A method and a wearable device are provided. The method includes providing a swimming mode in the wearable device, and storing standard swimming stroke data that have been collected in advance as corresponding template data, when a monitoring process starts, activating the swimming mode according to an instruction given by a user who will immediately enter water, and after the swimming mode has been activated, controlling a sensor to collect swimming stroke data of the user; obtaining test data for identifying a swimming state of the user from the swimming stroke data; and matching the test data with each template data, when the test data successfully matches the template data, identifying the swimming state of the user to be the swimming state that corresponds to the template data.

Apparatus and methods for monitoring electrical activity within the brain of a person (“brainwaves”) employing electrodes or other sensors placed proximate to portions of the body below the head to develop raw signals without physically touching the body and penetrating hair and clothing. Additionally, apparatus and methods for monitoring electrical activity within the brain of a person (“brainwaves”) employing non-contacting sensors placed proximate to portions of the head to develop raw signals. The raw signals are filtered to produce analysis signals including frequency components relevant to brain electrical activity while attenuating unrelated frequency components. The apparatus and methods can be used for biofeedback-based attention training, human performance training, gaming, biometrics, cognitive state detection, and relaxation training. Either wired or wireless signal connections are made to electronic circuitry, typically including a digital computer, for performing signal processing and analysis functions.

Computing device enhanced training environment system comprising a computing device, I/O subsystem for permitting a user to enter at least one attribute of the training or of the trainee, a plurality of sensors for generating sensory information, a training environment in which a training activity takes place, a database containing training related information. The computing device enhanced training environment system configured for at least one of the following: design a training program for a plurality of users, monitor training program performance, monitor training performance, instruct a user about the training, determine and/or set difficulty level in training apparatus.

A machine-implemented method for automated detection of drowsiness, which includes receiving from an imaging device directed at the face of an operator a series of images of the face of the operator onto processing hardware, on the processor detecting facial landmarks of the operator from the series of images to determine the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator, on the processor detecting the facial pose of the operator from the series of images to determine the level of gaze fixation by the operator, on the processor calculating the level of drowsiness of the operator by ensembling the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator and the level of gaze fixation by the operator, and generating an alarm when the calculated level of drowsiness of the operator exceeds a predefined value.

A method, system, and/or apparatus for automatically monitoring for possible infection or other physical health concerns, such as from Covid-19. The method or implementing software application uses or relies upon location information available on the mobile device from any source, such as cell phone usage and/or other device applications. The method and system automatically uses and/or learns user location and activity patterns and determines and infection risk that can be communicated as a warning to community members.

A method, performed by a wearable device, of providing haptic feedback to a user is provided. The method includes obtaining profile data of the user, obtaining biometric data of the user by using one or more biosensors, calculating, based on the profile data and the biometric data of the user, a target contact pressure to be applied to a body of the user by one or more haptic actuators, measuring a current contact pressure applied to the body of the user by the one or more haptic actuators by using one or more pressure sensors, and adjusting the current contact pressure of the one or more haptic actuators based on the current contact pressure and the target contact pressure.

An apparatus for determining a non-apparent attribute of an object having a sensor portion with which the object makes contact and to which the object applies pressure. The apparatus has a computer in communication with the sensor portion that receives signals from the sensor portion corresponding to the contact and pressure applied to the sensor portion, and determines from the signals the non-apparent attribute. The apparatus has an output in communication with the computer that identifies the non-apparent attribute determined by the computer. A method for determining a non-apparent attribute of an object.

An apparatus for promoting vascular circulation, including a garment configured to at least partially surround an anatomical structure of a patient. A compression element is coupled to the garment and configured to compress at least a portion of the anatomical structure when the compression element is actuated. A controller is configured to selectively actuate the compression element over a plurality of cycles. Each cycle has an actuated time during which the compression element is arranged to exert a first pressure and an unactuated time during which the compression element is arranged to exert a second pressure different than the first pressure, and the controller is configured to use a random value in determining the deflated time of one or more of the cycles.

A method and system for heterogeneous event detection. Sensor data is obtained and divided into discrete data windows. Each data window is defined by and corresponds to a time period of the sensor data. A time-frequency representation over the time period is calculated for each data window. A filter mask is calculated based on the data window corresponding to the time-frequency representation. The filter mask is applied for reverting the time-frequency representation to a time representation, resulting in filtered data. Features, such as extrema or other inflection points, are identified in the filtered data. The features define events, and transforming the time-frequency representation back into the time domain emphasizes differences between more and less prominent frequencies, facilitating identification of heterogeneous events. The method and system may be applied to body movements of people or animals, automaton movement, audio signals, light intensity, or any suitable time-dependent variable.

A system for reducing a kinetosis effect in at least one passenger of a vehicle comprises at least one set of headphones having two loudspeakers and at least one first ear bud, wherein the at least one set of headphones is designed, at least by means of a sensor device integrated in the first ear bud, to detect the kinetosis effect in the auditory canal of the respective passenger via measurement of the body temperature and to provide acoustic signals by means of the two loudspeakers in order to reduce the kinetosis effect of the passenger depending on the kinetosis effect detected. Forces acting on the passenger and their countenance can also be measured.