Abstract: A wearable apparatus and a method for ECG signal collection includes: a main body, including a first ECG sensor electrode provided on a side of the main body away from a wearing position of an individual and a second ECG sensor electrode provided on a side of the main body close to the wearing position, a securing portion, including a third ECG sensor electrode provided on a side of the securing portion away from the wearing position, and an ECG sensor, provided in the main body and configured to: electrically connect to the first ECG sensor electrode and the second ECG sensor electrode, electrically connect to the third ECG sensor electrode through a wire in the securing portion, and collect ECG signals from close circuits formed by the first ECG sensor electrode, the second ECG sensor electrode, and the third ECG sensor electrode.

Abstract: A wearable device includes: a body, a driving assembly, and a camera assembly. The body includes a working surface and a side wall connected to an edge of the working surface. The driving assembly is connected to the body and includes an adjusting component and a supporting component that protrude from the side wall. The adjusting component and the supporting component are rotatable relative to each other in a plane perpendicular to the working surface. The camera assembly includes a lens connected to the adjusting component and an image sensor connected to the supporting component. The relative rotation of the adjusting component and the supporting component drives the lens to move linearly in a direction perpendicular to a photosensitive surface of the image sensor.

Abstract: A method for configuring a monitoring component for a user includes receiving an electrocardiograph (ECG) signal from an ECG component, receiving a weight signal from a scale component, and combining features extracted from the ECG signal and the weight signal to generate a current biometric signal. Responsive to the current biometric signal matching a historical biometric signal, the method includes obtaining a user profile and determining a health status for association with the user profile by classifying the current biometric signal using disease models and fitness models.

Abstract: Methods, apparatuses and wearable devices for measuring an ECG signal for a user wearing a wearable device includes when the ECG signal is measured in a first mode, receiving the ECG signal by an ECG sensor from a closed circuit formed by a first ECG sensor electrode and a second ECG sensor electrode, in which the wearable device includes a main body detachable to the wearable device, a connecting portion, and electrode patches, and the main body includes the ECG sensor, the first ECG sensor electrode, and the second ECG sensor electrode, and when the ECG signal is measured in a second mode, receiving the ECG signal by the ECG sensor from a closed circuit formed by electrodes of the electrode patches, in which the ECG sensor is in the main body and the main body is connected to the electrode patches.

Abstract: A method for configuring a monitoring component for a user includes receiving an electrocardiograph (ECG) signal from an ECG component, receiving a weight signal from a scale component, and combining features extracted from the ECG signal and the weight signal to generate a current biometric signal. Responsive to the current biometric signal matching a historical biometric signal, the method includes obtaining a user profile and determining a health status for association with the user profile by classifying the current biometric signal using disease models and fitness models.

Abstract: A method for configuring a monitoring component for a user includes receiving an electrocardiograph (ECG) signal from an ECG component, receiving a weight signal from a scale component, and combining features extracted from the ECG signal and the weight signal to generate a current biometric signal. Responsive to the current biometric signal matching a historical biometric signal, the method includes obtaining a user profile and determining a health status for association with the user profile by classifying the current biometric signal using disease models and fitness models.

Abstract: This disclosure provides wearable-device based user-interested information determination methods, apparatuses and wearable devices. The method includes: receiving, by an electrocardiography (ECG) sensor associated with the wearable device, an ECG signal of a user, determining a feature set for the ECG signal, in which the feature set includes time-domain feature data of the ECG signal and frequency-domain feature data of the ECG signal, and determining the user-interested information based on similarity between the feature set and reference feature sets indicative of the user-interested information, in which the user-interested information includes health information associated with a disease. The wearable device includes an ECG sensor configured to receive an ECG signal and an FPGA system. The FPGA system includes modules for determine user-interested information based on the ECG signal. The apparatus includes a processor and a memory coupled to the processor.

Abstract: Methods, apparatuses and wearable devices for measuring an ECG signal for a user wearing a wearable device includes when the ECG signal is measured in a first mode, receiving the ECG signal by an ECG sensor from a closed circuit formed by a first ECG sensor electrode and a second ECG sensor electrode, in which the wearable device includes a main body detachable to the wearable device, a connecting portion, and electrode patches, and the main body includes the ECG sensor, the first ECG sensor electrode, and the second ECG sensor electrode, and when the ECG signal is measured in a second mode, receiving the ECG signal by the ECG sensor from a closed circuit formed by electrodes of the electrode patches, in which the ECG sensor is in the main body and the main body is connected to the electrode patches.

Abstract: A wearable apparatus and a method for ECG signal collection includes: a main body, including a first ECG sensor electrode provided on a side of the main body away from a wearing position of an individual and a second ECG sensor electrode provided on a side of the main body close to the wearing position, a securing portion, including a third ECG sensor electrode provided on a side of the securing portion away from the wearing position, and an ECG sensor, provided in the main body and configured to: electrically connect to the first ECG sensor electrode and the second ECG sensor electrode, electrically connect to the third ECG sensor electrode through a wire in the securing portion, and collect ECG signals from close circuits formed by the first ECG sensor electrode, the second ECG sensor electrode, and the third ECG sensor electrode.

Abstract: This disclosure provides wearable-device based user-interested information determination methods, apparatuses and wearable devices. The method includes: receiving, by an electrocardiography (ECG) sensor associated with the wearable device, an ECG signal of a user, determining a feature set for the ECG signal, in which the feature set includes time-domain feature data of the ECG signal and frequency-domain feature data of the ECG signal, and determining the user-interested information based on similarity between the feature set and reference feature sets indicative of the user-interested information, in which the user-interested information includes health information associated with a disease. The wearable device includes an ECG sensor configured to receive an ECG signal and an FPGA system. The FPGA system includes modules for determine user-interested information based on the ECG signal. The apparatus includes a processor and a memory coupled to the processor.

Abstract: A method for configuring a monitoring component for a user includes receiving an electrocardiograph (ECG) signal from an ECG component, receiving a weight signal from a scale component, and combining features extracted from the ECG signal and the weight signal to generate a current biometric signal. Responsive to the current biometric signal matching a historical biometric signal, the method includes obtaining a user profile and determining a health status for association with the user profile by classifying the current biometric signal using disease models and fitness models.