Wearable Pulse Waveform Measurement System and Method

Abstract

A pulse waveform measurement system includes an LED light source providing an incident beam having a predetermined wavelength onto a radial or other artery, samples reflected light at a predetermined sample rate, computes, and displays a pulse waveform and various parameters associated therewith. The wavelength and sample rate are set so as to provide desired data quality.

What is claimed is: 
     
         1 . A computer-based wearable pressure pulse waveform measurement device for determining one or more health parameters or health conditions, comprising:
 a first light source adapted to transmit light to a blood carrying artery at a measurement location;   an optical sensor adapted to receive a reflected light in response to the transmitted light from the blood carrying artery;   a processor configured to measure the reflected light and to convert the reflected light into measured digital pulse waveform measurement (PWM) data indicative of an entire shape of one cycle of the pressure pulse waveform in the blood carrying artery at the measurement location; and   the processor further configured to receive digital reference pulse waveform data, and configured to compare the entire shape of one cycle of the measured digital PWM data to an entire shape of one cycle of the digital reference pulse waveform data and to determine the one or more health parameters or health conditions, continuously, in real-time using machine learning.   
     
     
         2 . The device of  claim 1 , wherein the light source is transmitted to a radial artery. 
     
     
         3 . The device of  claim 1 , wherein the first light source comprises an LED (Light Emitting Diode) having a wavelength in the range of 500-640 nm. 
     
     
         4 . The device of  claim 1 , further comprising a second light source adapted to transmit light to the blood carrying artery at the measurement location, and wherein the optical sensor is disposed between the first and second light sources, and wherein the reflected light being in response to light from the first and second light sources such that the reflected light is distributed substantially uniformly across the sensor. 
     
     
         5 . The device of  claim 1 , wherein the processor measures the reflected light at a sampling rate in the range of 100-500 Hz. 
     
     
         6 . The device of  claim 1 , wherein the processor calculates at least one pressure pulse waveform parameter comprising at least one of p 2 , n 1 , p 3 , T 1 , ΔT, AP 1  and AP 2 . 
     
     
         7 . The device of  claim 6 , wherein the at least one health parameter, comprises at least one of: stiffness index, mean arterial pressure, stroke volume, augmentation index, blood pressure and heart rate. 
     
     
         8 . The device of  claim 1 , wherein the processor identifies a period from the measured pulse waveform by finding the time between pulses obtained by at least one of time domain convolution and frequency domain analysis. 
     
     
         9 . A computer-based method for determining one or more health parameters or health conditions by measuring a pressure pulse waveform of a user using a portable, wearable device, the method comprising:
 providing an optical source light from at least one light source disposed in the device, the optical source light being incident on a blood carrying artery at a measurement location on the user;   measuring a reflected light, with an optical sensor disposed in the device, in response to the optical source light, the reflected light being indicative of the pressure pulse waveform associated within the blood carrying artery at the measurement location;   converting the reflected light into measured digital pulse waveform measurement (PWM) data, indicative of an entire shape of one cycle of the pressure pulse waveform in the blood carrying artery of the user at the measurement location;   receiving digital reference pulse waveform data; and   comparing the entire shape of one cycle of the measured digital PWM data to an entire shape of one cycle of the digital reference pulse waveform data and determining the one or more health parameters or health conditions, continuously, in real-time using machine learning.   
     
     
         10 . The method of  claim 9 , further comprising: identifying a period from the PWM data by finding a time between pulses obtained by at least one of: time domain convolution and frequency domain analysis. 
     
     
         11 . The method of  claim 9 , further comprising:
 extracting pulse waveform segments from the PWM data; and   averaging the extracted pulse waveform segments, as averaged pulse waveform segments.   
     
     
         12 . The method of  claim 11 , wherein the pulse waveform segments are extracted by finding a time between pulses obtained by at least one of time domain convolution and frequency domain analysis. 
     
     
         13 . The method of  claim 11 , further comprising performing a mathematical curve fit to the averaged pulse waveform segments to obtain a fitted pulse waveform curve. 
     
     
         14 . The method of  claim 13 , wherein the fitted pulse waveform curve comprises at least one of: exponential and Gaussian. 
     
     
         15 . The method of  claim 9 , further comprising: convolving the PWM data with a standard pulse waveform curve. 
     
     
         16 . The method of  claim 15 , wherein the convolving is repeated multiple times in an iterative fashion. 
     
     
         17 . The method of  claim 9 , wherein the at least one light source comprises an LED (Light Emitting Diode) having a wavelength in the range of 500-640 nm. 
     
     
         18 . A computer-based method for measuring a pressure pulse waveform using a wearable device, comprising:
 providing an optical source light incident on a blood carrying artery;   measuring a reflected light in response to the optical source light;   providing measured digital pulse waveform measurement (PWM) data indicative of an entire shape of one cycle of the pressure pulse waveform associated within the blood carrying artery in response to the reflected light having sufficient signal quality to determine a plurality of pressure pulse waveform parameters;   wherein the plurality of pressure pulse waveform parameters comprises: p 1 , p 2 , n 1 , p 3 , T 1 , ΔT, A P1 , and A P2 ;   receiving digital reference pulse waveform data; and   comparing the measured PWM data to an entire shape of one cycle of the reference pulse waveform data and determining at least one of the pressure pulse waveform parameters, continuously, in real-time using machine learning.   
     
     
         19 . The method of  claim 18 , further comprising: computing from the at least one pressure pulse waveform parameter, at least one health parameter, comprising at least one of: stiffness index, mean arterial pressure, stroke volume, augmentation index, blood pressure and heart rate. 
     
     
         20 . The method of  claim 19 , further comprising: providing an alert when the at least one health parameter is in an unsafe range.