SSZT679 june 2018
This is the third installment in a three-part series on optical heart rate sensors for biometric wearables. The first installment focused on how these sensor systems work and what you can measure with them. Part 2 shared the top 10 lessons learned from Valencell’s completion of more than 50 biometric wearable product development cycles.
In an increasingly digital world, there are more and more uses for optical heart rate sensors in wearable devices. These devices have endless applications and provide insights on everything from personal activity and fitness levels to health status. Accurate biometric sensor data can lead to accurate fitness and health assessments, but what exactly can designers and engineers do with these assessments? Table 1 summarizes some of the common assessments used today in fitness applications, which also have validated health and medical implications.
| Assessment | Definition | What it means for fitness | What it means for health |
|---|---|---|---|
| VO2 max | Aerobic capacity: the primary measure of chronic change to cardiovascular fitness | Higher VO2 max correlates with better performance during aerobic activities | Higher VO2 max correlates with lower mortality and improved recovery from a cardiac event |
| Resting heart rate | Heart rate during an awake period of no exertion | A decrease in resting heart rate correlates with an increase in fitness | A steadily increasing resting heart rate correlates with the progression of cardiovascular disease |
| Heart rate recovery | Change in heart rate over one minute after intense exercise | Higher heart rate recovery implies better exercise endurance | Higher heart rate recovery implies better cardiovascular health |
| Heart rate response | Change in heart rate over one minute at the start of exercise | Higher heart rate response can imply low cardiac readiness for exercise | Higher heart rate response paired with chronotropic incompetence, the inability of the heart to increase its rate commensurate with increased activity or demand, can predict carotid atherosclerosis |
| Cardiac efficiency | Average cadence divided by average heart rate at steady state | The higher cardiac efficiency, the fewer heart beats needed for all physical activities | Steadily declining cardiac efficiency correlates with the onset of hypertension |
| Heart rate variability (HRV) | The statistical variability of heart rate intervals | HRV can diagnose psychosocial stress and overtraining in exercise | HRV can predict atrial fibrillation and arrhythmia |
(Info courtesy of the National Institutes of Health and Pacing and Clinical Electrophysiology)
Most wearables in the market today are targeted toward sports & fitness use cases, but you are beginning to see a shift toward wearables becoming personal health devices that can provide meaningful insights into a person’s health. This is because the photoplethysmogram (PPG) sensors in these wearables devices have achieved a level of accuracy that is good enough for many of the health and medical use cases that have already been proven with electrocardiography technology.
Here are some examples of how these assessments are used today and how they could be used in health and medical wearables in the future.
There have been many recent announcements about wearable devices’ new capabilities to detect atrial fibrillation, arrhythmia, core body temperature and more. These capabilities are being delivered by the same optical heart rate sensors using PPG already found in a great deal of wearable devices today.