Oximeter signaling: There’s more than meets the eye


Guest blogger, Jess Goodman M.D., is the current President of VitalSines Inc., a company which manufactures health monitoring systems. Dr. Goodman is a physician with 30+ years of experience and currently serves on the University of Toronto Teaching Staff.

Imagine staring at the moon on a clear night with your naked eye. You can make out the shape and the brightness of the moon, but that’s pretty much it. Now, imagine looking at the moon through a telescope. Suddenly you can see the craters on the moon and details you never noticed before. It’s spectacular! The difference between staring up at the moon with your naked eye versus looking at the moon through a telescope is much like what Texas Instruments’ AFE4400 and AFE4490 does for oximeter signals.  The AFE4400 and AFE4490 allows oximeter signals to be acquired at high sampling rates and high resolution. This reveals fine details in the oximeter signal that otherwise would not be apparent. The AFE4400 and AFE4490 removes noise related to ambient light without needing a high pass filter. A high pass filter distorts the pulse signal and makes analysis difficult.

The oximeter signal is information rich. However, only heart rate and blood oxygen saturation are used clinically at present. The oximeter signal is potentially able to provide a wide variety of physiological information. This includes blood pressure in the arm and blood pressure close to the heart, aortic pulse wave velocity, aortic stiffness, arterial compliance, cardiac stroke volume/output, respiratory rate and respiratory rhythm. The oximeter signal can even serve as a unique personal ID for identification purposes.

High oximeter sampling rate and resolution allow Aortic pulse wave velocity (PWV), a valuable health indicator, to be extracted from the oximeter signal. PWV is the speed with which waves travel along the body’s arteries. It will be shown below how PWV can be used to follow changes in blood pressure and how it can be used to predict a person’s lifespan.

PWV is largely determined by arterial stiffness and arterial pressure. Stiffness of the Aorta, the body's largest blood vessel, is a predictor of a person’s risk of death from all causes. Changes in Aortic pulse wave velocity due to aging greatly affect pulse shape seen in the fingertip oximeter signal. In the diagram below the pulse shape of an older person and a younger person show a great difference.

Analysis of the shape of the arterial pulse wave can provide an estimate of a person’s Aortic PWV, their Aortic Stiffness and allows tracking of blood pressure changes.

The pulse signal is made up of three waves, a Primary Wave, a Reflected Wave and a Diastolic Wave. When the heart beats a Primary Wave is generated and travels down the Aorta. When the Primary Wave reaches the bottom of the abdominal cavity it is reflected back to the heart. Timing between the Primary Wave and Reflected Waves is very important for health.

The speed with which the Reflected Wave travels depends on Aortic PWV.  PWV is low when we are young and increases with age. The Reflected Wave in a young person returns to the heart just as the heartbeat is ending. As the Reflected Wave’s speed increases with aging, it returns to the heart earlier. When it comes back too early, it collides with the outgoing flow of blood. This forces the heart to beat harder, increases blood pressure and reduces blood flow to the heart muscle between contractions. By detecting the height of the Reflected Wave’s peak and comparing this to the height of the Primary Wave, an Aortic Stiffness score can be calculated that can then be used to compare a person’s Physiological Age to their Chronological Age and display estimated Lifespan. This is shown in the screen shot below.

The same index between height of the Reflected Wave peak and the Primary Wave can be used to track blood pressure on a pulse to pulse basis. In the screenshot below a subject stands up at the 30 second mark. Blood pressure is seen to fall and then rise as the body adjusts to the stress of standing.

The oximeter signal obtained using high resolution and high sampling rate can also be used to reconstruct the arterial pulse at the wrists (radial artery), the elbow (brachial artery) and the Aorta (close to the heart). After calibration with a blood pressure cuff on the arm, it is even possible to use the finger pulse to follow true Systolic and Diastolic Blood Pressure on a continuous basis using a simple wrist watch type device with an oximeter sensor in its base.

Using the free HemoLab pulse analysis software created by Dr. Harald Stauss the oximeter signal can be transformed, using scientifically validated transfer functions, into first the radial artery pressure pulse and then the Aortic pressure pulse. The Aortic pressure pulse is then divided into Primary and Secondary waves and these when compared provide a close estimate of Aortic PWV. This can be used to calculate blood pressure close by the heart. This information would provide a more effective and safer way for medical personnel to manage Hypertension. An article authored by Dr. Stauss and his colleagues using HemoLab analysis on the oximeter signal to calculate Reflected Wave properties can be reviewed at here.

A screen shot of the Hemolab display analyzing my finger pulse is shown below. The oximeter pulse is labeled DVP (Digital Volume Pulse) because the volume changes in the arteries of the finger (digits) are responsible for oximeter signal fluctuations.

In the future there will be many personal health sensor systems worn on the body using oximeter sensors. The AFE4400 and AFE4490 will allow these sensors to provide a valuable understanding of health.

In my next blog I will describe use of an AFE4400 patch sensor worn on the palm as a way to continuously follow many aspects of health simply and the ways health data will transform health care globally.

In the meantime, check out my previous posts to learn how advanced technology, such as virtual hospitals, is being used to signal health care providers when someone’s health status changes to prompt intervention, avoiding hospital readmission. Or, how the AFE4400 and the AFE4490 Oximeter SoC allows high quality acquisition of the arterial pulse signal at the wrist in ways not previously possible.

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