16 results about "Pulse Wave Transit Time" patented technology

The invention relates to the technical field of deep learning, in particular to a dialysis hypotension risk prediction system and method based on deep learning, and the system comprises a multi-point signal collection module, a signal processing module, a multi-scale causal expansion convolutional network prediction module, an osmotic pressure correction module and a dialysis plan automatic adjustment module. The method comprises the following steps: synchronously collecting physiological signals of a patient through a finger tip photoelectric volume sensor and a radial artery piezoelectric sensor array, carrying out band-pass filtering and morphological refinement processing on the signals, extracting features, and calculating pulse wave conduction time and a change rate thereof; inputting the characteristic parameters into a multi-scale causal expansion convolutional network to predict the hypotension risk in dialysis; dynamically correcting the prediction result according to electrolyte monitoring data; based on the corrected risk, a hierarchical response strategy is adopted to automatically adjust dialysis parameters, a multi-scale causal expansion convolutional network is adopted to capture physiological parameter changes on different time scales at the same time, and high-precision prediction of hypotension is achieved.

A physiological information display apparatus includes a reception unit configured to receive a start signal and an end signal, the start signal indicating a start timing of a treatment for a subject, the end signal indicating an end timing of the treatment, a calculation unit configured to calculate a moving average value of a pulse wave transit time of the subject, a hemodynamic parameter of the subject, using the calculated moving average value, and a change rate of the hemodynamic parameter in a period from the start timing to the end timing, based on the start signal and the end signal received by the reception unit, and a display controller configured to output, to a display, the change rate calculated by the calculation unit.

A pulse wave transit time measurement device includes a neck band, a pair of electrocardiographic electrodes detecting an electrocardiographic signal, a photoplethysmographic sensor detecting a pulse wave signal, and a pulse wave transit time calculator calculating a pulse wave transit time based on a peak time difference between the electrocardiographic signal detected by the electrocardiographic electrodes and the pulse wave signal detected by the photoplethysmographic sensor. The photoplethysmographic sensor is positioned in or substantially in a central region of the neck band at a location at which the photoplethysmographic sensor is in contact with a neck of a user at or near a midline of the neck on the backside when the neck band is worn around the neck of the user.

A pulse wave transit time measurement device includes a pulse wave transit time calculator that calculates a pulse wave transit time based on a peak time difference between an electrocardiographic signal and a pulse wave signal, a posture classifier that classifies time serial data of the pulse wave transit time based on a posture detected by an acceleration sensor, and a fluctuation identifier that sets a reference posture from among classified postures, corrects, in conformity with the reference posture, the time serial data of the pulse wave transit time classified into the posture different from the reference posture, and determines fluctuations in the pulse wave transit time based on the time serial data of the pulse wave transit time in the reference posture and the time serial data of the pulse wave transit time having being corrected.

To provide a wearable physiological signal detection system applicable to an application scene such as in-home-care, walking support, labor safety and health management, and voluntary health prediction.SOLUTION: A wearable physiological signal sensing system disclosed in the present invention includes: a system circuit board having an upper surface and a lower surface; a stethoscope installed on the lower surface for sensing a cardiac sound signal of a user; a plurality of electrocardiographic electrodes installed on the lower surface, adjacent to the stethoscope for sensing an electrocardiographic signal of the user; and a blood oxygen concentration analyzer installed on the upper surface for sensing a blood oxygen concentration and a pulse wave signal of the user. The system circuit board is electrically connected to the stethoscope, the plurality of electrocardiographic electrodes, and the blood oxygen concentration analyzer. The system circuit board acquires a pulse wave transmission time of the user through comparison between the electrocardiographic signal and the pulse wave signal or comparison between the cardiac sound signal and the pulse wave signal, and estimates a continuous blood pressure of the user on the basis of the pulse wave transmission time.SELECTED DRAWING: Figure 13(a)

The pulsation is measured, and the pulse transit time (PTT) is measured by selecting the pulsation at two places where the displacement of the skin is large.SOLUTION: A pulsation measuring device 1 includes a radar device 2 and a signal processing device 3, and the radar device 2 is provided at least at three positions where the skin of a human body H can be scanned and scans the skin at the positions to output radar data as a biological signal. The signal processing device 3 acquires the output radar data, detects the displacement of the skin in the vertical direction at the position of the human body H scanned by the radar device 2 to specify the pulsation of the human body H, selects two places of the biological signal of the human body H where the displacement of the skin of the human body H is large, and calculates the pulse transit time (PTT) between the two places.SELECTED DRAWING: Figure 1

The application relates to a pulse wave transmission velocity measurement system and method, wherein the pulse wave transmission velocity measurement system comprises a chest signal acquisition device, a wrist signal acquisition device, a finger signal acquisition device and a data processing device; the chest signal acquisition device is used for acquiring a first signal, the first signal at least comprising an electrocardiosignal, and sending the first signal to the data processing device; the wrist signal acquisition device is used for acquiring a second signal, the second signal at least comprising a wrist pulse wave signal, and sending the second signal to the data processing device; the finger signal acquisition device is used for acquiring a third signal, the third signal at least comprising a finger pulse wave signal, and sending the third signal to the data processing device; and the data processing device is used for determining a pulse wave transmission velocity according to the first signal, the second signal and the third signal. The application solves the problem of low measurement accuracy of the pulse wave transmission velocity, and realizes the technical effect of accurately measuring the pulse wave transmission velocity.

A blood pressure prediction method and apparatus, an electronic device, and a computer-readable storage medium. The method includes: synchronously collecting physiological signals, the physiological signals include electrocardiogram signals, pulse signals and heart sound signal; extracting features from the physiological signals to obtain signal features, the signal features include pre-ejection duration and pulse wave transit time; and inputting the signal features into a pre-trained blood pressure prediction model to cause the blood pressure prediction model to output a blood pressure prediction result.

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 application relates to the technical field of wearable medical devices, in particular to a sleeveless continuous blood pressure monitoring method based on fusion of double-path pulse wave transit time and posture. The sleeveless continuous blood pressure monitoring method based on fusion of double-path pulse wave transit time and posture comprises the following steps: S1, device wearing and system initialization; S2, multi-modal signal synchronous acquisition; S3, signal pretreatment; S4, effective measurement state judgment; S5, wrist and heart height difference calculation; S6, pulse wave feature point recognition and transit time calculation; S7, initial blood pressure value calculation; S8, hydrostatic pressure correction; S9, result output and storage; and S10, returning to step S2 and performing next blood pressure measurement. The technical problems that blood pressure monitoring cannot be continuously measured, is easily disturbed by body position changes, has low measurement precision and lacks individualized calibration in the prior art are solved.

This invention provides a training method for a blood pressure prediction model and a method for predicting blood pressure data. The training method for the blood pressure prediction model includes: acquiring data from a wearable device to obtain a raw data sequence; preprocessing the raw data sequence to obtain a standard data sequence; extracting features from the standard pressure signal sequence and the standard blood pressure sequence based on peak and trough values ​​to obtain a pressure feature sequence, a blood pressure feature sequence, and a pulse wave propagation time sequence; extracting features from the standard acceleration sequence and the standard angular velocity sequence based on the rate of change and frequency to obtain a motion intensity sequence; fusing the pressure feature sequence, the blood pressure feature sequence, the pulse wave propagation time sequence, and the motion intensity sequence to form a multidimensional feature sequence; and training the blood pressure prediction pre-training model based on the multidimensional feature sequence to obtain the blood pressure prediction model. The blood pressure prediction model obtained by this invention has higher accuracy in predicting blood pressure.

The invention discloses a pulse wave velocity measuring method, device and equipment and a medium. The measuring method comprises the following steps: acquiring an electrocardiogram signal of a heart; acquiring a pulse wave signal of any detection point of the body surface artery; performing second derivative operation on the pulse wave signal to obtain a pulse wave acceleration signal; according to the pulse wave acceleration signal and the electrocardiogram signal, the pulse wave propagation time difference from the heart to the detection point is determined; acquiring a curve distance from the heart to the detection point; calculating the ratio of the curve distance to the pulse wave propagation time difference to obtain the pulse wave speed. According to the method, the limitation that the traditional pulse wave speed must depend on synchronous measurement of two arteries is eliminated, the stable and reliable pulse wave speed can be obtained only through the single-point pulse wave signal and the electrocardiogram signal, and the multi-point detection requirement of the traditional method is avoided; and errors of single-point pulse wave measurement are made up by means of high time precision of the electrocardiogram signals, so that clinical credibility of pulse wave speed detection is guaranteed.

This invention discloses a continuous non-invasive blood pressure monitoring system based on fingertip photoplethysmography (PPG). The system includes: an intelligent finger cot terminal for acquiring fingertip PPG signals and adjusting the fingertip contact pressure in real time using a closed-loop control formula to maintain a constant pressure state on the finger blood vessels; a mobile computing terminal for receiving fingertip PPG signals and performing preprocessing operations on the fingertip PPG signals; and a cloud service platform for calculating the preprocessed fingertip PPG signals based on a preset blood pressure calculation model to obtain a continuous blood pressure waveform and estimate hemodynamic parameters based on the continuous blood pressure waveform. The preset blood pressure calculation model is specifically a pulse wave analysis model, a pulse wave propagation time model, or a deep learning mapping model. The hemodynamic parameters are specifically stroke volume and cardiac output. Through the mobile computing terminal and the cloud service platform, continuous arterial pressure waveform reconstruction and physiological parameter calculation are realized, and long-term monitoring accuracy can be maintained through a periodic calibration mechanism.

The invention discloses a wearable physiological signal sensing system which comprises a system circuit board provided with an upper surface and a lower surface, a stethoscope arranged on the lower surface and used for sensing heart sound signals of a user, a plurality of electrocardio electrodes arranged on the lower surface and adjacent to the stethoscope and used for sensing electrocardio signals of the user, and an oximeter arranged on the upper surface and used for detecting the heart sound signals of the user. The blood oxygen sensor is used for sensing blood oxygen concentration and pulse wave signals of a user. The system circuit board is electrically connected with the stethoscope, the plurality of electrocardio electrodes and the oximeter, the system circuit board obtains the pulse wave transmission time of the user by comparing the electrocardio signal with the pulse wave signal or comparing the heart sound signal with the pulse wave signal, and the continuous blood pressure of the user is calculated according to the pulse wave transmission time.

The invention discloses a blood pressure measuring method based on a smart phone. According to the method, chest acceleration and fingertip pulse photoplethysmography (PPG) signal data are obtained by using a built-in accelerometer and a rear camera of the smart phone without any external equipment. After the collected signals are preprocessed, the signal quality is evaluated based on a template matching method, and when the signal quality score is lower than a preset threshold value, the blood pressure result is not output, and operation suggestions are given. For high-quality signals, waveform characteristics and pulse wave transit time (PTT) are calculated, and a machine learning model is adopted for blood pressure measurement. Through quality evaluation, feature processing and machine learning technologies, the problems of low measurement accuracy and susceptibility to interference in a complex environment are solved, the blood pressure measurement reliability of the mobile terminal equipment is improved, and a blood pressure measurement scheme which is more convenient than a traditional blood pressure measurement method is realized.

A signal processor of a blood pressure estimating device includes a pulse wave transit time acquirer that acquires a pulse wave transit time based on a pulse wave signal detected by a photoplethysmographic sensor and an electrocardiographic signal, a time measurer that measures a time elapsed from when acquisition of the pulse wave transit time is started, and a blood pressure estimator that estimates a blood pressure based on a predetermined relationship between the pulse wave transit time and the blood pressure. The photoplethysmographic sensor is in contact with a neck of a user at a position not directly over a carotid artery when the pulse wave transit time is acquired, and the blood pressure estimator estimates the blood pressure after the measured elapsed time has become a predetermined time or more.