that the person performed a supplemental gesture based on at least the wrist motion data obtained by the wrist motion sensor. The system may be further configured to generate a command to be executed by a responsive device based on the combination of at least the initial gesture and the supplemental gesture.

Abstract: Systems and methods for gesture-based control are provided. In some embodiments, a system may include a wearable device configured to be worn on a person's wrist. The wearable device may include a plurality of biopotential channels, a location sensor, and a processor. The system may be configured to generate a data stream based on the outputs from the biopotential channels and/or the location sensor. The system may be configured to enter a first state in which the output from the location sensor is processed according to a first set of logical rules. The system may be configured to classify a gesture, and, based on the gesture classification, transition to a second state in which the output from the location sensor is processed according to a second set of logical rules that is different than the first set of logical rules.

Abstract: Systems and methods for gesture-based control are described. In some embodiments, a system may include a device configured to be worn at a person's wrist. The wearable device may include a biopotential sensor, a wrist location sensor, and a wireless transmitter. The system may have a first state and a second state. In the first state, the system may be configured to classify first data based on an output from the wrist location sensor to detect a wake word gesture. In the second state, the system may be configured to classify second data to detect a second gesture, the second data being based on both wrist location data and biopotential data. The system may be configured to transition from the first state to the second state based, at least in part, on a detection of the wake word gesture.

Abstract: Systems and methods for gesture-based control are provided. In some embodiments, a system may include a wearable device configured to be worn on a person's wrist. The wearable device may include a plurality of biopotential channels, a location sensor, and a processor. The system may be configured to generate a data stream based on the outputs from the biopotential channels and/or the location sensor. The system may be configured to enter a first state in which the output from the location sensor is processed according to a first set of logical rules. The system may be configured to classify a gesture, and, based on the gesture classification, transition to a second state in which the output from the location sensor is processed according to a second set of logical rules that is different than the first set of logical rules.

Abstract: Systems and methods for selecting a target are provided. In some embodiments, a system may include a wearable device having one or more sensors. The sensors may be configured to detect physiological data and wrist location data. In some embodiments, the system may be configured to determine: (i) a vector intended by a user based on at least the wrist location data, and (ii) a gesture indicating an intention to make a selection based on at least the physiological data. The system may be configured to select a target indicated by the directional vector as determined when the gesture indicating the intention to make a selection is detected.

Abstract: Among other things, a received inbound message is presented to a person wearing a wearable device. The inbound message is presented to the person as perceptible stimulation at the skin of the person. Monitoring is done for presence of an outbound message derived from biopotential signals sensed at the skin of the person after the receipt of the inbound message.

Abstract: Systems and methods for gesture-based control are described. In some embodiments, a system may include a device configured to be worn at a person's wrist. The wearable device may include a biopotential sensor, a wrist location sensor, and a wireless transmitter. The system may have a first state and a second state. In the first state, the system may be configured to classify first data based on an output from the wrist location sensor to detect a wake word gesture. In the second state, the system may be configured to classify second data to detect a second gesture, the second data being based on both wrist location data and biopotential data. The system may be configured to transition from the first state to the second state based, at least in part, on a detection of the wake word gesture.

Abstract: A user interface device includes at least a biopotential sensor and a location sensor. The user interface device is constructed to be worn by a person. A responsive device, such as a computer, receives data based on the outputs from the biopotential sensor and the location sensor, and performs actions based on the received data. Primitive gestures detected in the received data are associated with inputs of an operating system of the responsive device. For a wrist-worn device, a primitive gesture can be based on a pose of the hand or location of a wrist or both. The association of primitive gestures with inputs of the operating system can include associating primitive gestures with mouse inputs, inputs to request launching an application or switching applications, or inputs to perform other operations.

Abstract: System and methods for gesture-based control are described. In some embodiments, a system may include a wearable device configured to be worn at a person's wrist. The wearable device may include a biopotential sensor and a wrist motion sensor. The system may be configured to determine that the person performed an initial gesture based on biopotentials detected by the biopotential sensor. The system may be configured to determine that the person performed a supplemental gesture based on at least the wrist motion data obtained by the wrist motion sensor. The system may be further configured to generate a command to be executed by a responsive device based on the combination of at least the initial gesture and the supplemental gesture.