Provided is a cognitive function testing system capable of efficiently and objectively measuring cognitive functions related to, for example, ADHD and easily collecting detailed data. In addition, a cognitive function estimation system is provided to enable estimating and determining the probability of an individual having a disorder such as ADHD after the cognitive functions related to, for example, ADHD have been efficiently and objectively measured. In contrast to the conventional Stroop interference test that uses paper, one problem is displayed on one screen, and not only the correctness result of the problem for the test subject, but also coordinate information for when the test subject responds by manipulating a touch panel display, are recorded in a problem answer table. Furthermore, an estimation calculation based on a learning algorithm can be used to estimate the degree of cognitive function of the test subject.

Accurate peak detection in physiological signals is fundamental for several tasks related to health monitoring. A method for fine-tuning candidate peak positions and detecting peaks of interest in signals is provided. The fine-tuning method addresses the problem of low signal resolution and reduces the error with respect to the gold-standard reference signal usually collected at higher sampling frequencies. Obtaining accurate peak positions without modifying the sampling frequency is essential in the context of wearable devices, which often present limited computational resources and storage. Furthermore, the method enables selection of the peaks of interest by classifying their tuned positions according to a set of features extracted from morphological characteristics of the signal. The present pipeline is illustrated through inter-beat interval (IBI) estimation from wrist-PPG signals collected from smartwatches. The method may also be suited to the refinement and detection of different fiducial points, including peaks and valleys of interest.

Accurate peak detection in physiological signals is fundamental for several tasks related to health monitoring. A method for fine-tuning candidate peak positions and detecting peaks of interest in signals is provided. The fine-tuning method addresses the problem of low signal resolution and reduces the error with respect to the gold-standard reference signal usually collected at higher sampling frequencies. Obtaining accurate peak positions without modifying the sampling frequency is essential in the context of wearable devices, which often present limited computational resources and storage. Furthermore, the method enables selection of the peaks of interest by classifying their tuned positions according to a set of features extracted from morphological characteristics of the signal. The present pipeline is illustrated through inter-beat interval (IBI) estimation from wrist-PPG signals collected from smartwatches. The method may also be suited to the refinement and detection of different fiducial points, including peaks and valleys of interest.

An instrumentation amplifier that includes input capacitance cancellation is provided. The architecture includes programmable capacitors between the input stage and a current feedback loop of the instrumentation amplifier to cancel input capacitances from electrode cables and a printed circuit board at the front end. An on-chip calibration unit can be employed to calibrate the programmable capacitors and improve the input impedance.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

This invention relates to a device for humidifying a textile electrode (1) comprising a first layer (3); a second layer (5); and a material capable of absorbing and retaining water (4); wherein the material capable of absorbing and retaining water (4) is located between the first layer (3) and the second layer (5); the first layer (3) is impermeable to liquid water and water vapour; and the second layer (5) is permeable to liquid water in a direction extending inwards towards the material capable of absorbing and retaining water, and is impermeable to liquid water and permeable to water vapour in the opposite direction thereto. This invention further relates to a system comprising such a humidification device.

A computer-implemented method for detecting pathological brain activity patterns from a scalp electroencephalographic signal, the method including the steps of obtaining (A) an electroencephalographic signal as a function of multiple channels and time; identifying (C), for each channel, the zero-crossings of the electroencephalographic signal over a fixed threshold; generating a zero-crossing representation of at least a segment of the obtained electroencephalographic signal with the identified zero-crossings; obtaining (D) a reference family of real functions of time and channels from a zero-crossing statistical analysis of zero-crossing representation of pre-recorded electroencephalographic signals; calculating (E) a matching score by comparing the zero-crossing representation of a segment of the electroencephalographic signal with at least one reference function from the reference family of functions; and computing the matching score as a function of time by sliding the at least one reference function from the reference family of functions over the electroencephalographic signal.

A neuromodulation system for treatment of physiological disorders. The system includes one or more stimulators for stimulating one or more cranial nerves; one or more detectors configured for detecting a predetermined physiological state; and a control unit that controls nerve stimulation by the one or more stimulators so that it is synchronized with the at least one predetermined physiological state detected by the one or more detectors. A method of neuromodulating a patient for treatment of physiological disorder. The method includes the steps of detecting a predetermined physiological state and applying stimulation to one of the cranial nerves during the predetermined physiological state by one or more stimulators of a neuromodulation system.

The present disclosure pertains to a system configured to detect slow wave sleep and/or non-slow wave sleep in a subject during a sleep session based on a predicted onset time of slow wave sleep and/or a predicted end time of slow wave sleep that is determined based on changes in cardiorespiratory parameters of the subject. Cardiorespiratory parameters in a subject typically begin to change before transitions between non-slow wave sleep and slow wave sleep. Predicting this time delay between the changes in the cardiorespiratory parameters and the onset and/or end of slow wave sleep facilitates better (e.g., more sensitive and/or more accurate) determination of slow wave sleep and/or non-slow wave sleep.