Consumer Wearable Health and Fitness Technology in Cardiovascular Medicine

JACC State-of-the-Art Review

Bradley J. Petek, MD; Mostafa A. Al-Alusi, MD; Nathaniel Moulson, MD; Aubrey J. Grant, MD; Cyril Besson, MSC; J. Sawalla Guseh, MD; Meagan M. Wasfy, MD, MPH; Vincent Gremeaux, MD, PHD; Timothy W. Churchill, MD; Aaron L. Baggish, MD; Bradley J. Petek, MD; Mostafa A. Al-Alusi, MD; Nathaniel Moulson, MD; Aubrey J. Grant, MD; Cyril Besson, MSC; J. Sawalla Guseh, MD; Meagan M. Wasfy, MD, MPH; Vincent Gremeaux, MD, PHD; Timothy W. Churchill, MD; Aaron L. Baggish, MD

Disclosures

J Am Coll Cardiol. 2023;82(3):245-264.

Abstract and Introduction

Abstract

The use of consumer wearable devices (CWDs) to track health and fitness has rapidly expanded over recent years because of advances in technology. The general population now has the capability to continuously track vital signs, exercise output, and advanced health metrics. Although understanding of basic health metrics may be intuitive (eg, peak heart rate), more complex metrics are derived from proprietary algorithms, differ among device manufacturers, and may not historically be common in clinical practice (eg, peak V̇O₂, exercise recovery scores). With the massive expansion of data collected at an individual patient level, careful interpretation is imperative. In this review, we critically analyze common health metrics provided by CWDs, describe common pitfalls in CWD interpretation, provide recommendations for the interpretation of abnormal results, present the utility of CWDs in exercise prescription, examine health disparities and inequities in CWD use and development, and present future directions for research and development.

Introduction

The 21st century has witnessed an explosion in the availability and use of consumer wearable devices (CWDs) capable of providing health and fitness metrics directly to the end user.^[1,2] While competitive athletes have utilized CWD metrics to measure, monitor, and improve their exercise performance for decades, these data are increasingly extending from the niche realm of elite-athlete training into the broader arena of monitoring health and wellness in the general population. Although this trend represents a profound democratization of access to physiological data, it also presents unique challenges for practicing clinicians, because patients frequently seek medical advice regarding the accuracy, interpretation, and therapeutic applications of CWD health metrics. These challenges are compounded by the rapid evolution of CWD technology, the diverse array of reported metrics, the frequent use of proprietary calculations and algorithms, and the lack of normative data for most CWD-derived parameters.

This review seeks to provide a tangible primer on CWD metrics for the practicing cardiovascular clinician with an emphasis on the following: 1) measurement techniques and accuracy of common health metrics; 2) pitfalls in CWD interpretation; 3) recommendations for interpretation of abnormal results; 4) the use of CWDs in exercise prescription; 5) important considerations pertaining to health disparities and inequity in the use of CWDs; and 6) future considerations for CWD development.

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Table 1. Differential Diagnosis and Recommended Testing to Consider for Abnormal Health Metrics From Consumer Wearable Devices
Metric	Differential Diagnosis	Confirmatory Diagnostic Testing to Be Considered	Additional Testing Considerations^a
Low heart rate (resting conditions)	Wearable device heart rate measurement failure Bradyarrhythmia Sinoatrial node dysfunction, high grade atrioventricular block Sinus bradycardia Anorexia/malnutrition, CNS disease, hypothermia, hypothyroidism, exercise training, medication effect, sleep apnea, increased vagal tone	• 12-lead ECG • Clinically approved ambulatory rhythm monitor	Bradyarrhythmia Refer to AHA/ACC guidelines following arrhythmia confirmation^b Sinus bradycardia • Careful medication history • Laboratory studies (BMP, TSH) • Sleep study
High heart rate (resting conditions)	Wearable device heart rate motion artifact Tachyarrhythmia Paroxysmal supraventricular tachycardia, ventricular tachycardia Sinus tachycardia Anxiety, dehydration, anemia, medication effect (eg, beta-blocker withdrawal, beta agonist), infection, heart failure, hyperthyroidism, pain, POTS, pregnancy, PE, shock, stimulant use, inappropriate sinus tachycardia	• 12-lead ECG • Clinically approved ambulatory rhythm monitor	Tachyarrhythmia Refer to AHA/ACC guidelines following arrhythmia confirmation^b Sinus tachycardia • Careful medication history • Laboratory studies (BMP, CBC, D-dimer, TSH, iron studies) • TTE
Low SpO₂ (resting conditions)	Wearable device SpO₂ measurement failure High altitude Hypoventilation Chest wall pathology (eg, kyphoscoliosis), CNS disease, sedatives, hypothyroidism, metabolic alkalosis, OSA, respiratory muscular weakness (eg, ALS) V/Q mismatch or shunt ARDS, asthma, atelectasis, pulmonary AVM, bronchiectasis, COPD, pulmonary edema (cardiac and noncardiac), ILD, intracardiac shunt, mucus plugging, PE, PNA	• Clinically approved pulse oximetry • Arterial blood gas	• Careful medication history • Chest radiography • Laboratory studies (D-dimer) • PFTs • TTE with bubble study
Irregular heart rhythm (resting conditions and during exercise)	Wearable device heart rate measurement failure Wearable device heart rate motion artifact Arrhythmia Respiratory sinus arrhythmia	• 12-lead ECG • Clinically approved ambulatory rhythm monitor	Arrhythmia Refer to AHA/ACC guidelines following arrhythmia confirmation^b Sinus arrhythmia No further testing recommended
HRV (low)	Wearable device heart rate measurement failure Aging Physical deconditioning Inadequate recovery/overtraining Infection Medication effect Mental stress Poor sleep Systemic illness Toxins (eg, EtOH) Thermal stress (warmer temperatures)	• Detailed medical and social history	No further testing recommended
HRR (low)	Wearable device heart rate measurement failure Physical deconditioning Medication effect Systemic illness Tachyarrhythmia	• Detailed medical and social history	• Exercise ECG with postrecovery monitoring
Peak V̇O₂ (low)	Wearable device V̇O₂ algorithm inaccuracy Physical deconditioning Cardiopulmonary disease Anemia Skeletal muscular disease (myopathy)	• CPET	• Laboratory studies (CBC)
High respiratory rate (resting conditions and during exercise)	Wearable device RR motion artifact Anxiety Cardiac disease (arrhythmia, ischemia, heart failure) Diabetic ketoacidosis Anemia Exercise Fever/sepsis Pulmonary disease (asthma, COPD, effusion, ILD, PE) Toxins	• Visual assessment and manual assessment of respiratory rate	• Chest radiography • Laboratory studies (ABG, CBC, CMP, toxicology) • PFTs
Low respiratory rate (resting conditions and during exercise)	Wearable device RR measurement failure CNS disease Hypothyroidism Medication effect Sleep apnea Toxins (eg, opiates)	• Visual assessment and manual assessment of respiratory rate	• Laboratory studies (TSH, toxicology) • Sleep study
Sleep (poor sleep)	Wearable device heart rate and/or RR measurement failure Dehydration Medication effect (eg, stimulants) Sleep disorder (eg, restless leg, syndrome, sleep apnea) Stress/anxiety Toxins (eg, EtOH)	• Detailed medical and social history	• Laboratory studies (iron studies) • Sleep study

^aA thorough history and physical examination is recommended as the starting point in the evaluation of all abnormal testing. ^bFor confirmed bradyarrhythmia, refer to the 2018 AHA/ACC/HRS guideline on the evaluation and management of patients with bradycardia and cardiac conduction delay.¹⁰² For confirmed tachyarrhythmia, refer to the 2015 AHA/ACC/HRS guideline for the management of adult patients with supraventricular tachycardia¹⁰³ or the 2017 AHA/ACC/HRS guideline for management of patients with ventricular arrhythmias and the prevention of sudden cardiac death¹⁰⁴ or the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation¹⁰⁵/2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation.¹⁰⁶
ABG = arterial blood gas; ARDS = acute respiratory distress syndrome; AVM = arteriovenous malformation; BMP = basic metabolic panel; CMP = comprehensive metabolic panel; CNS = central nervous system; COPD = chronic obstructive pulmonary disease; EtOH = alcohol; ILD = interstitial lung disease; OSA = obstructive sleep apnea; PE = pulmonary embolism; PFT = pulmonary function test; PNA = pneumonia; POTS = postural orthostatic tachycardiac syndrome; RR = respiratory rate; TSH = thyroid stimulating hormone; TTE = transthoracic echocardiography.

Table 2. Common Factors Affecting the Accuracy of Photoplethysmography Signals
Obesity
Darker skin tone
Tattoos
Decreased skin perfusion
Cold body temperature
Wrist body location
Inadequate skin contact
Motion
Ambient light

Table 3. Future Considerations for Consumer Wearable Device Design, Research, and Implementation
Promote studies comparing CWD technology with gold-standard reference devices in diverse cohorts of patients and environmental conditions.^5,72,99
Assess the safety and outcomes of CWDs for telemonitoring in patients with established forms of cardiovascular disease.^108,109
Optimize and study the accuracy of CWD technology in the measurement of health metrics during exercise (eg, exercise-induced arrhythmias).¹¹⁰
Assess how intraindividual alterations in CWD-derived health metrics affect outcomes in those with and without cardiovascular disease.
Study the effect of artificial intelligence on health metric measurement and interpretation.¹⁰⁹
Involve HCPs in CWD design and implementation to ensure clinically relevant health metrics and data reporting.^2,109
Prioritize data security for patients and accessibility to CWD data for HCPs in electronic health records.^2,6
Promote transparency surrounding medico-legal liability for HCPs being sent and interpreting data from CWDs.^6,44
Ensure equitable distribution of CWDs with consideration of incentives to alleviate costs for CWDs following medical approval.^44,111
Promote equitable compensation for HCPs in the interpretation of data from CWDs.^111,112
Develop ongoing CME for providers on interpretation of current and emerging CWD technology and to design and study the effect of educational tools to promote digital health literacy.^6,44,109