Series | What we talk about when we talk about optical heart rate sensors for biometric wearables

What do optical heart rate sensors measure?

Optical heart rate sensors generate a PPG waveform that measures heart rate and uses that heart rate data as a base biometric, but you can use the PPG waveform to measure much more than that. While it is difficult to obtain and maintain accurate PPG measurements (which we will discuss in detail in the next article), if you can successfully obtain an accurate PPG measurement, it can be very powerful. A high-quality PPG signal is the basis for many of the biometrics required in today's market. Figure 2 is a simplified PPG signal that represents the measurement of multiple biometrics.

Figure 2: Typical PPG waveform

Let's take a closer look at what some optical heart rate sensors can measure:

• Respiration rate

  A lower resting breathing rate generally indicates better physical condition.

• Maximum oxygen uptake (VO2max)

  VO2 measures the maximum amount of oxygen that the human body can take in and is a widely used indicator of aerobic endurance.

• Blood oxygen level (SpO2)

  Refers to the oxygen concentration in the blood.

• RR interval (heart rate variability)

  The RR interval is the time between blood pulses; generally speaking, the longer the heartbeat interval, the better. RR interval analysis can be used as an indicator of stress levels and different heart problems.

• blood pressure

  The PPG sensor signal allows blood pressure to be measured without a sphygmomanometer.

• Blood perfusion

  Perfusion refers to the body's ability to push blood through the circulatory system, specifically through the capillary beds throughout the body during times of death. Because PPG sensors track blood flow, they can measure changes in the relative perfusion rate of blood flow and blood perfusion levels.

• Heart Efficiency

  This is another indicator of cardiovascular health and physical condition. Generally speaking, it measures the efficiency of the heart's work per beat.

Challenges with optical heart rate sensors?

Designing an optical heart rate sensor for a wearable device is challenging because the design approach is greatly affected by human motion. To compensate for this, you need powerful optomechanics and signal extraction algorithms. Figure 3 illustrates some of the main challenges you may face when designing an optical heart rate sensor.

Figure 3: Key challenges in integrating an optical heart rate sensor

Photodynamics

Further details on optomechanical considerations for PPG sensor integration are provided below:

• Optomechanical coupling

  Is it possible to efficiently conduct light bidirectionally and couple it between the sensor and the human body? The key is to maximize the blood flow signal and minimize environmental noise (such as sunlight) that adds noise to the sensor.

• Is the correct wavelength used for the body part ? Different parts require different wavelengths because their physiology is different and they are affected differently by environmental noise.

• Does the design use multiple transmitters, and are they spaced correctly? Transmitter spacing is important to ensure that you measure sufficient volume and the right type of blood flow with fewer artifacts.

• During physical exercise or body movement, are mechanical effects , such as displacement between the skin and the sensor , minimized? This is a question for many common scenarios where wearable devices are worn for activities, such as running, jogging, and gym workouts.

Signal extraction algorithm

Further details on signal extraction considerations are provided below:

• Has the algorithm been validated on a diverse population?

  This is important because only through such validation can the device be guaranteed to function properly on a variety of skin tones, genders, body types, and health conditions.

• Is the algorithm robust against many types of motion noise?

  The algorithms must be able to work properly during a variety of activities, including walking, running (both high-speed steady running and interval training), sprinting, gym training, and everyday behaviors such as typing or driving.

• Will the algorithms continue to improve so they can handle more use cases and new types of biometrics?

  This technology and the wearables market are evolving rapidly, and you must continue to innovate to meet changing customer needs.