Abstract: Apnea-hypopnea detection includes obtaining accelerometer data from an accelerometer configured to measure micro-movements that are due to respiration. Displacement values are obtained from the accelerometer data. Features are obtained using the accelerometer data. An apnea-hypopnea index (AHI) is obtained from a machine learning model that uses the features as inputs. The displacement values correspond to peaks in the accelerometer data.

Abstract: A blood oxygen saturation measurement method includes: acquiring a pressure measurement signal between a blood oxygen saturation measurement apparatus and an object; in response to determining that the pressure measurement value is within a preset range, and acquiring a blood oxygen saturation measurement signal of the object; and according to the blood oxygen saturation measurement signal of the object, obtaining a blood oxygen saturation measurement value of the object.

Abstract: A device including sensors and a processor. The sensors are configured to detect movements of a user. The processor is configured to categorize the movements of the user as a micro-movement or a macro-movement; quantify a number of the micro-movements; quantify a number of the macro-movements; determine based upon the number of micro-movements whether a body part of interest of a user is supported; and provide feedback to the user if the body part of interested is unsupported and continuing to monitor the body part of interest if the user is supported without providing any feedback.

Abstract: The present application provides a method and apparatus for detecting an ECG signal and an electronic device. According to an example of the method, an ECG signal with a set time length is segmented to obtain a first set number of single heartbeats; feature data corresponding to each of the first set number of single heartbeats is determined to obtain a first set number of feature data; and a pathological category of the ECG signal with the set time length is determined based on the ECG signal with the set time length and the first set number of feature data.

Abstract: A wearable device includes a processor and a lower module. The lower module includes a pressure sensor for detecting a mechanical movement of a skin that covers an artery. The mechanical movement of the skin is due to blood flow through the artery. The processor is configured to receive skin movement information from the movement sensor; calculate a pulse front velocity (PFV), which is a velocity of a blood wave as the blood wave passes under the pressure sensor; estimate a pulse wave velocity (PWV) using the PFV; and estimate the blood pressure using the PWV.

Abstract: A device comprising: (a) an accelerometer or gyroscope that is capable of measuring movement, and (b) a sensor that is configured to monitor and determine a electrical signals or pulse signals of a heart so that the sensor detects a heart rate of a user; wherein the device is configured for placement on a first location of the user to determine a heart rate of the user; wherein the device is configured for placement on or contact with a second location of the user where the sensor measures the user's heart rate and the accelerometer or gyroscope measures a heart rate of a fetus located within the user; and (c) a processor configured to isolate the heart rate of the fetus from the heart rate of the user so that the heart rate of the fetus is displayed on the device.

Abstract: A permittivity apparatus that includes a permittivity material is received. The permittivity material includes one or more types of high permittivity materials. The permittivity apparatus is configured to be placed near or into a region of interest to be imaged. The permittivity apparatus is placed near or into the region of interest such that placing the permittivity apparatus near or into the region of interest changes a local stored electromagnetic energy distribution around or inside the region of interest. MRI images including the region of interest are then acquired. An MRI system includes radiofrequency coils and a permittivity apparatus that includes one or more types of high permittivity materials. The permittivity apparatus is configured to be placed near or into a region of interest to be imaged.

Abstract: A portable system has a magnet, magnet bore and shielding. The magnet bore extends through the magnet, and the magnet bore configured to receive at least some portion of a patient. The shielding forms a shielding area, and the shielding includes one or more layers. The shielding has a material that provides magnetic shielding that reduces or prevents a static magnetic field (SMF); a material that provides electromagnetic shielding and reduces or prevents a time-varying-electromagnetic field (EMF); a removable shielding removable or movable, wherein the patient is able to move into our out of the magnet bore when the removable shielding is in a moved position or a removed position and the removable shielding; and a shielding adapter covering a connection of devices and extending from the exterior of the portable system. All or a portion of the shielding includes a transparent portion.

Abstract: Assessing a blood pressure of a user includes obtaining photoplethysmogram (PPG)-related signals of the user; inputting the PPG-related signals to layers of a deep-learning (DL) model, where the layers exclude an output layer; obtaining, from the layers of the DL model, features related to blood pressure; inputting to a machine-learning (ML) model the obtained features, where the ML model is different from the DL model; and obtaining, as an output of the ML model, the blood pressure of the user.

Abstract: A method for modifying cognitive processes includes receiving respective electroencephalogram (EEG) signals from EEG sensors, where the EEG signals are of a brain of a user. Features are extracted from the respective EEG signals. A cognitive state of the brain of the user is obtained from a first machine learning (ML) model that uses the features as input. Feedback parameters of a feedback signal are obtained from a second model that uses the cognitive state as input. The feedback signal is and provided to the user and using a user device according to the feedback parameters.

Abstract: Provided are a display method and apparatus, a smart wearable device, and a computer-readable storage medium, the display method being used on the smart wearable device, and the smart wearable device including at least two screen display regions and at least two corresponding audio collection units; when a user is wearing the smart wearable device, the screen display regions are not simultaneously in the same plane. The display method includes according to voice signals collected by all of the audio collection units, determining an audio collection unit nearest a sound source; turning on a screen display region corresponding to the audio collection unit nearest the sound source to display current content.

Abstract: A portable device for measuring an electrocardiogram (ECG) of a user. The portable device includes a first ECG sensor that is configured to touch a body of the user, and a processor. The processor is configured to receive a first ECG measurement at a first location on the body of the user, where the first ECG sensor is placed at the first location of the body; identify a first region of the heart of the user based on the first location; direct the user to move the portable device to a second location on the body of the user; receive a second ECG measurement at the second location on the body; and identify a second region of the heart of the user based on the second location.

Abstract: A display method and apparatus, a wearable device, and a computer-readable storage medium are provided. The method is applied to the wearable device. The wearable device comprises at least two touchable screen display areas. The method comprises: displaying current content on a lightened screen display area; and adjusting the current content displayed on the lightened screen display area according to a touch event on another non-lightened screen display area. The reading and interaction processes of users do not conflict with each other.

Abstract: A display method and apparatus, a wearable device, and a computer-readable storage medium. The method is applied to the wearable device. The wearable device comprises an inertial sensor and at least two screen display areas; when a user wears the wearable device, the screen display areas are not located on the same plane at the same time. The method comprises: obtaining a target action of a user by means of measurement data collected by the inertial sensor; determining the screen display area corresponding to a sight range of the user according to the target action of the user; and lighting the screen display area to display the current content.

Abstract: Measuring, using a wearable device, a blood pressure of a user includes extracting, using sensor data of the wearable device, features related to a pulse wave; determining a pulse transit time (PTT); scaling at least one of the features using the PTT to obtain a scaled feature; using the scaled feature as an input to a machine-learning (ML) model; and obtaining, using an output of the ML model, the blood pressure of the user.

Abstract: A method includes obtaining a baseline blood pressure at an initial time window; estimating a plurality of intermediate blood pressure change estimates, the intermediate blood pressure change estimates correspond to respective time windows that are subsequent to the initial time window; estimating a final blood pressure change estimate between the initial and final time windows; and obtaining the blood pressure by adding the baseline blood pressure to the final blood pressure change estimate. Estimating the final blood pressure includes estimating a first blood pressure change between the initial time window and the final time window; estimating a plurality of second blood pressure changes, each second blood pressure change is between a respective time window of the respective time windows and the final time window; and estimating the final blood pressure change estimate as a combination of the first blood pressure change and the plurality of second blood pressure changes.

Abstract: The present disclosure provides a noise detection method and a noise detection apparatus. The method includes: segmenting a collected photoplethysmography signal into a plurality of sub-signal segments; extracting a characteristic of each sub-signal segment; for each sub-signal segment, determining a self-similarity of the sub-signal segment in the photoplethysmography signal based on the characteristic of the sub-signal segment; and determining that the sub-signal segment is noise when the self-similarity is lower than a threshold.

Abstract: The present disclosure provides a wearable device, a signal processing method and a signal processing apparatus, the signal processing method is applied to the wearable device, the wearable device is provided with a biosensor and a motion detector group, and the signal processing method includes the following steps. The human physiological signal collected by the biosensor is acquired, the human physiological signal is divided into multiple signal frames, each of the multiple signal frames corresponds to the time range; for each signal frame, it is determined whether the user wearing the wearable device is in the body motion state according to the body motion signal collected by the motion detector group within the time range corresponding to the signal frame, and when the user wearing the wearable device is not in the body motion state, the signal frame is stored into the preset buffer.

Abstract: Physiological signals produced at a wearable device are compressed and mapped to detect a health condition of a user of the wearable device. Physiological signal data indicating a physical quality of the user of the wearable device is produced based on noisy data recorded using sensors of the wearable device. The physiological signal data is compressed at the wearable device using a dictionary defined at a server device. The server device receives and decompresses the compressed physiological signal data to produce denoised physiological signal data indicating the physical quality of the user of the wearable device. A change in a physiological state of the user of the wearable device is determined using the denoised physiological signal data and historical physiological data of the user of the wearable device. The health condition is detected based on the change in the physiological state of the user of the wearable device.

Abstract: A wearable device includes a processor and a lower module. The lower module includes a pressure sensor for detecting a mechanical movement of a skin that covers an artery. The mechanical movement of the skin is due to blood flow through the artery. The processor is configured to receive skin movement information from the movement sensor; calculate a pulse front velocity (PFV), which is a velocity of a blood wave as the blood wave passes under the pressure sensor; estimate a pulse wave velocity (PWV) using the PFV; and estimate the blood pressure using the PWV.