Maxim Highlights Techniques to Derive Reliable Sensor Data from Healthcare Wearables

SAN JOSE, Calif., Jan. 22, 2020 /PRNewswire/ -- Getting reliable sensor data from wearables is complex, yet critical in order for users to trust the efficacy of their health trackers. Consider, as an example, an optical heart-rate sensor, which is actually sensing the changes in an electric current. Heartbeats cause the volume of arterial blood to change synchronously with each pulse. The change in volume changes the amount of light absorbed and reflected as it travels through live tissue. When that light exits the tissue and enters a photodetector, it changes the output current. By creating a sensing system that carefully sets up a proper series of "dominos," a current sensor becomes a heart-rate sensor.

This is how most sensors work. Sensors generally make esoteric electrical measurements (capacitance, impedance, current, voltage). But through an elaborate system construct, a physical event of interest (acceleration, pressure, footsteps, distance) is made to change that measurement. Knowing the system construct, we could then interpret the change into a physical parameter, all the while assuming everything else in the sensing system stays constant or at least is well controlled.

But what if the dominos aren't all under the designer's control?

Optical Path of Light
The path that light travels from the source (emitter) to the detector (receiver) is known as the optical path. This path spans across one or more media and any change in those media could interact and affect the light characteristics at the detector. As such, the received light encapsulates all changes in the media along the entire optical path.

For an optical heart-rate sensor, light comes from one or more LEDs and is aimed at live tissue. Before arriving at the tissue, the light has to travel through air and sometimes a layer of cover glass. Air, cover glass, and the surface of the tissue are three different optical media. Similarly, the tissue is not homogenous and could be modeled as successive layers of optical media with different refractive indices.

At the interface of any two media with different optical properties, light could be absorbed (attenuated), reflected (scattered) into the first medium, or transmitted into the second medium. Heart-rate sensing works because one of these media, the capillaries, changes volume over time synchronous to heart rate. The change affects the amount of light absorbed and reflected. Optical system design must make sure that the path most light takes to go from the LED to the photodetector also interacts with the capillaries. Data reliability is compromised when light can reach the photodetector without interacting with the capillaries or when something along the optical path changes unexpectedly.

Light-Attenuating Factors Outside the Designer's Control
Dirt and grime on the cover glass, hair, skin pigment, and color changes of the cover glass are all factors outside of a designer's control. Each medium serves to attenuate light passing through it, in both directions, and each may affect some wavelength of light more than others.

For heart-rate sensing, the important information is carried in the periodicity and not the overall amplitude of the signal. So, as long as the emitter is strong enough, some attenuation should not result in any loss of information. However, if the sensing configuration uses more than one LED or multiple wavelengths, it is possible that light intensity for each LED and/or wavelength would not be affected by the same proportion.

The air gap, or the distance between the skin surface and the optical components, is also outside of a designer's control and can impact the reliability of sensor data. Now, in many wearable applications, water (in the form of, say, sweat or rain) could be present in the "air gap." The resulting combinations and variations are numerous, but we could consider some generalities. When the sensing target is live tissue, which is mostly comprised of water, having water in the air gap actually narrows the difference in refractive index between the air gap and the target. This should allow a proportionately greater amount of light to be transmitted into the tissue, strengthening the sensing mechanism.

Maximizing Signal Path Performance
With everything that could affect the optical signal, it becomes increasingly important that the part of the optical data path that is under the designer's control gives the best signal-to-noise performance. A high-performance design makes discerning the reliability of the sensor data easier.

For example, any light which makes its way to the photodetector but did not enter the target tissue, not just the light emitted from the LED source, adds to the noise of the biosensing signal. Some integrated analog front-end (AFE) devices, like the MAX86140 and the MAX86171, sample any ambient current on the photodetector asynchronous to the LED light source and subtract them from the photodetector current. Indeed these AFEs even anticipate how ambient light conditions could change in typical use cases so that designers can trust that their effects will have little impact on the biosensing signals.

To learn more about the key considerations affecting reliability of sensor data, read this article from Maxim's Ian Chen: "Getting to Reliable Sensor Data: Interaction Between Electronics, Optics, and Mechanic Design."

SOURCE Maxim Integrated Products, Inc.

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