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Pulse oximetry fundamentals and MCUs

23 Jan 2014  | Jayaraman Kiruthi Vasan

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Pulse oximetry is employed to non-invasively monitor oxygen saturation in blood. It employs an indirect method of assessing these conditions immediately just by clipping a sensor onto your finger or ear. Use of pulse oximeters during surgical procedures has been made mandatory in most countries, and home users can now acquire comparable instruments at affordable prices.

The pulse oximeter provides a way of estimating how well the blood oxygenation takes place. Oxygen saturation (SpO2) is normally above 95 per cent for healthy individuals. Levels below this value can be an indication of lung or breathing problems, and monitoring the levels helps determine the need for and the efficacy of treatment. Typically patients suffering from chronic obstructive pulmonary disease (COPD), asthma, pneumonia, bronchiolitis, and the like benefit from using pulse oximeters.

A pulse oximeter leverages the pulsatile variations caused by surges in blood flow in your arteries as your heart beats. This blood flow has an effect on the optical density of tissues in the red and infra-red wavelengths, which the oximeter exploits to compute the arterial oxygen saturation level without any need for active calibration. Takuo Aoyagi of Nihon Kohden in Tokyo invented the method in 1972 and the device was clinically tested on patients and reported by a surgeon Susumu Nakajima in 1975.

In particular, a pulse oximeter measures the light absorbance of the tissue at two different wavelengths (Red and Infra-red) and determines the oxygen saturation (SpO2 per cent) of arterial blood. To differentiate between the arterial blood and other absorbing tissues and compounds, it utilises the pulsatile nature of blood by measuring the changes that take place.

Typically, the sensor consists of an ergonomically-designed clip that houses a photodiode on one side and two LEDs (Red and Infra-red) on the other side. When mounted on, say, a finger, the emitted red and infrared rays pass through the finger to the photodiode. The signal obtained from the photodiode gets amplified, filtered, conditioned and scaled, and processed further digitally.

There are several major factors affecting the signals obtained, such as the finger's thickness, the absorbance coefficient of the tissue medium, differences in intensities between red and infra-red lights, and the like, that need to be accounted for when determining the SpO2 values. Here's a look at the mathematical calculations used to cancel out these factors to make the measurement more accurate.

The Beer-Lambert Law gives us an expression for the emergent intensity of light passing through a medium as:

where In – the emergent light intensity, I0 – incident light intensity, α – absorbance co-efficient of the medium per unit length, and d – the thickness of the medium in unit lengths.

By forming equations for the baseline component (due to the non-moving absorptive components) and the pulsatile component (due to the blood which is pulsating) of the emergent light intensities and then obtaining a ratio, we can eliminate the input light intensity as a variable in the equation. Hence, the change in arterial transmittance is given by:

The infusion of arterial blood has an effect on the thickness of the finger, which is represented by Δd. This variable Δd can be eliminated by measuring arterial transmittance at two different wavelengths (Red and Infra-red) and finding their ratio.

Once the baseline and thickness variables have been eliminated, and after further processing, we can create a ratio of ratios ROS, expressed by dividing αred divided by αIR. This ratio of ratios is the key variable used in calculating the oxygen saturation level.

ROS is can be determined using either of two methods. The Peak and Valley method uses the ratio of the peak of the light's absorption (minimum intensity) during a pulse interval to the valley of the light absorption curve (maximum intensity) for each wavelength. The Derivative method uses the ratio of the absorption curve's time derivatives for each wavelength.

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