The Green Light on Your Wrist: How Smartwatches Measure Heart Rate and SpO2

You glance at your wrist. A small, rhythmic pulse of green light flashes against your skin, and moments later, a number appears on the screen: your heart rate. It feels like magic, a seamless conversion of biology into data. Devices like the Sanorum G53 promise a window into our body’s inner workings, tracking not just heart rate but also blood oxygen levels, sleep patterns, and more. But what is actually happening beneath that glowing display? It’s not magic; it’s a fascinating and elegant scientific principle called Photoplethysmography, or PPG. Let’s demystify that green light and understand how this technology truly works.

The Core Principle: A Traffic Check on a Micro-Highway

At its heart, PPG is a surprisingly simple concept. Imagine your blood vessels as tiny highways, and your red blood cells as the cars traveling on them. The smartwatch on your wrist acts like a traffic camera system. It uses small, bright LEDs to shine light into your skin and a sensor called a photodiode to measure how much of that light bounces back.

Here’s the key: blood absorbs light. Specifically, it absorbs more light than the surrounding tissue. With every heartbeat, a pressure wave from your heart pushes a greater volume of blood—more “cars”—through the highways in your wrist. This momentary increase in blood volume means more light is absorbed, and therefore, less light is reflected back to the sensor. Between heartbeats, the blood volume decreases, less light is absorbed, and more is reflected.

The watch’s sensor detects these minuscule, rhythmic changes in reflected light hundreds of times per second. An algorithm then analyzes this wave-like pattern of light intensity to calculate the frequency of the pulses. That frequency is your heart rate. It’s a clever, non-invasive way to “see” the pulse of blood flowing just beneath your skin.

Why Green for Heart Rate, and Red/Infrared for Blood Oxygen?

But if the principle is so simple, why do smartwatches like the Sanorum G53 use a specific green light for heart rate, and a different set of red and infrared lights for blood oxygen? The answer lies deeper within our skin, in a fascinating story of physics meeting biology.

Different colors of light have different wavelengths, which dictates how deeply they can penetrate our tissue. Green light has a shorter wavelength and is absorbed very strongly by hemoglobin, the protein in our red blood cells. Because it’s so readily absorbed, it doesn’t penetrate very deeply, which makes it perfect for measuring the blood flow in the superficial capillaries just below the skin’s surface. For all-day, continuous heart rate monitoring, this is ideal.

However, to measure blood oxygen saturation (SpO2), the watch needs to look deeper. This is where red and infrared light come in. They have longer wavelengths and can penetrate further into the tissue to reach larger blood vessels. The magic here is that oxygenated hemoglobin and deoxygenated hemoglobin absorb red and infrared light differently.
- Oxygenated blood (bright red) absorbs more infrared light and allows more red light to pass through.
- Deoxygenated blood (darker red) absorbs more red light and allows more infrared light to pass through.

To get an SpO2 reading, the watch rapidly flashes both red and infrared LEDs and measures the ratio of reflected light for each. Based on this ratio, an algorithm can estimate the percentage of your hemoglobin that is saturated with oxygen. This is the same fundamental principle used in the clip-on pulse oximeters you see in hospitals.

The “Brain” Behind the Light: How Algorithms Fight Noise

Shining light and measuring reflections is only half the battle. The signals captured by the PPG sensor are incredibly faint and susceptible to “noise”—interference that can corrupt the data. The single biggest challenge for any wrist-worn device is motion artifacts.

When you move your arm, especially during vigorous exercise, the watch can shift slightly. This movement causes changes in the reflected light that have nothing to do with your pulse, potentially overwhelming the true signal. This is why you might see your heart rate spike unrealistically at the beginning of a run.

This is where the so-called “cutting-edge AI smart chip” mentioned in product descriptions comes into play. It’s not sentient AI, but rather a suite of sophisticated signal processing algorithms. These algorithms act as the “brain” of the device. The watch also uses an accelerometer to detect your movement. The algorithm intelligently compares the data from the PPG sensor with the data from the accelerometer. If it detects a change in the light signal that corresponds perfectly with a physical jolt from the accelerometer, it can identify that signal as noise and filter it out, isolating the true pulse wave underneath. According to research in journals like IEEE Transactions on Biomedical Engineering, combining PPG and accelerometer data is the most effective way to mitigate motion artifacts, improving accuracy by over 15% in some cases.

When the Light Gets It Wrong: Understanding Inaccuracies

Even with a powerful algorithmic “brain,” these tiny sensors are not infallible. So, what happens when the light gets it wrong? Understanding the limitations is just as important as appreciating the technology. * Poor Fit: If the watch is too loose, ambient light can leak into the sensor, and the watch’s movement will create significant noise. The device must be snug (but not uncomfortably tight) for accurate readings. * Skin Pigmentation: Melanin in the skin also absorbs light. While manufacturers design algorithms to compensate for this, some studies in publications like the Journal of Clinical Monitoring and Computing have shown that accuracy can sometimes be affected on darker skin tones, potentially requiring adjustments in light intensity or algorithm sensitivity. * Low Perfusion: When you’re cold, the blood vessels in your extremities constrict, reducing blood flow to your wrist (a state called low perfusion). This makes the pulse signal weaker and harder for the sensor to detect. * Tattoos: The ink in tattoos can absorb the sensor’s light, interfering with its ability to reach the blood vessels. Accuracy can be significantly reduced over tattooed areas.

It’s also crucial to remember that while these devices are remarkably advanced, they are not medical-grade instruments. The U.S. Food and Drug Administration (FDA) generally requires medical-grade SpO2 meters to have an accuracy within a ±2-3% error margin. Consumer wearables strive to meet this standard but are typically marketed for wellness and fitness purposes, not for diagnosing medical conditions.

Conclusion: From Data Points to Health Insights

The next time you see that green light pulsing on your wrist, you’ll know it’s not magic, but a remarkable application of physics and biology. Through the simple interaction of light and blood flow, devices like the Sanorum G53 can provide a continuous stream of data about our bodies. By understanding how this technology works—from the choice of light color to the algorithms that fight noise—we can become more informed users. We can appreciate its power to offer valuable wellness insights while also recognizing its limitations. This knowledge empowers us to wear the device correctly, interpret its data wisely, and use it as a tool not just to see numbers, but to better understand the quiet, constant rhythm of our own lives.