A wearable Haptic Human Machine Interface (HHMI) receives electrical activity from muscles and nerves of a user. An electrical signal is determined having characteristics based on the received electrical activity. The electrical signal is generated and applied to an object to cause an action dependent on the received electrical activity. The object can be a biological component of the user, such as a muscle, another user, or a remotely located machine such as a drone. Exemplary uses include mitigating tremor, accelerated learning, cognitive therapy, remote robotic, drone and probe control and sensing, virtual and augmented reality, stroke, brain and spinal cord rehabilitation, gaming, education, pain relief, entertainment, remote surgery, remote participation in and/or observation of an event such as a sporting event, biofeedback and remotality. Remotality is the perception of a reality occurring remote from the user. The reality may be remote in time, location and/or physical form. The reality may be consistent with the natural world, comprised of an alternative, fictional world or a mixture of natural and fictional constituents.

Provided is an image display device used by being mounted to a head or a face of a user, including a first display unit that displays an internal image seen from a side of the user, a second display unit that displays an external image seen from outside the image display device, and a control unit that controls display of the internal image and the external image.

A myoelectric sensor for detecting myoelectric signals which accompany body movement includes: a wearing band that is elastic, expandable, and circular, and that is worn around a limb to surround the limb tightly; myoelectric detection units a plurality of which are disposed in the circumferential direction on the wearing band with intervals therebetween so as to cause each of a plurality of myoelectric detection electrodes to be in close contact with the surface of the limb, and which detect myoelectric signals from corresponding positions on the limb using the myoelectric detection electrodes; and connection cables that electrically connect mutually adjacent myoelectric detection units and thereby transmit the myoelectric signals. The connection cables each include a bent portion, the bent shape of which changes in response to changes in the distance between the mutually adjacent myoelectric detection units.

An electronic device that includes an electronic calendar containing scheduled events, the device further including a) software that matches an event with an optimal brain state, and b) means for convening to the user of the device such optimal brain state when the calendar indicates that the event is imminent or has arrived.

A method of continuous decoding of motion for a direct neural interface. The method of decoding estimates a motion variable from an observation variable obtained by a time-frequency transformation of the neural signals. The observation variable is modelled using a HMM model whose hidden states include at least an active state and an idle state. The motion variable is estimated using a Markov mixture of experts where each expert is associated with a state of the model. For a sequence of observation vectors, the probability that the model is in a given state is estimated, and from this a weighting coefficient is deduced for the prediction generated by the expert associated with this state. The motion variable is then estimated by combination of the estimates of the different experts with these weighting coefficients.

Biometric identification methods and apparatuses (including devices and systems) for uniquely identifying one an individual based on wearable garments including a plurality of sensors, including but not limited to sensors having multiple sensing modalities (e.g., movement, respiratory movements, heart rate, ECG, EEG, etc.).

The present application discloses various methods and apparatuses for determining a head movement, wherein a method for determining a head movement disclosed comprises: acquiring, in response to a head movement of a human body, brain electricity detection information of a human body; and determining the head movement corresponding to the brain electricity detection information. The present application provides a new solution for head movement recognition, by which accuracy of head movement recognition is improved.

Disclosed is a wearable device including a sensor array having a plurality of sensors each configured to detect a physical change in epidermis of a corresponding body area; and a body motion determination unit configured to determine movement of a body part based on sensing signals from the plurality of sensors, and determine whether the determined movement corresponds to one of at least one next motion which is able to be derived from a current motion state.

A system, method and apparatus for detecting facial expressions according to EMG signals.

A system for delivering sensory stimulation comprises a sensor configured to measure brain activity information of a patient during a sleep session; a sensory stimulator configured to deliver sensory simulation to the patient during the sleep session; and a computer system. One or more physical processors are programmed with computer program instructions which, when executed cause the computer system to: determine a first stimulation profile, a second stimulation profile, or a combination stimulation profile thereof based on obtained sleep cycle information and/or obtained cognitive domain information; and provide input to the sensory stimulator based on the determined stimulation profile, the provided input causing the sensory stimulator to deliver the sensory simulations to the patient based on the determined stimulation profile during the detected slow wave sleep in the patient.