Monitoring athletic performance is certainly nothing new. Advanced technologies in wearable sensors to monitor and evaluate physiological biomarkers offer increased opportunities to collect and quantify data without direct proximity to the athlete.
To better optimize workouts and evaluate the full performance, it’s necessary to get detailed cardiovascular and biomechanical insight into how the body performs. Obtaining numerical values on performance relative to baseline values or to that of peer athletes can help define how an athlete is performing instead of how they are perceived to be performing.
Wearable sensors can provide objective data points to help determine reasons for the performance level and reasoning for potentially altering workouts to reduce the burden of injury. The value of wearable sensors lies in part in their ability to function remotely, enabling monitoring and evaluation without physical immediacy. The integration of sensing components also offers a host of parameters necessary to gauge the performance and health of athletes in ways not possible a decade ago.
Necessity of Sensor Monitoring
All professional athletes want to be stronger, faster and better. To help them achieve that, sports scientists, team physicians and exercise physiologists can monitor relevant data to optimize their workouts as well as in-game performance.
Obtaining a rating of perceived exertion (RPE) enables the medical and training staff to gauge the athlete’s response to a workout or training regimen. The value, coupled with the duration of the workout, provides a quantitative (albeit subjective) estimate of how hard the athlete is responding to the workload (e.g., internal workload) at any given time. However, it does not show the full ramifications of the effects of the workout on the athlete’s body.
Quantifying the external workload or the demands exerted by the athlete using biomechanical-based wearable sensors enables one to gauge the output of the athlete based on the training regimen prescribed.
For example, by monitoring players' capacity on an NFL team over a two-year period using wearable sensor technology, members of Lehigh University’s research team found that athletes who had a workload above a certain threshold were approximately one and a half times as likely to suffer a soft-tissue injury.
By knowing how hard they’re working at any given point, models can be developed to reduce injury and establish rest schedules. That rest concept has recently been labeled “load management” and refers to balancing the playing time of athletes to simultaneously keep them fresh throughout an arduous season while mitigating injury from over- or under-training.
The concept is already being used in the NBA and has gained significant traction with the NFL, especially given the 17-game season in 2021 instead of the previous 16-game schedule. The principles governing load management can be applied to dictate an athlete’s return after a soft-tissue injury, a season-ending orthopedic injury (e.g., ACL tear or Achilles rupture), or even a return to sport following COVID-19.
For example, an athlete at Case Western Reserve University returning from a lower lumbar injury used wearable sensors to observe musculoskeletal and cardiovascular physiological adaptation over two weeks. The data on her internal workload, coupled with self-reporting of her RPE, informed researchers of her ramp-up to an ideal return to play.
An ongoing study funded by the American Orthopedic Society for Sports Medicine is looking at specific wearables from anterior cruciate ligament (ACL) reconstruction. Changes in muscle oxygen saturation levels are being examined as an individual returns to play and whether there are changes as the atrophied muscle starts to regain its strength compared to the contralateral leg.
Researchers are also examining how the information can be used to complement the subjective assessment the athletic trainer collects. The underpinning question motivating this study? Can wearable technology provide our team with continuous, internal, and physiological data that would give insight to evaluate how the ligament is rehabbing and better ascertain when we can clear the athlete from a musculoskeletal standpoint? Data garnered would help affirm or complement current decision-making strategies employed at the clinic.
Return to play extends to viral illness as well. For example, if an NFL athlete has COVID, after his CDC-mandated quarantine, there’s an ECG, echo, and a normal workout. If the athlete feels fine (when corroborated with the medical reports), he’s cleared to play.
Lehigh’s team has studied the incidence of injuries following the COVID-19 lockout with the hypothesis that detraining and changes in muscle physiology would contribute to increases in musculoskeletal injury to spikes in training intensities. Toward assessing this broad hypothesis, the team published a study in early 2021 assessing injury risks following the 2019-2020 Bundesliga season as a result of the lockdown. This retrospective study resulted in the following findings:
Players had 1.13x odds of being injured following the COVID-19 lockdown (95% CI 0.78, 1.64), with a 3.12x higher rate of injury when controlling for games played compared to injury rates pre-lockdown.
0.84 injuries per game post-COVID-19 lockdown vs. 0.27 injuries per game pre-COVID-19 lockdown.
Muscular injuries most common with 23 injuries total.
17% of all athletes experienced injury during their first competitive match following lockdown.
Wearables could be used for more insightful evaluation. Collecting biomechanical and physiological data enables normative comparisons if and when an athlete returns to sport following an injury or illness.
For example, collecting baseline heart rate, heart rate variability and movement data (velocity, acceleration, and external workload) in conjunction with RPE scores enables comparisons to similar workouts performed by the athlete during the rehabilitation phase.
Significant deviations in metrics would alert the medical staff that the athlete may not be ready, while small deviations (potentially serving as artifacts in the signal) would indicate a sufficient RTP.
With the development of biochemical sensors and blood tests, factoring in biomarkers such as troponin or lactate would further complement and add value to the role wearable technology could play to monitoring the health and safety of athletes.
Benefits Beyond Professionals
The benefits of performance monitoring extend beyond professionals to youth athletes, especially in an era of increased specialization. When those younger than 18 years specialize in one particular sport, they use specific muscle groups over and over, which results in unnatural abuse of the body.
A clear example is young baseball pitchers who wear out their elbows and end up undergoing the procedure commonly known as Tommy John surgery to repair a tear in the ulnar collateral ligament.
Another common example is in female soccer athletes, who have a higher likelihood (2-4x) of tearing their ACLs compared to male soccer athletes. The repetitive strain placed on the knee, primarily as athletes matriculate through the youth and high school sporting leagues, has a detrimental impact on their long-term biomechanics.
How does wearable sensor technology apply in this scenario?
First is working with device manufacturers to get the cost to a point where the technology can be widely disseminated and used with this group.
The second is to enable athletes to monitor how hard they're working, analogous to how professional athletes are working, with the same fidelity from a sensor accuracy and analytics standpoint.
Lehigh University works with sensors like the Vivalink ECG Cardiac Patch and Moxy Sensor, among numerous others, to ultimately support this group because it’s the largest cohort of athletes in the country.
By showing professional athletes using the technology to monitor themselves for optimum performance, behavior can be modeled for collegiate and youth athletes to ultimately make the game safer without as much injury.
Role of Proximity
Working with athletes onsite at a training facility or during a game scenario is common, but what about monitoring when the participant isn’t in the same location? Using Bluetooth or NFC technology makes it possible to synchronize multiple sensors into one portal or athlete performance index to measure more than one person in multiple locations.
Placing multiple sensors on different individuals or even the same sensor on different body parts enables more data and applications to ultimately prevent or reduce the likelihood of injury.
Lehigh’s team has extensive experience using wearable sensors. We’ve used biomechanical, physiological and biochemical sensors for monitoring athletes of all ages, ranging from professional athletes to collegiate and now to youth athletes.
The technology would be a viable method to monitor and evaluate athlete performance in a situation like the Sports Combines when it’s not always possible for all team representatives to be physically on-site.
Biomechanical sensors and physiological sensors for heart rate are used extensively by professional teams but aren’t yet as widely disseminated in the college ranks for several reasons.
Data privacy is an obvious factor, but there’s also the issue of how the information is used. Looking at heart rates can provide a wealth of data points, but how is that information evaluated, interpreted and ultimately used?
The context of using the data is a fundamental question that speaks to the complete technology platform beyond just the actual wearable sensor. Especially in non-professional ranks, the data package must be comprehensive yet easily digestible enough to be understood and used by those without extensive technology training.
Quality and Accuracy
For sensor technology to be viable, the type and quality of data are critical. Heart rate, respiration rate and skin temperature are physiological parameters we expect from a sensor.
One metric that's become increasingly popular from an exercise physiology standpoint is heart rate variability or HRV which reflects the true cardiovascular adaptation and is a metric of physiological stress.
But we look beyond the basic data points at causality among variables and the correlations. Heart rate, respiration rate, HRV, skin temperature, core temperature, sweat rate, muscle oxygen saturation levels and lactate levels are all parameters in an arsenal to develop models.
When biomechanical data is received, one can complement that with data from short intensity bursts, velocity, acceleration, external workload based on changes in acceleration and distance traveled. By examining NFL data, a correlation was found between distance traveled and workload (r2 = 0.95). That tends to be one of the best metrics for how hard an athlete works.
Researchers can look at how all these factors are related and glean insight into the value of technology to improve athlete performance. Complementing this data with eccentric hamstring testing or other testing protocols will provide a comprehensive platform to ultimately reduce injury burden.
The ability to contextualize information is key to the appropriate use of the data. That requires those using the data working with the wearable sensor manufacturer to create the right platform to obtain the desired data output. Interdisciplinary accuracy is vital to ensure what the sports scientists want to know meshes with the efficacy of the sensor. An example is Vivalink building software layers to extract different parameters such as incorporating an SPL2 device into the platform for an electrocardiogram(ECG) patch to provide continuous data flow.
Evaluation of Potential
The where and how wearables can be used presents vast potential. While they’re already being used on healthy athletes to measure performance, the opportunities to use them in the context of an injured athlete or someone recovering from a viral illness or musculoskeletal condition still present tremendous potential for exploration and discovery.
There’s also much to be determined regarding the type of wearable sensor devices applicable to athletes based on the type of workout or sport. Most athletes, professional and amateur, use whatever their sports trainer provides so knowing which devices to use and when becomes critical to accurate data monitoring, collection and evaluation.
Continued collaboration between the sports science community and athletes, facilitated through trained performance specialists, will continue to drive the evolution of the sensors and related technology platforms. The interdisciplinary team at Lehigh University and nationwide, comprised of orthopedic surgeons, exercise physiologists, physical therapists, athletic trainers and biomedical engineers, is geared towards creating robust analytical platforms from wearable devices such as the Vivalink ECG patch to ensure athletes of all ages can participate in the sports they love at a high level in a safe and organized manner.
Dhruv Seshadri is an assistant professor in bioengineering at Lehigh University in Bethlehem, Pennsylvania. Seshadri received his PhD in biomedical engineering from Case Western Reserve University and was concurrently a research engineer at the Louis Stokes Cleveland Veterans Affairs Medical Center in Cleveland, Ohio. Dhruv’s research background and interests are in the development, elucidation, and application of materials for wearable bioelectronics, drug delivery and regenerative medicine. His research focuses on wearable devices for maximizing human health and performance.
