ICare Health Monitor V3.9.5 FULL [Latest]
Miina Hunker
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Smart wearables generate a plethora of data through various sensors and software algorithms and understanding their basic engineering principles and limitations can be helpful for clinicians and scientists.
Evidence supports the use of wearable devices in cardiovascular risk assessment and cardiovascular disease prevention, diagnosis and management, but large, well-designed trials are needed to establish their advantages.
Several challenges still hinder the widespread adoption of wearables in clinical practice, including a concern for device accuracy, patient privacy and cost, and how to separate actionable data from noise.
Overcoming these challenges requires that various stakeholders come together to develop comprehensive evaluation frameworks, pragmatic regulatory policies, clinical trials and medical education curricula.
Heart rate (HR) measurements during rest and exercise can be used to predict the risk of cardiovascular disease. In healthy populations, a high resting HR has been associated with an increased risk of coronary artery disease and all-cause death12 and is also well recognized as a predictor of adverse outcomes in patients with heart failure (HF)13. An impaired HR recovery after exercise correlates with increased adverse cardiovascular events14. HR variability (HRV) has also been strongly linked to the risk of adverse cardiovascular events in healthy individuals and in patients with HF with reduced ejection fraction15.
Commercial wearables measure HR and heart rhythm through electrocardiography (ECG) or photoplethysmography (PPG) by calculating beat-to-beat time intervals and using algorithms to classify heart rhythm. ECG sensors come in various forms and are the gold standard for HR and heart rhythm measurement. Chest-strap monitors and ECG patches provide continuous monitoring of heart rhythm but are less appealing to the average consumer than other options such as smartwatches given their bulkiness, limited functions and long-term inconvenience. Some smartwatches can record a single-lead ECG as needed by placing a contralateral finger on the crown (negative electrode on the side of the watch), with the back of the watch serving as the positive electrode16. Single-lead ECGs are useful to diagnose simple and common arrhythmias such as atrial fibrillation (AF). However, these single-lead ECGs are often insufficient for the accurate diagnosis of more complex arrhythmias and other conditions such as myocardial infarction (MI) or to detect interval abnormalities unless specific manoeuvres are deployed17.
PPG measures changes in microvascular blood volume that translate into pulse waves and a tachogram recording18. An emitter sends a continuous pulse of photons through the skin and a photodetector measures the variable intensity of reflected photons from the tissue18. Most wearables continuously activate the PPG during exercise whereas, during rest and sleep, PPG measurements occur only intermittently to preserve battery life. PPG tachograms, especially when augmented by single-lead ECG, can also identify arrhythmias19. Nevertheless, PPG technology has limitations. The main drawback is that the sensor works best when in direct contact with the skin, which is not always the case with wearables secured with straps. Skin colour, moisture and even tattoos have also been postulated to affect PPG accuracy20, although one study showed similar device performance across a full range of skin tones21.
Given the variability in HR accuracy of PPG sensors across different wearable devices, a number of studies have directly compared their performance. One study that investigated the accuracy of the Apple Watch 3 (Apple, USA) and the Fitbit Charge 2 (Fitbit, USA) showed that both devices provided an acceptable PPG sensor HR accuracy (
Biochemical sensors can measure body fluid electrolytes with the use of electrochemical transducers, offering valuable information about plasma volume status and analyte concentrations30. However, the accuracy of these sensors changes with skin temperature, skin contamination with dust, dried sweat or other substances, and hair density. One example of biochemical sensors are the minimally invasive continuous glucose monitors that have been clinically validated but are difficult to embed in consumer-grade wearables and mostly function as a stand-alone product31. Non-invasive sensors of sweat and saliva might be more practical to integrate into wearables but still need to be carefully evaluated32.
Biomechanical sensors incorporated into clothing or shoes, such as ballistocardiograms, seismocardiograms and dielectric sensors, have been developed in an attempt to passively and continuously measure variables such as cardiac output, lung fluid volume and weight1, which could be beneficial in managing conditions such as HF. Other biomechanical sensors, such as flexible, tattoo-like sensors based on microfluidics, are also promising for non-invasive, haemodynamic, continuous monitoring. However, all these emerging sensors still require extensive clinical validation33.
Figure 1 summarizes common smart wearable devices, their embedded sensors and their applications in cardiovascular care. Table 1 lists common wearable products on the market, the published studies on these products and their regulatory status.
Summary of common commercial smart wearables available on the market, where they are worn on the body, their built-in sensors, and the different types of measurements collected by each sensor and their various cardiovascular clinical applications. BP, blood pressure; CVD, cardiovascular disease; ECG, electrocardiogram; GPS, Global Positioning System; HR, heart rate; HRR, heart rate recovery; HRV, heart rate variability; PPG, photoplethysmography; SaO2, oxygen saturation.
In this section, we discuss the literature supporting the use of wearable devices in cardiovascular patient care, reviewing the critical clinical studies on the most common cardiovascular applications published in the past 15 years (Table 2).
Global cardiovascular disease risk assessment is traditionally based on clinical risk scores that estimate the 10-year risk. However, most of these scores do not capture the dynamic changes in personalized risk that closely follow lifestyle habits. The incorporation of subjective lifestyle behaviours in risk assessment has been challenging; therefore, objective data derived from wearables provide a renewed opportunity to make the assessment of the risk of cardiovascular disease more accurate, comprehensive and dynamic over a lifetime. Several studies have shown wearable-measured physical activity to have an inverse dose-dependent relationship with all-cause mortality5,34,35,36,37,38. Moderate-to-vigorous physical activity (MVPA), measured with the use of triaxial accelerometers, was associated with a lower mortality than light physical activity or sedentary behaviour in several US cohorts and in a Swedish population-based cohort34,35,36,37,38. Another study of women with a mean (s.d.) age of 72 (5.7) years showed that as few as 4,400 steps per day were significantly associated with a 41% reduction in mortality compared with 2,700 steps per day, but the benefits levelled at 7,500 steps per day39. Of note, stepping intensity was not associated with mortality after adjusting for steps per day.
Frequent wearable-generated HR measurements, such as resting average HR, HR recovery and HRV, can potentially be incorporated in cardiovascular risk scores given their correlation with cardiovascular disease, as described in previous sections. Moreover, longitudinal HR data can establish what is normal for an individual and, subsequently, recognize important deviations in lifestyle earlier, before cardiovascular disease develops46. HR-guided training has also been gaining popularity47; however, no clinical trials have examined the benefits of this training.
Initiating hypertension screening in young adulthood is widely recommended to prevent cardiovascular disease24. Oscillometric or cuff-less wearables that accurately measure BP and are continuously worn on the wrist might be more convenient in the ambulatory setting than traditional upper arm BP devices for the screening of hypertension, the self-monitoring of BP and the titration of antihypertensive drugs48. However, dedicated studies on the use of these wearable wrist devices for hypertension screening and management are needed. Continuous wearable BP measurements using novel sensors will potentially facilitate the measurement of BP during sleep or activities such as exercise when oscillometric measurements are not practical. Future studies are needed to determine whether these continuous BP data have any clinical significance33. For example, the continuous measurement of BP can have the potential to detect cardiac arrest or haemodynamic shock, thus saving lives.
The diagnosis of symptomatic arrhythmias has also moved from burdensome strategies, such as the use of bulky Holter monitors, to more convenient wearable monitors. Wearable monitors can provide continuous, single-lead ECG monitoring, such as the Zio patch, or continuous PPG heart rhythm monitoring coupled with as-needed ECG such as the Apple Watch. Although most of these devices are only single lead, they can be as effective or even exceed the ability of conventional Holter monitoring to detect arrhythmias owing to their convenient usability over longer periods of time55,56. A DNN that used single-lead, ambulatory ECG data was able to classify 12 rhythm classes with a high diagnostic performance similar to, and perhaps exceeding, practicing cardiologists57. This technology could be applied to wearables in the future. The IPED study58 was a multicentre, randomized trial that recruited 243 patients who presented to the emergency department with palpitations and presyncope without a clear aetiology. Participants in the IPED study were randomly assigned to an intervention group with KardiaMobile SL (AliveCor, USA) or to standard care. At 90 days, a symptomatic rhythm was detected in 55.6% of participants in the intervention group compared with only 9.5% in the control group. The mean time to symptomatic rhythm detection in the intervention group was 9.5 days compared with 42.9 days in the control group58. Although KardiaMobile is not considered a wearable device, wearables with single-lead ECG can be similarly used to diagnose arrhythmias in patients with palpitations or presyncope.
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