A method is provided, performed by a wearable computing device comprising at least one bio-signal measuring sensor, the at least one bio-signal measuring sensor including at least one brainwave sensor, comprising: acquiring at least one bio-signal measurement from a user using the at least one bio-signal measuring sensor, the at least one bio-signal measurement comprising at least one brainwave state measurement; processing the at least one bio-signal measurement, including at least the at least one brainwave state measurement, in accordance with a profile associated with the user; determining a correspondence between the processed at least one bio-signal measurement and at least one predefined device control action; and in accordance with the correspondence determination, controlling operation of at least one component of the wearable computing device, such as modifying content displayed on a display of the wearable computing device. Various types of bio-signals, including brainwaves, may be measured and used to control the device in various ways.

Aspects of the present disclosure provide a method for obtaining biological information associated with a user, comprising receiving electrical signals via a first electrode on an ear tip of an earpiece inserted in an ear of the user, receiving electrical signals via a second electrode on an external portion of the earpiece, and deriving an electrocardiogram (ECG) based on the signals received via the first electrode and the second electrode. Aspects also provide a method for determining a pulse travel time (PTT) associated with a user, comprising obtaining a proximal signal using an earpiece inserted in of the user, obtaining a distal signal using the earpiece, and deriving the PTT based on the obtained proximal signal and the obtained distal signal.

To reduce errors in determining a degree of arousal due to variations in blinking among an individual or between individuals.

To execute the steps of: acquiring first biological information related to an ocular potential of a user from a processing device worn by the user; and calculating a degree of arousal of the user based on a distance between a projection axis parallel to an equal degree of arousal line and a point where the first biological information is plotted in a coordinate space where a height and width are the axes for an ocular potential peak.

Hat, helmet, and other headgear apparatus includes dry electrophysiological electrodes and, optionally, other physiological and/or environmental sensors to measure signals such as ECG from the head of a subject. Methods of use of such apparatus to provide fitness, health, or other measured or derived, estimated, or predicted metrics are also disclosed.

Hat, helmet, and other headgear apparatus includes dry electrophysiological electrodes and, optionally, other physiological and/or environmental sensors to measure signals such as ECG from the head of a subject. Methods of use of such apparatus to provide fitness, health, or other measured or derived, estimated, or predicted metrics are also disclosed.

A system and method for determining parameters of stimulation electrical signals for vagus nerve stimulation is discussed. Initial parameters of the signals are selected to provide reliable response to stimulation in physiological measurements of a subject. One or more physiological and neurological indices are determined based on a vagus nerve response model. For a selected vagus nerve activation, the electrical parameters of the signals are varied while monitoring changes in physiological parameters and values of the indices. The electrical parameters are varied until desired response in the physiological measurements and the values of the indices is observed. The electrical parameters are then stored as preferred parameters and can be used to activate the selected vagus nerve of the subject.

Embodiments in accordance with the present disclosure are directed to methods and apparatuses used for slow wave activity (SWA) optimization. An example method includes receiving one or more bio-signals from a user and classifying sleep stages by processing the bio-signals. The method further include determining dominant peripheral nervous system (PNS) oscillations based on the bio-signals and as a function of time and stage of sleep, and characterizing at least one property of the dominant PNS oscillations, including a phase, a phase shift, an amplitude, and/or frequency. The method further include providing an indication of an optimal window for maximizing SWA generation based on the phase, the phase shift, the amplitude, or the frequency. The indication is provided to stimulation circuitry that delivers stimulation to the user within the optimal window. Feedback is provided responsive to the stimulation based on an EEG signal of the user.

Embodiments in accordance with the present disclosure are directed to methods and apparatuses used for slow wave activity (SWA) optimization. An example method includes receiving one or more bio-signals from a user and classifying sleep stages by processing the bio-signals. The method further include determining dominant peripheral nervous system (PNS) oscillations based on the bio-signals and as a function of time and stage of sleep, and characterizing at least one property of the dominant PNS oscillations, including a phase, a phase shift, an amplitude, and/or frequency. The method further include providing an indication of an optimal window for maximizing SWA generation based on the phase, the phase shift, the amplitude, or the frequency. The indication is provided to stimulation circuitry that delivers stimulation to the user within the optimal window. Feedback is provided responsive to the stimulation based on an EEG signal of the user.

Device and method for determining an efficacy of chronic pain treatment including providing a first set of at least one stimulus to a subject, obtaining first measurements of at least two physiological parameters in response to the first set of at least one stimulus, providing chronic pain treatment to the subject, providing a second set of at least one stimulus to the subject, obtaining second measurements of the at least two physiological parameters in response to the second set of at least one stimulus; and determining an efficacy of the chronic pain treatment by applying a classification algorithm on the first and second measurements of the at least two physiological parameters.

Systems and methods include a cellular, WiFi, and Bluetooth transceiver coupled to a processor; an accelerometer or a motion sensor coupled to the processor; and a sensor coupled to the processor to sense mood or body vital sign.