44 results about "Sommeil paradoxal" patented technology

A sleep controlling apparatus includes a measuring unit that measures biological information of a subject; a first detecting unit that detects a sleeping state of the subject selected from the group consisting of a falling asleep state, a REM sleep state, a light non-REM sleep state and a deep non-REM sleep state, based on the biological information measured by the measuring unit; a first stimulating unit that applies a first stimulus of an intensity lower than a predetermined threshold value to the subject when the light non-REM sleep state is detected by the first detecting unit; and a second stimulating unit that applies a second stimulus of an intensity higher than the first stimulus after the first stimulus is applied to the subject.

Described are a positive airway pressure system and method for treatment of a sleeping disorder in a patient. The system includes a generator, a sensor and a processing arrangement. The generator supplies airflow and applies a pressure at to an airway of a patient. The sensor measures data corresponding to patient's breathing patterns. The processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of at least one of the following patient's states: (i) a regular breathing state, (ii) a sleep disorder breathing state, (iii) a REM sleep state and (iv) a troubled wakefulness state. The processing arrangement adjusts the applied pressure as a function of the patient's state.

A programmable alarm clock system, method of operation and program product therefor with sleep analysis to identify and wake a person during non-REM sleep patterns, resulting in less subsequent drowsiness and better day-to-day functioning. The programmable alarm clock system includes at least one brain activity sensor attachable to a head of a sleeper. Brain activity signals from the sensor(s) are sent to a receiver at a local computer. The user, before retiring inputs a wake up time and attaches the sensor(s). The local computer sends brain activity signals to a remotely connected sleep analyzing server which analyzes the brain activity and identifies REM sleep periods and non-REM sleep periods. The labeled brain activity periods are returned to the local computer which waits for the wake up time. Then, the local computer sets an alarm time by adjusting the wake up time to coincide with a non-REM sleep period, if necessary and if possible. At the alarm time, the local computer sends a trigger to a remotely triggered local alarm device such as a clock, which sounds an alarm to wake the user / sleeper.

To provide an adjustable bed that assists a user to turn comfortably in his or her sleep without mental stress. Once an automatic mode starts, measurement on the depth of sleep of the user lying on the bed is launched. The depth of sleep is measured by detecting biological information such as brain waves, heart rate, and respiratory rate of the user using electrode sensors or the like, and analyzing the biological information according to a polysomnography method or the like. If the depth of sleep is 0, i.e., the user is in REM sleep, and if one hour or more has passed since the measurement is launched or since an immediately preceding turn operation, a turn operation is performed to turn the user.

A diaphragm pacing stimulatory method and a system to implement the method are provided to improve respiratory function and the quality of sleep in patients whose sleep is compromised by poor respiration. The diaphragm pacing method includes adaptations that make it particularly compatible with the onset of sleep and sustaining sleep. Embodiments of the method are operated independently of breathing effort the patient may make during sleep. Patients for whom the invention is appropriate include those with a neuromuscular disease, such as amyotrophic lateral sclerosis (ALS). System elements include an external electrical stimulator coupled to one or more implanted electrodes that stimulate diaphragm contraction. The system and method provide for a pacing of the diaphragm, improved breathing, and improved sleep. Features of improved sleep include longer sleep time, an increased amount of REM sleep, and fewer episodes of wakefulness and restlessness.

Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor may access sensor data signals related to bodily movement and respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include variability of respiration rate or variability of respiration amplitude. A processor may then determine a sleep stage based on a combination bodily movement and respiration variability. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).

The present apparatus and method for using the same detects Rapid Eye Movement (REM) in a sleeping mammal and awakens the mammal after the cessation of a specific episode of REM. The system comprises an alarm setting unit for setting a predetermined wakeup time, a data collection unit for collecting physiological data from the mammal over time, a processing unit for determining the occurrence and cessation of REM and for providing a stimulation signal for awakening the mammal within a prescribed window of time before the predetermined wakeup time and after the cessation of REM and after the mammal's nadir in body temperature with respect to time.

Described is a system including a sensor and a processing arrangement. The sensor measures data corresponding to a patient's breathing patterns. The processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of a REM sleep state. In another embodiment, the processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of one of the following states: (i) a wake state and (ii) a sleep state. In another embodiment, a neural network analyzes the data to determine whether the breathing patterns are indicative of one of the following states: (i) a REM sleep state, (ii) a wake state and (iii) a sleep state. In another embodiment, the processing arrangement analyzes the data to determine whether the breathing pattern is indicative of an arousal.

The invention relates to a system and method for diagnosis and treatment of a breathing pattern of a patient. Described is a system including a sensor and a processing arrangement. The sensor measures data corresponding to a patient's breathing patterns. The processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of a REM sleep state. In another embodiment, the processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of one of the following states: (i) a wake state and (ii) a sleep state. In another embodiment, a neural network analyzes the data to determine whether the breathing patterns are indicative of one of the following states: (i) a REM sleep state, (ii) a wake state and (iii) a sleep state. In another embodiment, the processing arrangement analyzes the data to determine whether the breathing pattern is indicative of an arousal.

Provided are a histamine-H3 receptor antagonist; and a preventive and / or a remedy for metabolic system diseases such as obesity, diabetes, hormone secretion disorder, hyperlipemia, gout, fatty liver, circulatory system diseases, for example, stenocardia, acute / congestive cardiac insufficiency, cardiac infarction, coronary arteriosclerosis, hypertension, nephropathy, sleep disorder and various diseases accompanied by sleep disorder such as idiopathic hypersomnnia, repetitive hypersomnnia, true hypersomnnia, narcolepsy, sleep periodic acromotion disorder, sleep apnea syndrome, circadian rhythm disorder, chronic fatigue syndrome, REM sleep disorder, senile insomnia, night worker sleep insanitation, idiopathic insomnia, repetitive insomnia, true insomnia, electrolyte metabolism disorder, and central and peripheral nervous system diseases such as bulimia, emotional disorder, melancholia, anxiety, epilepsy, delirium, dementia, shinzophrenia, attention deficit / hyperactivity disorder, memory disorder, Alzheimer's disease, Parkinson's disease, sleep disorder, recognition disorder, motion disorder, paresthesia, dysosmia, epilepsy, morphine resistance, narcotic dependency, alcoholic dependency. The histamine-H3 receptor antagonist comprises a piperidine derivative compound of formula (I) [wherein X1 and X2 independently represent a nitrogen atom or CH; Y represents a specific group; X3 represents Os—(CH2)m; R1 and R2 independently represent a hydrogen atom, a halogen atom, a linear or branched lower alkyl group, a lower alkoxy group, or an acetyl group substituted with 2 or 3 fluorine atoms; s is 0 or 1; and m is an integer to make (m+s) 0 or from 1 to 4], or its pharmaceutically-acceptable salt.

The invention discloses a sleep stage recognition method based on audio processing. According to the method, intelligent equipment with functions of audio acquisition and processing is used and comprises a smartphone and a smartwatch, wherein an audio module is used as an audio acquisition device; numerical characteristics of acquired audio frequency are extracted, sleep related events (including snoring, trunk movement, coughing and odontoprisis) occurring during sleeping are recognized with a mode recognition method, external expression differences of people in the REM (rapid eyes movement) sleep stage and the N-REM (non-rapid-eyes movement) sleep stage are taken as entry points, and the sleep stage is recognized for sleep of people in combination with the external expression differences of people in the medical REM sleep stage and the medical N-REM sleep stage. The method has the advantages that the equipment is simple and easy to obtain, an equipment room and a server room for communication are not required, the method is non-invasive and the like, and the method can be widely applied to multiple application fields of daily sleeping monitoring, sleeping quality evaluation, living habit evaluation and the like.

The invention discloses a new use of bisbenzylisoquinoline compound shown in formula (I) or pharmaceutically acceptable salt thereof except for tetrandrine and fangchinoline. The use is application of the bisbenzylisoquinoline compound shown in formula (I) or pharmaceutically acceptable salt thereof in preparing a medicine or healthcare product for treating insomnia and improving sleep. The bisbenzylisoquinoline compound shown in formula (I) or pharmaceutically acceptable salt thereof can be used as an effective component and made into any dosage form. The result of animal experiment indicates that: the bisbenzylisoquinoline compound shown in formula (I) or pharmaceutically acceptable salt thereof can obviously prolong the total sleep time of normal rats and mouse, including REM (rapid eye movement) sleep time and NREM (non-rapid eye movement) sleep time. The application disclosed by the invention is suitable for various types of insomnia or sleep disorders.

A system and method determines from EEG signals the lack of awareness and the depth of anesthesia of a patient to whom an anesthetic agent is being administered. In particular, a log-log representation of the EEG power spectrum is converted to two intersecting lines so that the intersection point and the relative slopes can be analyzed to determine a state of awareness of a patient. This system and method may also be used in an analysis of the brain function of a sleeping individual to distinguish between different levels of non-REM sleep, REM sleep, and awakeness.

A physiological sensor apparatus comprises a physiological sensor, a headband and an eye mask. In one example, the physiological sensor includes a plurality of electroencephalography (EEG) electrodes that are used to sense a signal indicative of a sleep stage (e.g., REM sleep or non-REM sleep) of a user. Each end of the headband attaches to respective ends of the sensor and eye mask such that when the sensor is disposed on the forehead of the user, the eye mask shields the eyes of the user from visible light. The diameter of the headband is adjustable by the user to secure the sensor to the forehead of the user. The sensor accurately determines the sleep stages of the user over a period of sleep of the user because the adjustable headband and eye mask prevent the electrodes from being displaced from the forehead of the user during the period of sleep.

A sleep state determination apparatus includes: a measurement unit which measures biological information; and a determination unit which calculates a first index in accordance with an activity of a first autonomic nerve and a second index in accordance with an activity of a second autonomic nerve, based on the biological information which is measured by the measurement unit, derives first variation information which indicates a variation of the first index and a second variation information which indicates a variation of the second index, and determines whether a sleep state indicated by the biological information is REM sleep or non-REM sleep, based on the first variation information and the second variation information.

Described is a system including a sensor and a processing arrangement. The sensor measures data corresponding to a patient's breathing patterns. The processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of a REM sleep state. In another embodiment, the processing arrangement analyzes the breathing patterns to determine whether the breathing patterns are indicative of one of the following states: (i) a wake state and (ii) a sleep state. In another embodiment, a neural network analyzes the data to determine whether the breathing patterns are indicative of one of the following states: (i) a REM sleep state, (ii) a wake state and (iii) a sleep state. In another embodiment, the processing arrangement analyzes the data to determine whether the breathing pattern is indicative of an arousal.

A method of analysis is disclosed. The method comprises receiving a non-ECG signal indicative of heart beats of a sleeping subject; extracting from the signal a series of inter-beat intervals (IBI); calculating at least one Poincare parameter characterizing a Poincare plot of the IBI series; and using the Poincare parameter(s) to determine a REM sleep of the sleeping subject. In some embodiments, sleep stages other than REM sleep and / or wake stages are determined.