Abstract: An electrode assembly can include a reservoir defining a plurality of openings on a first surface of the reservoir, a wicking material extending through one or more of the plurality of openings, and a conductive terminal. An electrode assembly can include a reservoir cap, a reservoir bottom configured to fit to the reservoir cap and define a reservoir therewith, an electrode disposed within the reservoir, and a wicking element in electrical communication with the electrode and configured to absorb a fluid, wherein at least a portion the wicking element is configured to protrude from the reservoir bottom.

Abstract: Devices disclosed according to various embodiments use one or more arrays of atomic magnetometers to detect biologically derived magnetic fields. The disclosed devices and methods relate to application of utilization of a magnetic sensor with unique properties requiring changes in design, allowing new functions, and requiring alternative analysis methodologies. Various embodiments are also directed to methods for obtaining and processing biological magnetic signals. These methods may take advantage of the unique spatial arrangement of the atomic magnetometers and the capacity sensors to he used in either a scalar or a vector mode. Various embodiments have advantages over current magnetometer arrays for the purpose of detecting biological magnetic fields. Such advantages may include, for example: smaller size, lower power consumption, no necessity for cryogenic cooling, potential wafer-level fabrication, and/or the potential of better localization biological signals.

Abstract: An exemplary method for analyzing behavior of a system includes receiving dynamical measurement data regarding the system, applying a quadratically constrained quadratic 0-1 problem to identify data among the received data, and storing the identified data. An exemplary seizure warning method includes continuously calculating STLmax values, identifying critical sites by applying a quadratically constrained quadratic 0-1 solution to data (e.g. STLmax profiles) derived from pre-seizure onset and post-seizure onset EEG signals, monitoring a T-index curve of the identified critical sites, warning of an impending seizure, observing a seizure and then repeating the cycle by identifying critical sites using the new data, and then monitoring them.