Abstract: An information display device includes a component extraction unit configured to extract a requested component from multiple given waveforms that are cut out of multiple signal waveforms based on biological signals that are detected; and a noise component selection unit configured to accept selecting, as a noise component, a result of the extracting from multiple results of the extracting by the component extraction unit, and the noise component selection unit displays the multiple results of the extracting by the component extraction unit and times at which the specific waveforms occur.

Abstract: A system and method for evaluation, detection, conditioning, and treatment of neurological functioning and conditions which uses data obtained while a person is engaged in simultaneously in a range of primary physical tasks combined with defined types of associative activity, such as listening, reading, speaking, mathematics, logic puzzles, navigation of a virtual environment, recall of past stimuli, etc. The data from the physical and associative activities are combined to generate a composite functioning score visualization indicating the relative functioning of areas aspects of neurological functioning; including those in which deficiencies may be present, which are early indicators of possible neurological conditions. Through algorithmic recommendations combined with expert and user input, a conditioning regimen targeting neurological aspects of interest paired with periodic testing allows the user to track their progress in these areas over time.

Abstract: This invention is a non-invasive Brain to Computer Interface (BCI) method for interpreting a word, phrase, or command from brain activity by identifying a pattern of electromagnetic brain activity which occurs when a person uses different action modalities to communicate a word, phrase, or command. This method can enable people with neuromuscular limitations and/or paralysis to communicate. It can also enable people to communicate and/or to control environmental devices via their thought patterns in situations where communication via touch screen, keyboard, mouse, voice command, or gesture recognition is not appropriate and/or possible.

Abstract: A pain measurement and diagnostic system (PMD) for bioanalytical analysis of pain matrix activity and the autonomic nervous system to diagnose and validate patient treatments, health status and outcomes to diagnose and validate patient treatments and outcomes. The PMD is implemented using medical devices for measuring and reporting objective measurements of pain through patient monitoring and analyzing related biological, psychological, social, environmental, and demographic factors that may contribute to and effect physiological outcomes for patients and through the analysis, improve diagnosis of pain, the evaluation of related disease states, and treatment options.

Abstract: An in-the-ear hearing aid device is disclosed. The device at least one electro-acoustic transducer, and at least one sensor or at least one active electronic component. The at least one electro-acoustic transducer comprises a capsule enclosing a transducer sound active part and a transducer air volume. The transducer air volume is air volume which is enclosed by said capsule and which is in fluid-connection with said transducer sound active part. At least a portion of said at least one sensor or of said at least one active electronic component is provided within said transducer air volume.

Abstract: A 3D model of AC electrical conductivity (at a given frequency) of an anatomic volume can be created by obtaining two MRI images of the anatomic volume, where the two images have different repetition times. Then, for each voxel in the anatomic volume, a ratio IR of the intensity of the corresponding voxels in the two MRI images is calculated. This calculated IR is then mapped into a corresponding voxel of a 3D model of AC electrical conductivity at the given frequency. The given frequency is below 1 MHz (e.g., 200 kHz). In some embodiments, the 3D model of AC electrical conductivity at the given frequency is used to determine the positions for the electrodes in TTFields (Tumor Treating Fields) treatment.

Abstract: There is provided herein a motion-based evaluation of reaction time that utilizes motion detection hardware of a mobile device to determine auditory and visual stimulated reaction time. In an embodiment, the subject holds a mobile computing device equipped with built-in triaxis accelerometer and gyroscope with both hands at arms length away from the face. A visual or auditory stimulus is then presented on screen via a software application that also records the response time for the individual to initiate a movement of the device. A simple reaction time test could include the movement of the device in any direction that exceeded a threshold of movement beyond what would be expected from static holding. An embodiment of a choice reaction time test would provide for specific directional movements as it related to an instructed stimulus.

Abstract: A method of distinguishing sleep period states that a person experiences during a sleep period, the method comprising: using a non-contact microphone to acquire a sleep sound signal representing sounds made by a person during sleep; segmenting the sleep sound signals into epochs; generating a sleep sound feature vector for each epoch; providing a first model that gives a probability that a given sleep period state experienced by the person in a given epoch exhibits a given sleep sound feature vector; providing a second model that gives a probability that a first sleep period state associated with a first epoch transitions to a second sleep period state associated with a subsequent second epoch; and processing the feature vectors using the first and second models to determine a sleep period state of the person from a plurality of possible sleep period states for each of the epochs.

Abstract: Electrical non-invasive brain stimulation (NIBS) delivers weak electrical currents to the brain via electrodes that are affixed to the scalp. NIBS can excite or inhibit the brain in areas that are impacted by that electrical current during and for a short time following stimulation. Electrical NIBS can be used to change brain structure in terms of increasing white matter integrity as measured by diffusion tensor imaging. Together the electrical NIBS can induce changes in brain structure and function. The present methods and devices are adaptable to and configurable for facilitating the enhancement of brain performance, and the treatment of neurological diseases and tissues. The present methods and devices are advantageously designed to utilize modern electrodes deployed with, inter alia, various spatial arrangements, polarities, and current strengths to target brain areas or networks to thereby enhance performance or deliver therapeutic interventions.

Abstract: A brainwave feedback system, adapted to generate feedback based on a user's brainwave, the brainwave feedback system comprises: a brainwave sensing device, configured to obtain a first brainwave signal of the user; a server, storing a keyword string pool including a plurality of sorted keywords, and performing a feedback procedure when a first physiological parameter falls outside of a predetermined parameter range, wherein the first physiological parameter is associated with the first brainwave signal, the feedback procedure includes choosing a keyword from the keyword string pool by the server as a feedback keyword, and outputting the feedback keyword; and an output component, in communicable connection with the server, wherein the output component presents an analysis result corresponding to the first physiological parameter. The present disclosure further discloses an operation method of brainwave feedback system.

Abstract: Universal switch modules, universal switches, and methods of using the same are disclosed, including methods of preparing an individual to interface with an electronic device or software. For example, a method is disclosed that can include measuring brain-related signals of the individual to obtain a first sensed brain-related signal when the individual generates a task-irrelevant thought. The method can include transmitting the first sensed brain-related signal to a processing unit. The method can include associating the task-irrelevant thought and the first sensed brain-related signal with N input commands. The method can include compiling the task-irrelevant thought, the first sensed brain-related signal, and the N input commands to an electronic database.

Abstract: The present invention relates to a patient feedback system (10) for providing feedback information on the use of a therapeutic device (14) to a patient (12), said system (10) comprising: an interface (34) for receiving personal profile data (18) of the patient (12); a database (16) for storing reference profile data (18?) and reference device settings (54) from a plurality of reference patients (42) using therapeutic devices; a cohort selection module (36) for comparing the personal profile data (18) of the patient (12) with the reference profile data (18?) of the reference patients (42) in the database (16) and for determining a cohort (44) for the patient (12) from the plurality of reference patients (42) based upon said comparison, wherein said cohort (44) comprises a subset of the reference patients (42) having reference profile data (18?) similar to the personal profile data (18) of the patient (12); and a feedback unit (38) for determining feedback information based on the reference device settings (54)

Abstract: A method for determining the intention of a user of a vehicle to brake or accelerate, comprising: acquiring (100) a plurality of EEG signals on the user, applying (101) a predetermined spatial filter on the plurality of EEG signals so as to obtain a target EEG component, detecting (102) a spectral pattern in the EEG component corresponding to an intention to brake or detecting a phase pattern in the EEG component corresponding to an intention to accelerate.

Abstract: A biopotential can be measured with high accuracy without the electrodes coming into direct contact with the skin and without being affected by any motion artifact. The present invention comprises a first lead which detects a biopotential containing noise components, a second lead which is electrically isolated from the first lead and detects noise components, and a differential amplifier circuit which is input with a first signal output from the first lead and a second signal output from the second lead, and which amplifies and outputs a difference between the first signal and the second signal, wherein a value of an input impedance on the second signal side of the differential amplifier circuit is set so that the noise components detected from the second lead will have a frequency that is higher than a frequency spectrum of the biopotential.

Abstract: A method (10) that encodes electrode locations to a mean scalp mesh for adaptation to subsequent image scans.

Abstract: Examples of the present disclosure describe systems and methods for probabilistic neural network architecture generation. In an example, an underlying distribution over neural network architectures based on various parameters is sampled using probabilistic modeling. Training data is evaluated in order to iteratively update the underlying distribution, thereby generating a probability distribution over the neural network architectures. The distribution is iteratively trained until the parameters associated with the neural network architecture converge. Once it is determined that the parameters have converged, the resulting probability distribution may be used to generate a resulting neural network architecture. As a result, intermediate architectures need not be fully trained, which dramatically reduces memory usage and/or processing time.

Abstract: A system (1) for estimating the brain blood volume and/or brain blood flow and/or depth of anesthesia of a patient, comprises at least one excitation electrode (110E) to be placed on the head (20) of a patient (2) for applying an excitation signal, at least one sensing electrode (110S) to be placed on the head (20) of the patient (2) for sensing a measurement signal caused by the excitation signal, and a processor device (12) for processing said measurement signal (VC) sensed by the at least one sensing electrode (110S) for determining an output indicative of the brain blood volume and/or the brain blood flow. Herein, the processor device (12) is constituted to reduce noise in the measurement signal (VC) by applying a non-linear noise-reduction algorithm. In this way a system for estimating the brain blood volume and/or the brain blood flow of a patient is provided which may lead to an increased accuracy and hence more exact estimates.

Abstract: An audio system is described for calibrating one or more transducers for a user using the auditory steady state response (ASSR) of the user. The audio system presents an audio calibration signal to the user via a transducer array in the headset. The system measures electrical signals that are generated in the auditory cortex of the brain of the user in response to the presented audio calibration signal. The audio system determines an ASSR of the user based on the measured electrical signals. The audio system determines a value for one or more sound filter parameter based on the determined ASSR and a model. The audio system calibrates the transducer array using the determined sound filter parameters. The calibrated transducer array is used to present audio content to the user.

Abstract: Methods, systems, and computer programs encoded on a computer storage medium, for improving EEG measurements by identifying artifacts present in EEG measurements and providing a real-time indication to a user of likely artifacts in EEG measurements are described. EEG measurements of a patient can be obtained by placing a wearable device or EEG cap on a patient's head. Sensors in the cap provide EEG data to a computing device that processes the data to identify one or more artifacts in the EEG data. The artifacts can be identified by conducting one or more operations of determining the signal to noise ratio of the line noise, calculating mutual information between sensor pairs, and applying the p-welch method. Based on the types of artifacts identified, the computing device can output an indicator that provides feedback to the technician performing an EEG test to make adjustments to the test setup.

Abstract: Methods and systems are provided for detecting a mental health condition. Structured and unstructured information is analyzed using natural language processing to extract information including clinical data values and medical concepts pertaining to a user. Reference medical information is evaluated using natural language processing to correlate medical data with mental health conditions. A classification for a mental health condition of the user is determined using a machine learning model and based on the extracted information and correlations, wherein the extracted information includes blood analysis for the user. The user is assigned to a segment of users based on the extracted information. A treatment for the mental health condition of the user is indicated based on the classification and the assigned segment of users.

Abstract: An apparatus including circuitry configured to determine a probability by combining at least: a probability that an event is present within a current feature of interest given a first set of previous features of interest, and a probability that the event is present within the current feature of interest given a second set of previous features of interest, different to the first set of previous features of interest; circuitry configured to detect the event based on the determined probability; and circuitry configured to control, in dependence on the detection of the event, performance of an action.

Abstract: A method of detecting an improvement in a seizure condition of a patient includes identifying a first EEG synchronization of the seizure condition of the patient; applying a therapy configured to improve the seizure condition of the patient; and identifying a second EEG synchronization of the seizure condition of the patient subsequent to application of the therapy, wherein an improvement of the seizure condition of the patient is demonstrated by a reduced EEG synchronization of the patient such that the second EEG synchronization is less than the first EEG synchronization.

Abstract: Disclosed is a method for the generation of a consciousness indicator for a non-communicating subject, including the steps of generating an auditory stimulation, receiving an electrocardiographic signal of the subject obtained from a recording during the generation of the auditory stimulation, extracting at least one feature from the electrocardiographic signal and deducing a consciousness indicator from an analysis of the electrocardiographic feature.

Abstract: Methods, systems and wearable devices for real-time mental stress assessment are provided. The methods and systems employ deep learning using a Gated Recurrent Unit (GRU) gating mechanism in a recurrent neural network with a sliding window approach applied to raw EEG data.

Abstract: Certain aspects of the invention provide a system and a method for treating an epileptic condition or a tumor of the brain. In one embodiment, the method of treating the epileptic condition includes acquiring inter- and post-ictal imaging profiles and from the brain of the patient and determining an ictal propagation pathway based on the profiles. A volume of cortical activation is determined for each of a plurality of virtual electrode placement positions based on the ictal propagation pathway and the virtual electrode placement position. An electrode is implanted at a position selected from the plurality of virtual electrode placement positions, based on the volume of cortical activation at the implantation position. An electrical pulse is delivered from the electrode, where the electrical pulse is of a magnitude and duration effective to at least reduce the epileptic seizure.

Abstract: Apparatuses and methods for non-invasively detecting and classifying transcranial electrical signals are disclosed herein. In an embodiment, system for detecting and interpreting transcranial electrical signals includes: a headset including a plurality of electrodes arranged for detection of the user's transcranial electrical signals; a display configured to display information to the user while the user wears the headset; and a control unit programmed to: (i) receive data relating to the transcranial electrical signals detected by the electrodes of the headset; (ii) create a data matrix with the received data; (iii) convert the data matrix into one or more user values; (iv) define a user output state based on the one or more user values; and (iv) cause alteration of an aspect of the display based on the user output state.

Abstract: The present invention relates to a quantitative electroencephalogram (QEEG) monitor and system capable of monitoring and displaying simultaneously neuropathological characteristic and activity of both sides of a subject's brain. The methods include various indices and examination of differences in these indices by which neurophysiological conditions or problems can be identified and treated. These methods, and the systems and devices using these methods preferably can be used for identifying these neurophysiological conditions or brain dysfunction with monitors and methods for seizure detection, for sedation monitoring, for anesthesia monitoring, and the like. These bilateral brain monitoring methods and systems, and the devices using these methods can be used by individuals or clinicians with little or no training in signal analysis or processing. These bilateral monitoring methods can also be used in a range of applications.

Abstract: In some examples, a facial gasket device includes a plurality of physiological sensors to detect physiological signals, and a signal processor to receive output signals based on measurements of the plurality of physiological sensors, the signal processor programmable to selectively combine a collection of the output signals to detect a target physiological activity of the user.

Abstract: A system and method is provided for tracking sleep dynamics in a subject. In one aspect, a method includes acquiring physiological data using sensors positioned about the subject, and acquiring behavioral data using input provided by the subject. The method also includes generating a statistical model of wakefulness by combining information obtained from the acquired physiological data and behavior data, and estimating a probability indicative of a degree to which the subject is awake at each point in time during sleep onset using the statistical model. The method further includes generating a report indicative of sleep onset in the subject.

Abstract: Sleep performance systems and methods of using the same are disclosed. The sleep performance systems can improve the quality of sleep by making one or more recommendations to the subject for increasing a sleep quality score. The sleep performance systems can have one or more electroencephalography (EEG) electrodes configured to measure a subject's brain activity during sleep. The sleep performance systems can have a processor configured to quantify the quality of the subject's slow-wave sleep by determining one or more sleep performance scores associated with the measured brain activity. The sleep performance systems can recommend and/or activate sleep improvement programs based on various threshold scores.

Abstract: A computer-implemented method of providing virtual reality (VR) or Augmented Reality (AR) training includes adapting the VR/AR training based on feedback on the user's biometric data, which may include electroencephalogram (EEG) data and other biometric data. Associations are determined between the biometric data and psychological/neurological factors related to learning, such as a cognitive load, attention, anxiety, and motivation. In one implementation, predictive analytics are used to adapt the VR/AR training to maintain the user with an optimal learning zone during the training.

Abstract: A system may present notifications to an occupant of a vehicle and determine whether the occupant has given attention to the notification. The system oscillates a visual notification at an output frequency. The system captures images of an eye of the occupant to determine an eye pupil oscillation frequency associated with the occupant. The system compares the eye pupil oscillation frequency to the output frequency. The system determines whether attention was given to the notification based on whether the output frequency and the eye pupil oscillation frequency match. If the system determines that attention was not given, the system may cause performance of one or more follow-up operations.

Abstract: A method of detecting abnormalities in ECG signals by providing an ECG signal to a neural network, performing a first series of convolution operations to a first subset of layers and in a final layer, and determining a plurality of preliminary classification estimates, each preliminary classification estimate corresponding with a time segment of the ECG signal. Furthermore, determining input data for a second subset of layers of the neural network by concatenating the preliminary classification with the output of a layer of the first subset of layers that precedes the final layer of the first subset of layers. Within the second subset of layers of the neural network, performing a second series of convolution operations. In a final layer of the second subset, determining plurality of final classification estimates, each final classification estimate corresponding with a time segment of the ECG signal.

Abstract: An apparatus for providing a customized mobility driving path using a brain wave signal includes a sensor configured to collect a brain wave signal for a driver of a mobility in a predetermined channel region, an analyzer configured to determine information to be provided regarding a planned path by analyzing the brain wave signal collected in the predetermined channel region, and a controller configured to control an operation of the mobility based on the information to be provided.

Abstract: A system for application selection using behavioral propensities includes a computing device configured to identify a negative behavioral propensity associated with a human subject, generate, using category training data including a plurality of applications and a plurality of correlated categories, and using a classification algorithm, an application category classifier, wherein the application category classifier inputs applications and outputs categories of the applications, receive an application to be loaded to a device operated by the human subject, identify, using the application category classifier, a category of the application, wherein identifying the category includes determining, a plurality of application data elements, classifying each application data element of the plurality of application data elements to an application data object of a plurality of application data objects using an object classifier, and inputting the plurality of objects to the application category classifier, and determine

Abstract: A system and method are provided for monitoring subject behavior during sleep onset. In some aspects, a system includes one or more sensors configured to acquire behavioral data from a subject using input provided during sleep onset. The system also includes a processor programmed to at least assemble a time-series of behavioral responses using the behavioral data acquired using the one or more sensors, and estimate an instantaneous probability of response using the time-series of behavioral responses. The processor is also programmed to generate a statistical model of wakefulness using the instantaneous probability of response, and estimate, using the model, a probability indicative of a degree to which the subject is awake at each point in time during the sleep onset process. The processor is further configured to generate a report indicative of sleep onset in the subject. The system also includes an output for displaying the report.

Abstract: The disclosure provides for a method for generating an ultrasound image that includes transmitting, by a plurality of transmitters in a transducer, at least two transmit beams at different angles, where at least parts of the transmit beams cover an overlapping region, and receiving, by a plurality of sensors of the transducer, reflected signals of the transmit beams. The method further comprises calculating channel coherence for the received signals to produce one or more channel coherence images, and calculating transmit coherence for the received signals to produce one or more transmit coherence images. The information from at least one of the channel coherence images and at least one of the transmit coherence images are combined to identify moving objects. The received signals from different transmits in overlapping regions are then processed to produce a final image that is compensated for the moving objects.

Abstract: One embodiment of an exemplary ambulatory seizure monitoring method calculates a phase lock value synchrony level of a neurological signal of an individual; detects an onset of a seizure event for the individual by comparing the phase lock value synchrony level with a patient threshold for the individual; and transmits a notification to a remote communication device indicating the onset of the seizure event for the individual.

Abstract: A sensor system has a low-noise sensor controller providing communications between an active-temperature-regulated optical sensor and an external monitor. A low-noise sensor controller drives optical emitters, receives resulting detected signals after attenuation by a blood perfused tissue site and communicates the detector signals to the attached signal processor. An optically-isolated controller front-end receives and digitizes the detected signals. A controller serializer transmits the digitized detector signal to the processor via a single, shielded coaxial cable.

Abstract: Apparatus for ophthalmic electrophysiological testing, the apparatus comprising: an EER stimulator for providing an electrical stimulus to an eye so as to evoke an electrophysiological response, wherein the EER stimulator comprises a power source; an amplifier for receiving the electrophysiological response and measuring that response, wherein the amplifier is integrated with the EER stimulator; and at least one switch disposed between the power source and the amplifier for isolating the power source from the amplifier when the electrical stimulus is delivered to the eye.

Abstract: Apparatus for applying Transcranial Magnetic Stimulation (TMS) to an individual, wherein the apparatus comprises: a head mount for disposition on the head of an individual; and a plurality of magnet assemblies for releasable mounting on the head mount, wherein each of the magnet assemblies comprises a permanent magnet, and at least one of (i) a movement mechanism for moving the permanent magnet and/or (ii) a magnetic shield shutter mechanism, for selectively providing a rapidly changing magnetic field capable of inducing weak electric currents in the brain of an individual so as to modify the natural electrical activity of the brain of the individual; wherein the number of magnet assemblies mounted on the head mount, their individual positioning on the head mount, and their selective provision of a rapidly changing magnetic field is selected so as to allow the spatial, strength and temporal characteristics of the magnetic field to be custom tailored for each individual, whereby to provide individual-specific

Abstract: A method of authentication of a user is provided. The method comprises capturing a brain activity signal from a user; comparing the brain activity signal with reference data; and determining, based at least in part on the comparison, whether the identity of the user can be confirmed. Also provided is a computing device comprising at least one processor and at least one memory. The computing device is adapted to: communicate with a brain activity sensing system to capture a brain activity signal from the user; provide the captured brain activity signal to an authentication service computing system; and authenticate the user based at least in part on the result of a comparison with reference data received from the authentication service computing system. A system comprising the computing device and a brain activity sensing system, and am authentication service computing device are also provided.

Abstract: Provided is a data processing apparatus including a signal data processor configured to collect signal data detected through polysomnography, to extract feature data by analyzing a feature of the collected signal data, and to transform the extracted feature data to time series data; and a sleep stage classification model processor configured to input the processed signal data to a pre-generated sleep stage classification model, and to classify a sleep stage corresponding to the signal data. The signal data processor is configured to extract feature data by analyzing a feature of each of an electroencephalographic (EEG) signal, an electro-oculographic (EOG) signal, and an electromyographic (EMG) signal with respect to the signal data, and to transform the extracted feature data to an epoch unit of time series data to input the extracted feature data to the pre-generated sleep stage classification model.

Abstract: An error monitoring apparatus and method are provided. The error monitoring method includes collecting an Event-Related Potential (ERP) for at least one passenger in a first mobility for a predetermined amount of time, analyzing the ERP collected for the predetermined amount of time, and transmitting error information of the first mobility to a traffic control server based on a result of analysis. The error information of the first mobility includes at least one of information on a time when the ERP is generated, a waveform of the ERP, position information of the first mobility or operation information of a second mobility, and the second mobility is different from the first mobility and has caused the ERP.

Abstract: The present invention provides a system for selecting appropriate brain-training content for each user. The selection system includes: a storage unit for storing detection values obtained by detecting blood flow rates in the head of a user, identifiers for predetermined test content to be performed by the user at the time of the detection of the detection values, and an identifier for the user in association with one another; a calculation unit for calculating, on the basis of the detection values stored in the storage unit, brain-activity values indicating the degree of brain-activity of the user when the predetermined test content is performed by the user; and a selection unit for selecting, on the basis of the brain-activity values calculated by the calculation unit during performance of the predetermined test content, brain-training content to be performed by the user.

Abstract: A method and system for utilizing empirical null hypothesis for a biological time series is disclosed herein. The method also includes calculating an amount that a second plurality of epochs is similar to a first plurality of epochs using large-scale testing to estimate an empirical null hypothesis for a subset of the epochs. The method also includes determining if the second plurality of epochs is from the same EEG recording.

Abstract: The present invention disclosed a device and method for assessing in real time the hypnotic and analgesic effect in a subject during wakefulness, sedation and general anaesthesia via drug interactions and physiological signals. In a preferred embodiment of the present invention, the analgesic and hypnotic effect of drug(s) infused in a subject could be accurately assessed in real time through the device and method disclosed in the present invention, comprising steps of receiving data from electroencephalography (EEG) device, receiving data from brain impedance tomography device, obtaining pharmacodynamic and pharmacokinetic parameters of drug(s) infused in the subject, defining initial indices of consciousness and nociception as a function of said EEG and brain impedance tomography data, and generating output of final indices of consciousness and nociception in real time from processing input of EEG, brain tomography and drug interaction data using established mathematical manipulation.

Abstract: An acquisition unit is configured to acquire measurement values of a target device. A likelihood calculation unit is configured to calculate an occurrence likelihood for each of a plurality of phenomena that are liable to occur to the target device based on the measurement values acquired by the acquisition unit. A table storage unit is configured to store a table in which the plurality of phenomena and occurrence causes of abnormalities of the target device are associated to each other. As estimation unit is configured to estimate the occurrence causes based on the occurrence likelihood and the table.

Abstract: Methods, apparatus and systems for wireless sleep monitoring are disclosed. In one embodiment, a described sleep monitoring system comprises: at least one sensor in a venue, wherein the at least one sensor comprises a wireless non-contact sensor having no physical contact with the user; a processor communicatively coupled to the at least one sensor; a memory communicatively coupled to the processor; and a set of instructions stored in the memory. The set of instructions, when executed by the processor, causes the processor to perform: obtaining, based on the at least one sensor, a plurality of time series of sensing features (TSSF) associated with a sleep motion of a user in the venue, and monitoring the sleep motion of the user jointly based on the plurality of TSSF.

Abstract: Disclosed is an application cleaning method and device, a storage medium and an electronic device. In the embodiments of the present disclosure, the method involves: collecting multi-dimensional features of an application as samples, and constructing a sample set of the application; according to information gain ratios of the features with regard to sample classification, carrying out sample classification on the sample set so as to construct a decision tree model of the application; according to a prediction time, collecting corresponding multi-dimensional features of the application as prediction samples; and according to the prediction samples and the decision tree model, predicting whether the application can be cleaned.