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We get quite a few inquiries here at Valencell about optical heart rate monitoring and how it works. So we put together this guide to provide some answers to some of the most common questions we get on optical heart rate monitoring. This is a long post, so here’s a quick outline in case you want to scrool to a particular section:

How does optical heart rate monitoring (OHRM) work?

How does OHRM technology work?

This must be a new innovation, right? A brief history of PPG

What are the primary challenges with OHRM wearables?

So how do I get OHRM right?

What metrics you can get from PPG?

What form factors are using OHRM?

How are OHRM devices being used today?

How does Optical Heart Rate Monitoring (OHRM) work?

Most wearables with heart rate monitors today use a method called photoplethysmography (PPG) to measure heart rate. PPG is a technical term for shining light into the skin and measuring the amount of light that is scattered by blood flow. That’s an oversimplification, but PPG sensors are based on the fact that light entering the body will scatter in a predictable manner as the blood flow dynamics change, such as with changes in blood pulse rates (heart rate) or with changes in blood volume (cardiac output).

How does the technology work?

PPG sensors use four primary technical components to measure heart rate:

1. Optical emitters – generally at least 2 LED’s that send light waves into the skin, although some PPG sensors are adding more emitters and varying light wavelengths. Because of the wide differences in skin thickness, tone and morphology associated with a diversity of people, most state-of-the-art OHRM’s use multiple light wavelengths that interact differently with different levels of skin and tissue.

2. Photodetector(s) – the photodetector captures the light refracted from the user of the device and translates those signals into one’s and zero’s that can be calculated into meaningful heart rate data.

3. Accelerometer – the accelerometer measures motion and is used in combination with the photodetector signal as inputs into PPG algorithms.

4. Algorithms – the algorithms process the signals from the photodetector and the accelerometer into motion-tolerant heart rate data, but can also calculate additional biometrics such as  VO2, calories burned, R-R interval, heart rate variability, blood metabolite concentrations, blood oxygen levels, and even blood pressure.

MEMS Motion Sensor – Optical Sensors

Watch this: Building a Wearable with Heart Rate Monitoring

PPG sensors must be a new innovation, right?

PPG is actually almost 150 years old, but it has been revolutionized in the 21st century for new use cases. Real-time optical blood flow monitoring was first used in the late 1800s by having people hold their hand up to a candle in a dark room to see the vascular structure and blood flow. More recently in the early 1980s, the first pulse oximeters were launched for hospital use, measuring pulse rate and blood oxygen using two alternating LEDs. These are very similar to the finger or ear clip devices still used in healthcare facilities today.

PPG sensor developments in the last 5-10 years have focused on consumer and medical wearable devices and services. This required a radical development known as motion-tolerant PPG because using PPG sensors during motion and activity massively increases the amount of motion noise that must be removed to find the blood flow signal.

Here’s a brief visual history of PPG sensors:

optical heart rate monitoring – technology timeline

What are the primary challenges with OHRM wearables?

PPG sounds relatively simple, but it’s actually very difficult to implement accurately for wearables. Measuring PPG during a resting state (sleeping, sitting, and standing still) is relatively straightforward, but measuring PPG during physical activity is incredibly complex. In fact, there are five fundamental challenges you will face in building wearable devices with OHRM:

1. Optical noise – The biggest technical hurdle in processing PPG sensor signals is separating the biometric signal from the noise, especially motion noise. Unfortunately, when you shine light into a person’s skin only a small fraction of the light returns to the sensor, and of the total light collected, only ~1/100th of it may actually indicate heart-pumped Blood pressure monitor. The rest of the signals are simply scattered by other material, such as skin, muscle, tendons, etc.

2. Skin tone – Humans have a diverse range of skin tones and different skin tones absorb light differently. For example, darker skin absorbs more light, which presents a problem because many OHRM’s don’t use the right mitigations to accurately measure heart rate through dark skin. Check out this post for more detail: Are PPG sensors less accurate for people with darker skin? This also presents a problem for measuring heart rate through tattooed skin, which Apple found out the hard way in what became known as “tattoogate” when people with wrist tattoos found that the heart rate monitor on the Apple Watch performed poorly – or not at all – for them.

Read this: How to Test Biometric Wearables

3. Crossover problem – One of the most challenging aspects of optical noise for OHRMs that is created by motion and activity happens during what is known as periodic activity, which is an activity that involves continuous repetition of similar motion. This is most often seen in the step rates measured during jogging and running because step rates typically fall into the same general range as that of heartbeats (140-180 beats/steps per minute). The problem that many OHRMs face is that it becomes easy for the algorithms interpreting incoming optical sensor data to mistake step rate (“cadence”) for heart rate. This is known as the “crossover problem”, because if you look at the measurements on a graph when the heart rate and step rate crossover each other, many OHRMs tend to lock on to step rate and present that number as the heart rate, even though the heart rate may be changing drastically after the crossover.

4. Sensor location – The location of the OHRM on the body presents unique challenges that vary significantly by location. It turns out that the wrist is one of the worst places for accurate PPG monitoring of heart rate because of the much higher optical noise created in that region (muscle, tendon, bone, etc.) and because of the high degree of variability in vascular structure and blood perfusion across the human populations. The forearm is considerably better because of the higher density of blood vessels near the surface of the skin. However, the ear is by far the best location on the body for OHRM because it is essentially just cartilage and blood vessels, which don’t move much even when the body is in vigorous motion, and because of an ideal arteriole bank between the anti-tragus and concha of the ear, thereby drastically reducing the optical noise that must be filtered.