Introduction
In the last decade, consumer technologies have seen significant advancements in monitoring cardiovascular parameters. What started as devices primarily focused on tracking exercise markers has evolved to include physiological and health-care-related measurements. With the belief that these devices can help identify and monitor cardiovascular disease, the public has eagerly adopted them. Consequently, clinicians are now frequently presented with health app data accompanied by a wide range of concerns and queries. The original article assesses the accuracy of these devices, validates their outputs, and evaluates their suitability for professionals to make management decisions. We delve into the underlying methods and technologies, exploring the evidence supporting their use as diagnostic and monitoring tools across various cardiovascular conditions.
Devices, Data, and Apps
Wearable medical devices, such as ambulatory blood pressure and electrocardiogram (ECG) monitors, have been used in healthcare for decades. Today, devices accessible to the public, including smartphones, wristbands, watches, scales, shirts, rings, and eyeglasses, incorporate similar functionality. Patients have recognized the potential of these technologies and often bring health app-derived data to their doctors. While physicians acknowledge their potential usefulness, they are uncertain about the evidence base and appropriate utilization of such data.
The measurements obtained from wearable devices range from established parameters like heart rate, blood pressure, and oxygen saturation to more nuanced metrics such as step counts, minutes of activity, heart rate variability, and intrathoracic impedance. Wireless technology enables the integration of multiple sensors, combining different signals to enhance measurement accuracy or compute parameters indirectly. WiFi connectivity facilitates continuous and simultaneous monitoring of multiple parameters, with data upload to cloud storage, enabling prompt clinician notification of significant changes. Software apps process and curate data from raw sensor signals, presenting relevant information in user-friendly graphical displays on smartphones, smartwatches, or personal computers. These apps can also provide health advice based on physical activity levels or forward sensor data directly to healthcare providers.
Challenges and Future Perspectives
The ubiquity of wearable devices raises concerns about their use in clinical decision-making without adequate validation. Despite numerous studies, wearable devices have yet to demonstrate improvement in defined medical outcomes. Thus, further research is necessary to identify both the risks and benefits to patients and healthcare systems. Medical training needs to address these risks and benefits as the evidence base grows, along with the challenge of managing large volumes of disparate device data.
Cardiologists, accustomed to assessing traditional cardiovascular symptoms based on patients' subjective descriptions, must now assimilate data from these new sources and eventually use them to monitor treatment responses. Machine learning and artificial intelligence offer potential applications for analyzing data from wearable devices, uncovering novel associations in diagnosis, risk prediction, and treatment choices. Additionally, advancements in sensor technology, including the emergence of smart fabrics, will expand the possibilities. These fabrics incorporate innovative sensing methods, enabling the integration of biomedical sensing technology into clothing and wearable devices.
The regulatory landscape for digital healthcare must develop rapidly to ensure the safe and effective use of wearable technologies. Public trust and acceptance are vital factors in their widespread adoption. Ideally, wearables could help reduce healthcare inequalities, provided they are affordable and accessible to individuals who may struggle with the technology due to a lack of familiarity or specific health conditions. The combination of wearables and telemedicine has the potential to revolutionize community care and reduce acute hospital admissions and healthcare spending.
Conclusion
Wearable technologies have the potential to enhance cardiovascular healthcare by providing valuable insights into patients' symptoms, activity levels, comorbidities, and context. However, their integration into clinical practice requires thorough validation, addressing risks, and demonstrating clear benefits in improving medical outcomes. As advancements continue, wearables, combined with machine learning and sensor technology, hold promise for diagnosing, predicting risks, and personalizing treatment approaches.
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