34 results about "Pulse Transit Time" patented technology

The present invention relates to a device, system and method for calibrating a blood pressure, BP, surrogate for use in monitoring a subject's blood pressure. The device comprises a BP input (51), a sensor input (52) and a processing unit (53) that is configured to compute a control signal for controlling the pressure-delivery system (10) to repeatedly inflate its cuff in directly consecutive partial inflations up to a cuff pressure equal to or below the subject's mean BP, compute pulse-related values from the first and second time-dependent sensor signals, measured during the repeated directly consecutive partial inflations of the cuff, using a first feature in the first time-dependent sensor signal and a second feature in the second time-dependent sensor signal, the pulse-related values being pulse arrival time, PAT, values or pulse transit time, PTT, values, and compute a calibration parameter for a BP surrogate from the BP measurement value and pairs of the pulse-related values and corresponding cuff pressure values, computed from the first and second time-dependent sensor signals measured during the repeated directly consecutive partial inflations of the cuff, a pair comprising a pulse-related value and a corresponding, temporally related cuff pressure value.

The invention belongs to a non-invasive blood pressure measurement method, and provides a blood pressure measurement method based on forearm local pulse transit time and a related device aiming at the technical problems that an existing blood pressure measurement method based on the forearm local pulse transit time is weak in relevancy and prone to being affected by complex factors. Non-invasive blood pressure measurement is realized by using an artificial neural network, and by synchronously detecting two paths of front arm local photoelectric volume pulse wave signals, front arm local pulse conduction time which is not highly related to blood pressure is taken as a core; in combination with demographic features having high correlation to blood pressure and other hemodynamic features except local pulse transit time, including time domain features, frequency domain features, time domain statistical features and frequency domain statistical features, sending the features to the trained prediction network model for prediction to obtain a model including systolic pressure, diastolic pressure, blood pressure, blood pressure, blood pressure, blood pressure, blood pressure, blood pressure, blood pressure and the like. And real-time blood pressure data of pulse pressure difference and average pressure.

A method that selects high-quality data within recorded signals from patient monitoring devices, where portions of the signals may be corrupted by noise and should therefore be excluded. Signals are compared to models of expected signal characteristics, and portions of the signals that do not match the models may be excluded. Some models may check for expected relationships between signals from different devices. One such model identifies feature points in two signals from two different devices and calculates the time difference between each feature point in one signal and the earliest subsequent feature point in the other signal; data is excluded if this time difference exceeds an expected range. For example, an expected relationship between electrocardiogram and blood pressure signals is that the R-wave peak should be followed by a blood pressure peak within an expected delay time (the pulse transit time); this check can exclude invalid ECG / BP data.

An electronic device according to an embodiment may include communication circuitry and at least one processor. The at least one processor may be configured to receive a first PPG signal obtained by a first wearable device from the first wearable device via the communication circuitry and receive a second PPG signal from a second wearable device. The first wearable device may be worn on a first position of a user and the second wearable device may be worn on a second position of the user. The at least one processor may be configured to obtain a pulse transit time (PTT) taken for a pulse wave to be transferred from the first position to the second position, based on the first PPG signal and the second PPG signal. The at least one processor may be configured to obtain a distance between the first wearable device and the second wearable device. The at least one processor may be configured to obtain a pulse wave velocity (PWV) at which the pulse wave is transferred, based on the distance and the PTT. The at least one processor may be configured to obtain a first blood pressure by using a pulse wave analysis (PWA) method, based on the first PPG signal and / or the second PPG signal. The at least one processor may be configured to obtain a vascular characteristic value related to a characteristic of a blood vessel, based on the PWV and the first blood pressure. The at least one processor may be configured to obtain a blood pressure correction value for correcting a second blood pressure to be obtained, based on the vascular characteristic value.

Methods, systems, and computer-readable medium for determining a systemic vascular resistance (SVR), by receiving a systolic blood pressure (SBP) and a diastolic blood pressure (DPB) from a calibrated photoplethysmography (PPG) device, receiving a pulse transit time (PTT) from the PPG device, determining a stroke volume based on the PTT, determining a mean arterial pressure (MAP) based on the SBP and the DBP, receiving a heart rate, determining a cardiac output based on the heart rate and the stroke volume, determining a first value based on a right atrial pressure (RAP) or central venous pressure (CVP) and the map, determining a second value based on the first value and the cardiac output, and determining a SVR based on the second value and a factor.

The present disclosure describes a wearable monitoring platform capable of capturing and transmitting a wide range of physiological, environmental, and positional data in both clinical and field settings. The system centers around a reusable base unit housed in a partially flexible enclosure, incorporating multi-modal sensors, a controller, edge-processing capabilities, and a dynamic multi-mode communication interface. The wearable is expandable through smart cable modules that provide additional sensing capabilities such as multi-lead electrocardiogram ("ECG"), photoplethysmography ("PPG"), pulse transit time, electroencephalography, and fetal monitoring.

A system and method for contactless determination of pulse-transit time from a received image sequence. The method including: determining hemoglobin concentration (HC) signals over time at a first region of interest (ROI) and a second ROI, the first ROI and the second ROI forming a pair of ROIs, the second ROI located downstream from the first ROI along a common pulse wave path; determining a pulse transit time based on a time difference between peaks in the HC signals; and outputting the pulse transit time. The method can further include determining pulse wave velocity (PWV) using the determined PTT and a distance between the pair of ROIs, and outputting the determined PWV. The method can further include determining an estimate of blood pressure using the determined PWV with a trained machine learning model, and outputting the determined estimate of blood pressure.

A system for measuring the propagation time of light pulses between at least two cells. The presented system further enables the calculation of the distance between at least two units (101a, 101b), and the successive derivative of the distance with respect to time, in different configurations. Bidirectional light time transfer between the two cells is used to calculate the propagation time of the light pulses generated by the light source of each cell.

A system and method for contactless determination of pulse-wave velocity or pulse-transit time from a received image sequence. The method including determining one or more tracked points on the body-part; tracking displacement of the one or more tracked points over a measurement period; determining a ballistocardiogram signal by determining a derivative of the displacement of the one or more tracked points; determining a pulse wave signal of the subject captured in the image sequence based on bit values from a set of bitplanes that represent hemoglobin concentration changes; determining the pulse-transit time or the pulse-wave velocity by determining a phase shift between the pulse wave signal and the ballistocardiogram signal; and outputting the pulse-transit time or the pulse-wave velocity.

The present invention relates to a method for determining a pulse wave velocity and / or a pulse transit time of a patient. The method comprises receiving at least two seismocardiograms of the patient, wherein each seismocardiogram at least partially comprises a heartbeat of the patient and determining a first seismocardiogram template, wherein the first seismocardiogram template is at least partially based on the at least two seismocardiograms. The method further comprises determining a time shift with respect to the first seismocardiogram template for each of the at least two seismocardiograms, shifting each of the at least two seismocardiograms based on the determined respective time shift and determining a second seismocardiogram template, wherein the second template is based on the at least two time-shifted seismocardiograms.

Computing device and method using machine learning for pulmonary artery pressure measurement based on electrical impedance tomography. The following steps are repeated n times: (i) inject an alternating electrical current between a pair of electrodes, the pair of electrodes being located on a belt, the belt being positioned around the chest of a person; (ii) determine corresponding voltage values between m pairs of electrodes located on the belt. The determined n*m voltage values are transmitted to the computing device. The computing device executes a machine learning engine, the machine learning engine using a predictive model stored at the computing device for inferring outputs based on inputs. The inputs comprise the determined n*m voltage values. The outputs comprise a matrix of values representative of at least one of: lung perfusion, pulse transit time values and pulmonary artery pressure values.

A method for determining distance values ​​comprises: transmitting a transmitted signal with at least one transmitted pulse and receiving a received signal with at least one received pulse; measuring at least one pulse transit time based on the transmitted signal, the received signal, and a periodic time reference signal; and determining a distance value based on the pulse transit time; wherein measuring the pulse transit time comprises determining at least one signal section duration, which represents at least a portion of the pulse transit time, as a function of a plurality of mutually different reference times that are distributed over a period length of the time reference signal.

The application discloses a non-contact blood pressure measurement method based on pulse transmission time, and relates to the technical field of medical health monitoring.The chest and wrist of a target are simultaneously monitored by a radar device, and the pulse transmission distance and time are calculated, thereby significantly improving the blood pressure monitoring precision, and overcoming the limitation that the traditional method only relies on a single pulse signal to cause insufficient information amount; meanwhile, by utilizing micro kinetic energy accumulation and point cloud modeling technology, the key parts can be accurately positioned and the signal quality can be enhanced under complex environment, the signal-to-noise ratio is effectively improved, and the sensing problem under the low signal-to-noise ratio environment is solved.In addition, the pulse wave signal is processed through a series of enhancement algorithms, reliable extraction of weak physiological signals is realized, and the non-contact blood pressure monitoring is more accurate and reliable.Based on the calculation method of the human physiological model, the blood pressure measurement result has a clear physiological basis, and the problem that the neural network mapping is not interpretable is avoided.

The invention discloses a non-contact blood pressure measurement method based on pulse transmission time, relates to the technical field of medical health monitoring, and aims to monitor the chest and the wrist of a target simultaneously through radar equipment and calculate the pulse transmission distance and time, so that the blood pressure monitoring precision is remarkably improved; the limitation of insufficient information amount caused by only depending on a single pulse signal in a traditional method is overcome; meanwhile, by utilizing the micro-motion energy accumulation and point cloud modeling technology, the key part can still be accurately positioned and the signal quality can be enhanced in a complex environment, the signal-to-noise ratio is effectively improved, and the sensing problem in a low signal-to-noise ratio environment is solved. In addition, the pulse wave signals are processed through a series of enhancement algorithms, reliable extraction of weak physiological signals is achieved, and non-contact blood pressure monitoring is more accurate and reliable. Based on a calculation method of a human physiological model, a blood pressure measurement result has a clear physiological basis, and the problem that neural network mapping cannot be explained is avoided.

A system and method for determining blood flow using multi-wavelength photoplethysmography is provided. The method including: receiving the photoplethysmography signals from an optical input sensor positioned to capture the photoplethysmography signals from the skin of a user, the photoplethysmography signals including at least two different optical wavelengths; determining arteriolar pulse transit time using time delays determined between the photoplethysmography signals of different wavelengths; determining skin blood flow as a function of the determined arteriolar pulse transit time; and outputting the skin blood flow.

The present application discloses a method and apparatus for blood pressure detection, applicable to electronic devices. The method may include: acquiring a user's first photoplethysmography (PPG) signal, and determining the user's first electrocardiogram (ECG) signal based on the first PPG signal; performing peak detection on the first PPG signal and the first ECG signal to determine the user's first pulse transit time; performing a first quality test on the first ECG signal and the first pulse transit time, and if the result of the first quality test is determined to be normal, determining the user's blood pressure value based on the first pulse transit time. The present application can improve the accuracy of blood pressure detection results and reduce the cost of blood pressure detection.

The present invention provides a method and a device for calibrating a blood pressure estimation model for determining tonoarteriogram (TAG) signals, which relates to a cross field between biomedicine and scientific engineering. The method comprises: after applying a first pressure to a first preset location, determining individual pulse transit time (PTT) of a respective pulse wave at a preset region during a preset movement process in a plurality of preset time periods; for each of the preset time period, acquiring a first pressure at the respective first moment of time and a first height difference of the first preset location relative to a heart location; acquiring a second pressure according to the first pressure at all of the first moment of time; determining a sample blood pressure information within the preset time period according to the second pressure and the first height difference to calibrate the blood pressure estimation model, and obtaining a continuous beat-to-beat blood pressure information according to the blood pressure estimation model, obtaining TAG signals according to the beat-to-beat blood pressure information and a target PPG signal. The present invention calibrates the blood pressure estimation model without the need of a cuff-type blood pressure measurement device, and a high-precision TAG signals can be obtained.

The invention relates to a method for determining distance values, comprising: emitting a transmit signal having at least one transmit pulse and receiving a receive signal having at least one receive pulse; measuring at least one pulse propagation time on the basis of the transmit signal, the receive signal and a periodic time reference signal; and determining a distance value on the basis of the pulse propagation time; wherein measuring the pulse propagation time comprises determining at least one signal portion duration, which represents at least one part of the pulse propagation time, as a function of a plurality of different reference times distributed over a period length of the time reference signal.

This application relates to a method and device for monitoring vascular parameters. The method includes: acquiring finger pressure information and finger arterial physiological information during a monitoring period; obtaining the actual value of the oscillation envelope using the finger arterial physiological information, and obtaining the actual value of the pulse transit time using the finger arterial physiological information; obtaining a first model; obtaining a second model; and simultaneously optimizing the objective function using the first and second models to obtain estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on a first error and a second error, where the first error is obtained from the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model, and the second error is obtained from the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model. This method can improve the accuracy and robustness of vascular parameter estimation.

One example medical device system and method includes an accelerometer circuit configured to generate at least one signal, a memory, and a processing circuit coupled to the accelerometer circuit and the memory. The processing circuit is configured to determine a first plurality of pulse transit times (PTTs), determine a sit-to-stand transition based on the at least one accelerometer signal, determine a second plurality of PTTs after the sit-to-stand transition based on the sit-to-stand transition occurring, and determine a likelihood that a person, e.g., a patient, can have fallen based on the first plurality of PTTs and the second plurality of PTTs.

The application discloses an old person emotional accompanying and health management large model for fusing child voice synthesis, and relates to the technical field of intelligent old people care and emotional accompanying. The system continuously collects physiological data such as blood pressure, heart rate and pulse transit time of the old person, calculates the deviation degree of each physiological characteristic parameter and combines the deviation degree into a physiological deviation vector; converts the deviation degree into an objective condition description text, generates a care feeling description text from the child's perspective by using a lightweight language model; analyzes the emotional tone and concern degree score from the text, and maps to generate voice emotional control parameters containing speech speed factors and fundamental frequency offset; after the dialogue is triggered, the child character reply text, the child voiceprint embedding vector and the voice emotional control parameters are input into the voice synthesis engine, and the child digital avatar voice suitable for the real-time physical condition of the old person is output. The application synchronizes the emotional expression of the child voice with the health condition of the old person, and improves the realism and empathy effect of the digital avatar accompanying.

The present disclosure describes a system for detecting abnormal blood pressure or blood volume in a user, the system comprising a processing system; a pulse transit time (PTT) detection system for providing a PTT signal indicative of a PTT of the user to the processing system, wherein PTT of the user is used as a surrogate for a blood pressure (BP) of the user; and an electrodermal activity (EDA) detection system for providing an EDA signal indicative of an EDA of the user to the processing system; wherein the processing system processes the PTT signal and the EDA signal to determine an index indicative of an abnormal blood pressure or blood volume of the user.

In one embodiment, a method includes acquiring a motion signal by an IMU sensor of a wearable device and acquiring a PPG signal by a PPG sensor of the wearable device, where the PPG sensor is synchronized with the IMU sensor. The method further includes determining, from the IMU signal, an AVO of a wearer of the wearable device; determining from the PPG signal, a pulse arrival time of the wearer; and estimating, based on (1) the AVO determined from the IMU signals and (2) the pulse arrival time determined from the PPG signal, a PTT of the wearer.

A self-training system is provided, including: a respiration measurement unit, a blood oxygen measurement unit, a blood pressure measurement unit, an electrode unit, an audio stimulation unit, a display unit and a control unit. The display unit displays a virtual image including a plurality of display areas when the display unit is in a normal mode. Said display areas respectively correspond to a pulse transit time data, a brainwave signal, a heart rate variability data, a breathing signal, a heart rate data, a blood pressure data and a blood oxygen saturation signal. The control unit controls the said display areas to display respective real-time display charts according to respective signals and data, and controls the audio stimulation unit to play a binaural beats with frequency following response so that the user can receive stimulations and guidance to lower blood pressure and relieve physiological and psychological stress.

An electronic device according to one embodiment may comprise a communication module and at least one processor. The at least one processor may be configured to receive a first PPG signal obtained by a first wearable device from the first wearable device and receive a second PPG signal from a second wearable device through a communication circuit. The first wearable device may be worn at a first location on a user and the second wearable device may be worn at a second location on the user. The at least one processor may be configured to obtain a pulse transit time (PTT) for which pulse waves are transmitted from the first location to the second location, on the basis of the first PPG signal and the second PPG signal. . The at least one processor may be configured to obtain the distance between the first wearable device and the second wearable device. The at least one processor may be configured to obtain a pulse wave velocity (PWV) at which pulse waves are transmitted, on the basis of the distance and the PTT. The at least one processor may be configured to obtain a first blood pressure by using a pulse wave analysis (PWA) method on the basis of the first PPG signal and / or the second PPG signal. The at least one processor may be configured to obtain a blood vessel characteristic value related to the characteristics of blood vessels, on the basis of the PWV and the first blood pressure. The at least one processor may be configured to obtain a blood pressure correction value for correction of a second blood pressure that is to be obtained, on the basis of the blood vessel characteristic value.

A system for measuring the propagation time of optical pulses between at least two units. The presented system further enables the calculation of the distance between at least two units (101a, 101b), and the successive derivatives of said distance with respect to time, in various configurations. The bidirectional optical time transfer between two units is used for the calculation of the propagation time of optical pulses, which are generated by the optical source of each unit.

Various arrangements for measuring blood pressure using sensor fusion are presented herein. A radio frequency (RF) signal is transmitted, and a radar sensor of the fixture receives the RF reflected signal. The RF reflected signal at the first range of distances is analyzed to identify a first pulse pressure waveform (PPW) at the aortic valve of the user. A stationary device receives vital sign data measured by a mobile device at a limb of a user. The vital sign data is analyzed to identify a second PPW at the limb of the user. A pulse transit time from the aortic valve to the limb is determined using the first PPW and the second PPW. Using the PTT, a blood pressure (BP) of the user is determined and an indication of BP is output.

Devices, systems and techniques to measure changes in pulse transit time (PTT) and, in some cases, determine pulse wave velocity (PWV), in a blood vessel to support continuous ambulatory monitoring of PTT and / or PWV. Each heartbeat creates a pressure wave that propagates along the arterial system. A pressure wave may travel faster along a rigid artery when compared to a more flexible artery. In this manner, PTT may be an indirect indicator of blood vessel flexibility and patient health.

A hearing aid comprising a physiological sensor is disclosed, the hearing aid being comprised in a system comprising an input unit, an output unit, a signal-to-noise ratio estimator, a processing unit, a memory unit, at least a first and a second physiological sensor; the system being configured to: determine, based on the first physiological sensor, a first time point corresponding to a first maximum upstroke point of a first measured parameter; determine, based on the second physiological sensor, a second time point corresponding to a second maximum upstroke point of a second measured parameter; determine a current pulse transit time by calculating a time difference between the first time point and the second time point; and determine a current listening effort of a hearing aid user based on the current pulse transit time and a stored reference set of signal-to-noise ratios and pulse transit times.

In one embodiment, a method includes acquiring a motion signal by an IMU sensor of a wearable device and acquiring a PPG signal by a PPG sensor of the wearable device, where the PPG sensor is synchronized with the IMU sensor. The method further includes determining, from the IMU signal, an AVO of a wearer of the wearable device; determining from the PPG signal, a pulse arrival time of the wearer; and estimating, based on (1) the AVO determined from the IMU signals and (2) the pulse arrival time determined from the PPG signal, a PTT of the wearer.