The present disclosure pertains to a system and method for determining sleep stages during individual sleep cycles based on algorithms and/or parameters that correspond to the individual sleep cycles. The system enables more accurate real-time sleep stage determinations compared to prior art systems. Sleep cycles are detected in real-time based on an electroencephalogram (EEG), and/or by other methods. At the end of a sleep cycle, the system is configured such that the specific algorithms and/or parameters used for the previous sleep cycle to determine sleep stages are replaced by new ones which are specifically adapted for the next sleep cycle.

A fault detection device includes at least one electricity generating unit, to impress a signal on a first useful signal path; at least one first comparison unit, to determine if the signal of the first useful signal path lies within a measuring range; and at least one first interference signal path, designed as a current measurement path, for current-detecting measurement of a first interference signal. A signal path defect analysis unit, is included to detect a signal path defect, upon the impressed signal not being measured on the at least one first interference signal path and upon the checked signal of the comparison unit being determined to lie within the measuring range. Furthermore, corresponding methods are for the detection of signal path defects in a voltage measuring system for measuring bioelectric signals are defined.

A fault detection device includes at least one electricity generating unit, to impress a signal on a first useful signal path; at least one first comparison unit, to determine if the signal of the first useful signal path lies within a measuring range; and at least one first interference signal path, designed as a current measurement path, for current-detecting measurement of a first interference signal. A signal path defect analysis unit, is included to detect a signal path defect, upon the impressed signal not being measured on the at least one first interference signal path and upon the checked signal of the comparison unit being determined to lie within the measuring range. Furthermore, corresponding methods are for the detection of signal path defects in a voltage measuring system for measuring bioelectric signals are defined.

A method of treating a neurological disorder and/or disease includes positioning a stimulation apparatus on a patient. The stimulation apparatus includes an electrode array having a plurality of electrodes and an emitter array having a plurality of emitters. The method further includes measuring electroencephalography (EEG) signals of the patient with the electrode array. The method further includes emitting radiation into the patient's brain from the emitter array based on the measured EEG signals in order to treat the neurological disorder and/or disease.

Described is a system for decoding and validating memory consolidation. During operation, the system receives electroencephalographic (EEG) data while a subject is performing a specific task. Nuisance signals are then removed from the EEG data, resulting in a nuisance free signal. Skill feature vectors are generated from the nuisance free signal using time-invariant feature extraction. A skill classifier can then be trained for the specific task based on the skill feature vectors to generate a subject specific model regarding a memory replay for the specific task. Finally, electrodes in a neural cap are activated based on the memory replay.

Described is a system for decoding and validating memory consolidation. During operation, the system receives electroencephalographic (EEG) data while a subject is performing a specific task. Nuisance signals are then removed from the EEG data, resulting in a nuisance free signal. Skill feature vectors are generated from the nuisance free signal using time-invariant feature extraction. A skill classifier can then be trained for the specific task based on the skill feature vectors to generate a subject specific model regarding a memory replay for the specific task. Finally, electrodes in a neural cap are activated based on the memory replay.

A wearable monitoring device includes a band configured to at least partially encircle a portion of the body of a subject and at least one optical emitter and at least one optical detector attached to the band. The band includes a generally cylindrical outer body portion and a generally cylindrical inner body portion secured together in concentric relationship. The inner body portion includes light transmissive material and has outer and inner surfaces. A layer of cladding material is near the inner body portion inner surface, and a plurality of windows are formed in the cladding material that each serve as a light-guiding interface to the body of the subject. The plurality of windows are circumferentially spaced apart from each other.

A wearable monitoring device includes a band configured to at least partially encircle a portion of the body of a subject and at least one optical emitter and at least one optical detector attached to the band. The band includes a generally cylindrical outer body portion and a generally cylindrical inner body portion secured together in concentric relationship. The inner body portion includes light transmissive material and has outer and inner surfaces. A layer of cladding material is near the inner body portion inner surface, and a plurality of windows are formed in the cladding material that each serve as a light-guiding interface to the body of the subject. The plurality of windows are circumferentially spaced apart from each other.

A method, comprising receiving a time series of patient body signal, determining first and second sliding time windows for the time series; applying an autoregression algorithm, comprising: applying an autoregression analysis to each of the first and second windows, yielding autoregression coefficients and a residual variance for each window; estimating a parameter vector for each window based on the autoregression coefficients and residual variances; and determining a difference between the parameter vectors; and determining seizure onset and seizure termination based on the difference between the parameter vectors. A non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

Methods and apparatuses are described for modulating multiple integrated neural networks to alter composite sensory processes, such as audition or hearing. These methods and apparatuses may be used for therapeutic and non-therapeutic uses, including enhancing entertainment and communication, by providing a cranio-cervical tuning apparatus worn in or around the outer ear or auricle. These methods and apparatuses may include functional neurosensory bias for neurosensory scrambling neuromodulation to influence composite or multi-modal sensory processes.