A symptom intervention system monitors data representative of a user's movement, identifies an onset of a symptom of a physical condition, and applies an actuation to intervene with the identified onset. A machine-learned model is trained to identify an onset of a symptom based on the monitored data . The system may use the machine-learned model to determine whether to modify an upcoming administration of a chemical stimulus that is administered to the user to treat their physical condition. The system may determine a modification to a dose or a time associated with the upcoming administration of the stimulus and apply the stimulus to the user based on the determined modification. The system may use the machine-learned model to determine that the user is exhibiting a particular symptom of their physical condition. Depending on the symptom, the system may depolarize or hyperpolarize neurons of the user.

A symptom intervention system monitors data representative of a user's movement, identifies an onset of a symptom of a physical condition, and applies an actuation to intervene with the identified onset. A machine-learned model is trained to identify an onset of a symptom based on the monitored data . The system may use the machine-learned model to determine whether to modify an upcoming administration of a chemical stimulus that is administered to the user to treat their physical condition. The system may determine a modification to a dose or a time associated with the upcoming administration of the stimulus and apply the stimulus to the user based on the determined modification. The system may use the machine-learned model to determine that the user is exhibiting a particular symptom of their physical condition. Depending on the symptom, the system may depolarize or hyperpolarize neurons of the user.

A symptom intervention system monitors data representative of a user's movement, identifies an onset of a symptom of a physical condition, and applies an actuation to intervene with the identified onset. A machine-learned model is trained to identify an onset of a symptom based on the monitored data . The system may use the machine-learned model to determine whether to modify an upcoming administration of a chemical stimulus that is administered to the user to treat their physical condition. The system may determine a modification to a dose or a time associated with the upcoming administration of the stimulus and apply the stimulus to the user based on the determined modification. The system may use the machine-learned model to determine that the user is exhibiting a particular symptom of their physical condition. Depending on the symptom, the system may depolarize or hyperpolarize neurons of the user.

An apparatus for measuring patient data includes a frame having a plurality of electrode hubs. Each hub can include one or more electrode members. The frame can be configured to receive a head of a patient. Each of the electrode hubs can have a single electrode member or a plurality of electrode members that extend from or are connected to an outer member for contacting a scalp of the head of the patient. The outer member can have at least one circuit configured to transmit data received by at least one of the electrode members to a measurement device via a wireless communication connection (e.g. Bluetooth, near field communication, etc.) or a wired communication connection.

A measurement device includes a biosensor that acquires biological information, a pressing force detection component that detects a pressing force produced when the biosensor makes contact with a part of a living body to be measured, and a processor that converts the biological information to a first measurement value, calculates a second measurement value by correcting the first measurement value based on the pressing force, and outputs the second measurement value.

A measurement device includes a biosensor that acquires biological information, a pressing force detection component that detects a pressing force produced when the biosensor makes contact with a part of a living body to be measured, and a processor that converts the biological information to a first measurement value, calculates a second measurement value by correcting the first measurement value based on the pressing force, and outputs the second measurement value.

Measurements of an arbitrary magnetic field having one or more magnetic field components are acquired from a plurality of magnetometers, and a generic model of at least one of the one or more magnetic field components of the arbitrary magnetic field is generated in the vicinity of the magnetometers. The generic magnetic field model comprises an initial number of different basis functions. Maxwell's equations are applied to the generic magnetic field model to reduce the initial number of different basis functions, thereby yielding a Maxwell-constrained model of the magnetic field component(s) of the arbitrary magnetic field, and the magnetic field component(s) of the arbitrary magnetic field are estimated at each of at least one of the magnetometers based on the constrained magnetic field model and the arbitrary magnetic field measurements acquired from each magnetometer.

Multilayer electrodes, electrode systems, and stimulation systems are disclosed. An electrode may include a conductive layer with a unitary tail, a connector disposed on a distal end of the tail, and a nonconductive top layer disposed along a top portion of the conductive layer. An electrode may include a magnetic lead connector socket, or a receptacle formed by a depression in the conductive layer configured to receive a male connector. An electrode system may include a plurality of conductive zones and a plurality of connectors. A stimulation system may include an electronics layer in electrical contact with a conductive layer via a puncture connection, and may provide an iontophoretic treatment followed by a TENS treatment. Other electrodes, systems and methods are also disclosed.

A pulse transit time measurement device according to an aspect includes: a belt unit; a plurality of first electrodes and second electrodes provided on the belt unit; a third electrode provided on the belt unit; a first electrocardiographic signal acquisition unit that acquires a first electrocardiographic signal of a user using the plurality of first electrodes; a second electrocardiographic signal acquisition unit that acquires a second electrocardiographic signal of the user with the second electrode and the third electrode; a feature amount parameter calculation unit that calculates a feature amount parameter related to a waveform feature point of the first electrocardiographic signal on the basis of a waveform feature point of the second electrocardiographic signal; a pulse wave signal acquisition unit that acquires a pulse wave signal representing a pulse wave of the user; and a pulse transit time calculation unit that detects a waveform feature point.

An electrode apparatus is applicable on a skin with hair of a mammal for measuring an electrical bio-signal. The electrode apparatus comprises cylindrical chambers, each of which comprises a wall, which forms a cavity within the cylindrical chambers, a roof at a first end of each of said cylindrical chambers, a second end of said cylindrical chambers opposite to the first end being open, and at least one electrode. An elongated structure is located within each of the cylindrical chambers, and comprises a first portion parallel to a central axis of a cylindrical chamber within which it is. A first end of the elongated structure, the first end of the elongated structure belonging to the first portion, is attached to the roof. At least one second portion, each comprising a second end opposite to the first end, deviates from a direction of the central axis of a cylindrical chamber within which it is. The elongated structure rotatable in order to bundle hair when applied to the mammal so as to improve a contact of the electrode with the skin of the mammal.