How to Create Accurate Performance-Tracking Sports Wearables

How to Create Accurate Performance-Tracking Sports Wearables

Whether you run long distances on weekends or participate in recreational or professional-level sports, you'd probably be interested in an accurate way to track your progress and performance. Wearables offer a solution.

The sports technology market is projected to reach USD31.1 billion by 2024, and wearables represent the largest and fastest growing segment, according to research from analyst firm MarketsandMarkets. It's no wonder—wearables equipped with biosensors continuously collect data and come in convenient and comfortable formats, such as wristbands, clothing, chest straps, belts, and jewelry. When this data is analyzed with sophisticated algorithms, the wearer gains valuable insights about athletic performance and overall well-being.

Figure 1. Wearable sports technologies provide runners and other fitness buffs with valuable insights about performance and overall well-being.

Get Smarter About Your Fitness Routine

Wearables can track key parameters such as heart rate, blood-oxygen level, stress levels, body temperature, and sleep quality. Users can then apply these insights toward more productive workouts, better chronic disease management, more proactive preventive care, and also a more personalized healthcare model. For athletes in particular, the devices as well as software tools can help with player safety assessment, workout injury prevention, and physical conditioning and performance. For example, RF technology-based tracking systems can track acceleration, jumps, and other movements by basketball players.

Effective wearable sports technology must be highly accurate, provide useful measurements, operate for long periods of time between charges, and be comfortable and unobtrusive. The underlying technology plays a key role in enabling each of these characteristics.

Biosensors Uncover a Treasure Trove of Wellness Insights

Continuous heart-rate monitoring provides the beat-to-beat-to-beat data that is an indication of heart-rate variability, which tells a lot about the body:

  • How well it is reacting to exercise
  • How well it is recovering from the activity
  • Fitness levels and any related improvements
  • How well it is tracking to goals
  • Remaining energy during an activity

Providing this type of data requires optical and mechanical design expertise, low-power electrical design know-how, and algorithm capabilities. As for the components, they should ideally be precise, small, and consume very little power.

Advancements in optical sensors have been a significant contributor to the efficacy of wearable health and fitness monitoring solutions. Sensors can now accurately monitor photoplethysmography (PPG), body temperature, and other vitals. There are now even biosensor modules for wearables that integrate multiple parameters, such as synchronized PPG with electrocardiogram (ECG) monitoring. Using light to interrogate tissue, PPG provides an optical measurement of the volumetric change of blood in tissue during the cardiac cycle. ECG, on the other hand, uses electrodes to measure electrical signals in the heart. Both can be used to provide heart-rate measurements, and ECG sensors also yield reliable heart-rate variability data. PPG monitoring is particularly challenging, however, as it is affected by ambient light, different skin conditions and colors, blood perfusion, and physical motion artifacts.

The challenges of integrating optical-sensing technology into wearables will vary based on the end device. Getting accurate measurements from smartwatches will be tougher than doing so in in-ear monitors, for instance. The wrist is an area with low blood perfusion and high motion, which creates noise that impacts the readings. The ear has higher blood perfusion and, therefore, can yield more precise measurements.

Development Platforms Accelerate Your Wearable Design Cycle

Advancements in semiconductor solutions address the accuracy, power efficiency, and size challenges of wearable designs. Maxim, for example, has long been focused on developing products that provide the insights to enable a healthier world. For example, MAX-HEALTH-BAND is an evaluation and development platform that streams raw data from sensors or processes raw data to output heart rate, heart-rate variability, activity classification, calorie consumption, and step count information. The platform, which can shave off up to six months of development time, includes:

  • The MAX86140 ultra-low-power optical pulse-oximeter/heart-rate sensor (Figure 3), which has a low-noise signal conditioning analog front-end (AFE), including a 19-bit analog-to-digital converter (ADC), an ambient light cancellation circuit, and a picket-fence detect-and-replace algorithm. The picket-fence algorithm enables consistently accurate heart-rate detection under varying light conditions, such as shadows and bright light.

Figure 2. MAX86140 block diagram.

  • The MAX20303 wearable power-management IC (PMIC) (Figure 4), which includes an eccentric rotating mass (ERM)/linear resonant actuator (LRA) haptic driver with automatic resonance tracking, micro quiescent current boost and buck regulators, a linear lithium-ion battery charger, micro quiescent current low-dropout (LDO) regulators, and an optional fuel gauge

High Resolution Image ›
Figure 3. MAX20303 block diagram.

  • Maxim's motion-compensated algorithms, which extract data based on PPG signals

MAX-ECG-MONITOR provides an evaluation and development platform for monitoring clinical-grade ECG and heart rate. It's available in a wet electrode patch for clinical applications, as well as a chest strap for fitness applications. The platform includes the MAX30003 ultra-low-power, clinical-grade, integrated biopotential AFE, which provides ECG waveforms and heart-rate detection. Its continuous measurements can be useful for trend- or predictive-type applications. Because the platform's built-in heart-rate detection includes an interrupt feature that eliminates the need to run a heart-rate algorithm on a microcontroller, it yields robust R-R detection in a high-motion environment at very low power. The platform supports long battery life through a couple of key features: operation at 85µW at 1.1V supply voltage and configurable interrupts that allow the microcontroller to wake only on every heart beat to reduce overall system power.

In summary, delivering accurate data from wearable form factors requires underlying technologies that are precise, power efficient, and small. IC vendors are providing resources for designers to create smartwatches, chest straps, clothing, and other wearable devices that deliver continuous, real-time health and fitness insights to shape their performance. An extended version of this article originally appeared in Power Systems Design.