The World of Wearables – Does the Data Support the Use?

Biologic and performance feedback are fundamental for athletes and their teams to improve performance, augment longevity, and minimize injuries. The need for objective feedback has provided a natural marriage between wearable technologies and athletes that seek data to improve performance and provide real-time feedback. Wearables also offer the significant advantage to other feedback sources as they can be used dynamically during athletic performances and sporting environments.

Wearables for biologic and performance feedback to quantify skill level and performance, augment or improve technique, characterize movement, and for injury prevention have shown benefit in sought outcomes compared to traditional forms of training.1 Beyond performance metrics, both athletes and nonathletes commonly use wearables to determine energy expenditure through accelerometry, heat-sensing technologies, and heart rate counters. Accelerometry to estimate step count is one of the most commonly available resources used by the general public and multiple direct-to-consumer devices are available. In a small study of 10 participants, the step-count accuracy of smartphone-based technology was compared to wearable technology during a protocol-based treadmill test. The research team found that in general smartphones accurately estimated step count and wearable devices were less accurate with errors up to 20%.2 Accuracy can be negatively impacted with aging and various medical diseases. A study using Fitbit® at the wrist and at the hip with a Samsung® GT-I9300 mobile phone had estimation errors >60% in activity tracking when used in a population of elderly adults with reduced mobility.3

When considering a device to assess activity, heart rate counters tend to add value to accelerometers alone as they can assess energy expenditure with supine exercise and non-weight bearing exercises. The accuracy of available heart rate monitors is variable amongst different products and is significantly influenced by activity.4 In a study of fifty healthy adults, Gillinov et al5 assessed the accuracy of an electrocardiographic chest strap monitor (Polar H7), forearm monitor (Scosche Rhythm+™) and two randomly assigned wrist-worn heart rate monitors (Apple Watch®, Fitbit Blaze®, Garmin Forerunner® 235, TomTom™ Spark Cardio) on each wrist to standard electrocardiograms. The chest strap monitor was the most accurate followed by the Apple Watch® (rc=0.92), TomTom™ Spark (rc=0.83), Garmin Forerunner® (rc=0.81), Scosche Rhythm+™ (rc=0.75) and Fitbit Blaze® (rc=0.67). All devices performed well during treadmill testing. However only the Apple Watch® was accurate on an elliptical training without arm levels (rc=0.94). The Garmin®, Apple Watch®, and Scosche Rhythm+™ had acceptable accuracy (rc >0.80) during bicycling. This study, and others, highlight the limitations of current commercially available wrist wearables in accurately monitoring heart rate during exercise. For athletes with documented heart disease whose cardiologists have provided upper heart rate thresholds to stay below during exercise, these data caution against using these technologies as medical grade devices given these limitations.

There is significant interest from healthcare providers to use wearable technologies to assist patients in improving their health and fitness, monitoring and managing disease states, and to screen for disease.

First, let's consider the use of wearables for the prevention of a common disease state. Obesity is increasing worldwide and strongly correlates with risk of cardiovascular disease. The vast majority of phone-based applications and wearable technologies provide some metric of activity. As people tracked their activity and receive this feedback, they tend to become more active.6 A systematic review was performed to evaluate published evidence regarding the impact of wearable technologies to assist with weight loss. The review included twelve studies of overweight or obese participants. In eleven out of twelve studies, weight loss was the primary endpoint evaluated. In six studies, the technology-based group experienced greater weight loss compared to a control population. One study showed significant weight loss with a combination approach that included a mobile application and additional web-based interfaces to monitor diet and compliance. In another two studies, a combination of a wearable devices plus a smartphone-based application to provide multiple levels of interventions improved outcomes. Two studies did not find a significant weight loss benefit with the mobile applications or wearable-guided approaches. Dropout rates were problematic for most of the studies and in the four that examined long-term weight loss, no benefit was found at 12 and 24 months with technology-based support.7 In summary, wearables show promise when used to augment short-term weight loss compared to historical approaches in small studies, however technologic advances, improved education, and combination approaches with proven weight-loss strategies are needed to achieve better long-term outcomes.

The next question to address is whether the data from wearables are actionable and lead to changes in therapy particularly in the context of coronary artery disease. Cardiovascular disease is a leading cause of mortality throughout the world in both developed and underdeveloped countries. Even in high to master level athletes, the diagnosis and management of coronary artery disease remains essential.8 A potential means of improving access to early diagnosis is through smartphone-based technologies given the broad availability of these devices worldwide. The ST LEUIS trial was a multicenter international study that compared smartphone-derived ECGs to those of a standard 12-lead ECG.9 Of 204 study participants who presented with chest pain or ST elevation myocardial infarction (STEMI) activation, the smartphone electrocardiogram (ECG) versus the standard ECG had a sensitivity, specificity, positive, and negative predictive value for STEMI/left bundle branch block of 0.89, 0.84, 0.70 and 0.95, respectively. As this technology evolves, the potential impact of early diagnosis and treatment worldwide may be significant in modifying the disease course of an acute myocardial infarction.

Finally, can wearables be used to screen for a disease? Atrial fibrillation (AF) is the most common clinically significant cardiac arrhythmia. In the general population, exercise is a means to lower risk of AF through decreasing body weight, lowering blood pressure, minimizing sleep apnea risk, and improving macro- and micro-vascular flow and function. However, as exercise intensity and duration increase in elite athletes, AF risk also increases. A meta-analysis found a 5-fold increase in risk of AF in endurance athletes compared to nonendurance athletes.10 There are a number of wearable devices that record ECG tracings. These include the Apple Watch®, Series 4 and 5, and the Kardia devices made by Alivecor® (watch strap, smart phone attachment). There are also chest worn devices that can record ECG tracings from Qardio®Core and Hexoskin.11 The Apple Watch® and Kardia devices have received FDA clearance to discriminate between sinus rhythm and AF.

Palpitations are common in athletes and vary in incidence between 0.3-70% reflecting the type of sport and the age of the competitor. In elite athletes, AF accounts for 9% of the arrhythmias and up to 40% in competitors with long-standing symptoms.12 Broad use of wearables in athletes to screen for arrhythmias remains problematic due to the low incidence of heart rhythm disorders. Although the Apple Watch® in a general population of 419,297 patients demonstrated value in AF diagnosis in a low incidence population, only 2161 participants (0.52%) received notifications of irregular pulse. Within this notification population, 450 wore a continuous ECG monitor which in 34% diagnosed AF. Simplifying these numbers, in a study of 419,297 patients, 150 (0.036%) were ultimately diagnosed with AF through device diagnostics that led to an ECG diagnosis.13

For an athlete with palpitations, in a small case series of six patients, the data derived from a smartphone-derived ECG allowed an arrhythmia correlation of the symptoms and a return to play in all patients.14 For athletes considering using these technologies for evaluation of symptoms, it is critical to recognize that only two are approved to distinguish between AF and sinus rhythm. Although AF is a common arrhythmia in elite athletes, it still represents a small proportion of the arrhythmias that are present, and the diagnosis and interpretation of these other symptomatic arrhythmias is not an approved feature in currently available devices.

Critical in the assessment of any screening approach or tool is to understand the implications of false positives that can lead to anxiety, lower quality of life, and upstream testing and interventions that have relative risks and consequences. In regards to AF, the majority of false positives with handheld devices are a consequence of abnormal waveforms from finger or limb movement artifacts that affect the detection algorithms.15 The potential for artifact can be magnified during athletic training or competition. False positives should improve with technology advancements. However, even with highly specific early detection of AF, it is unclear if the inherent augmentation of additional testing and therapeutic ramifications after diagnosis will favorably impact patients.

In summary, wearables have shown promise in the prevention and screening of cardiovascular diseases. While data are emerging and expanding, at present, they do not support their broad use in asymptomatic athletes to prevent or screen for cardiovascular disease. In older patients or those with risk factors, large trials such as the HeartLine™Study will assess if wearable device diagnostics can favorably impact guideline-based therapy use and lower long-term adverse consequences of AF. In athletes with symptoms, wearables can provide diagnostic data over time that can be used and interpreted by their healthcare team to guide athletic participation and the need for additional testing.

References

  1. Adesida Y, Papi E, McGregor AH. Exploring the role of wearable technology in sport kinematics and kinetics: a systematic review. Sensors (Basel) 2019;19:1597.
  2. Case MA, Burwick HA, Volpp KG, Patel MS. Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA 2015;313:625-26.
  3. Lauritzen J, Munoz A, Luis Sevillano J, Civit A. The usefulness of activity trackers in elderly with reduced mobility: a case study. Stud Health Technol Inform 2013;192:759-62.
  4. O'Driscoll R, Turicchi J, Beaulieu K, et al. How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies. Br J Sports Med 2020;54:332-40.
  5. Gillinov S, Etiwy M, Wang R, et al. Variable accuracy of wearable heart rate monitors during aerobic exercise. Med Sci Sports Exerc 2017;49:1697-1703.
  6. Cadmus-Bertram LA, Marcus BH, Patterson RE, Parker BA, Morey BL. Randomized trial of a Fitbit-based physical activity intervention for women. Am J Prev Med 2015;49:414-18.
  7. Wang E, Abrahamson K, Liu PJ, Ahmed A. Can mobile technology improve weight loss in overweight adults? a systematic review. West J Nurs Res 2019;193945919888224.
  8. Merghani A, Maestrini V, Rosmini S, et al. Prevalence of subclinical coronary artery disease in masters endurance athletes with a low atherosclerotic risk profile. Circulation 2017;136:126-37.
  9. Muhlestein JB, Anderson JL, Bethea CF, et al. Feasibility of combining serial smartphone single-lead electrocardiograms for the diagnosis of ST-elevation myocardial infarction. Am Heart J 2020;221:125-35.
  10. Abdulla J, Nielsen JR. Is the risk of atrial fibrillation higher in athletes than in the general population? A systematic review and meta-analysis. Europace 2009;11:1156-59.
  11. Al-Alusi MA, Ding E, McManus DD, Lubitz SA. Wearing your heart on your sleeve: the future of cardiac rhythm monitoring. Curr Cardiol Rep 2019;21:158.
  12. Lawless CE,Briner W. Palpitations in athletes. Sports Med 2008;38:687-702.
  13. Perez MV, Mahaffey KW, Hedlin H, et al. Large-scale assessment of a Smartwatch to identify atrial fibrillation. N Engl J Med 2019;381:1909-17.
  14. Peritz DC, Howard A, Ciocca M, Chung EH. Smartphone ECG aids real time diagnosis of palpitations in the competitive college athlete. J Electrocardiol 2015;48:896-99.
  15. Raja JM, Elsakr C, Roman S, et al. Apple Watch, wearables, and heart rhythm: where do we stand? Ann Transl Med 2019;7:417.

Clinical Topics: Arrhythmias and Clinical EP, Sports and Exercise Cardiology, Atherosclerotic Disease (CAD/PAD), EP Basic Science, Atrial Fibrillation/Supraventricular Arrhythmias, Sports and Exercise and ECG and Stress Testing

Keywords: Sports, Chest Pain, Electrocardiography, Blood Pressure, Quality of Life, Incidence, Risk Factors, Cardiovascular Diseases, Coronary Artery Disease, Myocardial Infarction, Bundle-Branch Block, Atrial Fibrillation, Overweight, Benchmarking, Longevity, Heart Rate, Bicycling, Exercise Test, Mobile Applications, Weight Loss, Technology, Wireless Technology


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