A system for marking cardiac time intervals from heart valve signals includes a non-invasive sensor unit for capturing electrical signals and composite vibration objects, a memory containing computer instructions, and one or more processors coupled to the memory. The one or more processors causes the one or more processors to perform operations including separating a plurality of individual heart vibration events into heart valve signals from the composite vibration objects, and marking cardiac time interval from the heart valve signals by detecting individual heartbeats using at least one or more of a PCA algorithm or deep learning.

Methods, apparatuses and systems directed to pattern learning, recognition, and metrology. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In certain implementations, the present invention provides for methods and systems suitable for analyzing and recognizing patterns in biological signals such as multi-electrode array waveform data. In other implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes. In other implementations, the present invention provides methods and systems for dynamic learning of patterns in supervised and unsupervised manners.

A data processing method includes: a data preparing step of preparing actual data of a three-dimensional chromatogram including a chromatogram and a spectrum acquired by chromatography analysis for a sample containing a plurality of components, and spectral data for the plurality of components in the sample whose peaks overlap each other on the chromatogram of the actual data; a similarity calculating step of calculating, for each wavelength region, a similarity between wavelength regions corresponding to each other in the spectral data for the plurality of components prepared in the data preparing step while comprehensively changing the wavelength regions; a target range setting step of setting a target range by searching for a wavelength region having a similarity lower than an overall similarity between the spectral data for the plurality of components based on a calculation result in the similarity calculating step; and a peak separating step of creating chromatogram data for the plurality of components by performing, using the spectral data for the plurality of components, matrix decomposition of the actual data in the target range set in the target range setting step.

A system includes a wearable device including an accelerometer configured to record accelerometer data during an activity; a modeling device programmed to determine device acceleration data of the wearable device during the activity based on the accelerometer data, the device acceleration data including x-axis, y-axis, and z-axis acceleration data of the device, translate the device acceleration data to wearer acceleration data of a wearer during the activity, wherein the wearer acceleration data includes at least x-axis and y-axis wearer acceleration data, wherein the y-axis acceleration data of the wearer indicates acceleration along a sagittal axis of the wearer, identify a lift, and utilize a trained lift classification machine learning model to classify the lift as high-risk or low-risk based on a ratio of the x-axis wearer acceleration data to the wearer y-axis acceleration data; and a feedback element configured to provide tangible feedback based on identification of a high-risk lift.

The present invention relates to a generation of a signal by executing a waveform dataset comprising waveform descriptive parameters. The execution of the waveform description parameters is limited by target device information specifying one or more specific target devices and time information specifying an execution period of the waveform descriptive parameters. By providing a waveform dataset comprising not only the waveform descriptive parameters, but also further information, in particular time information for limiting the execution period of the waveform descriptive parameters, the generation of the respective waveform signal is controlled.

A method for improving an identification accuracy of mixture components by using a known mixture Raman spectrum is disclosed. After calculating a first similarity between a to-be-tested Raman spectrum characteristic vector group and a pure substance Raman spectrum characteristic vector group of an nth kind of pure substance in a Raman spectrum standard library, the method uses a known mixture library to calculate to obtain a second similarity between a to-be-identified substance Raman spectrum characteristic vector group and a spectral peak characteristic vector group with offset information corresponding to a pure substance in a known mixture, and determines a similarity between a to-be-tested mixture and the nth kind of pure substance according to the first similarity and all second similarities to thus obtain a component identification result. The present application uses the known mixture library to assist the Raman spectrum standard library in searching.

A method includes: collecting an original signal in a specified time interval, and performing combined acceleration processing on the original signal to obtain a combined acceleration signal; performing state processing on the combined acceleration signal to obtain a motion time interval, and extracting a plurality of feature groups from the combined acceleration signal according to a preset motion rule; and performing screening on the plurality of feature groups to obtain a first feature group, extracting a median value from the first feature group, and obtaining a stride frequency in the specified time interval based on the median value and a collection frequency, and obtaining a quantity of steps through calculation based on the motion time interval and the stride frequency.

An information processing apparatus includes an extraction unit, a determination unit, a display control unit, and a display unit. The extraction unit is configured to extract, by predetermined pattern matching, candidate peaks in a certain arbitrary period of time from among at least one or more pieces of waveform data. The determination unit is configured to determine, from among the candidate peaks of the waveform data, a single peak based on a score related to the pattern matching. The display control unit is configured to output display information for displaying a position of the peak. The display unit is configured to display the display information.

An electronic device includes: a housing including a front plate oriented in a first direction and a rear plate oriented in a second direction; a display visible through at least a portion of the front plate; and a biometric sensor module located between the front plate and the rear plate. The biometric sensor module may include: a cover glass oriented in the second direction; at least one light source configured to emit light to the outside; a light detector disposed adjacent to the at least one light source, and configured to receive reflected light corresponding to light emitted from the light source; a light guide disposed between the light detector and the cover glass, and configured to provide a path of the reflected light received by the light detector; and a circuit board electrically connected to the at least one light source and the light detector.

Doppler lidar for detecting wind speeds, comprising a device (MO) for generating pulsed coherent laser light on N wavelength channels, amplitude modulation (AM) being performed separately for each individual wavelength channel for shaping the pulse individually for each channel, a device (TK, SC) for transmitting generated, frequency-shifted and amplified pulses of the laser light in predetermined spatial directions, a detector (n×Det.) for receiving the generated and the backscattered laser light on N wavelength channels, and an electronic evaluation device (n×SV) for determining a Doppler shift amount between the transmitted light and the received light on N wavelength channels, wherein a timing modulator (TM) is assigned to the N wavelength channels for individual control of a pulse repetition frequency (PRF) and/or pulse repetition period (PRT) in addition to the pulse shape for wavelength channels.