Why the study?
Conventional myocardial infarction detection requires expensive and inconvenient medical tests such as blood tests or wearable ECG sensors that can only be performed in medical institutions.
Does the Health-Radio contactless radar-based system accurately detect myocardial infarction compared to healthy controls?
Does the Health-Radio contactless radar-based system accurately detect myocardial infarction compared to healthy controls?
A novel contactless radar-based system can detect myocardial infarction via heart rate variability with moderate to high accuracy, offering a potential tool for smart-home healthcare.
Answers are grounded in this paper and cite their sources.
May support contactless MI detection in controlled settings; leaves open prospective validation before clinical use.
Myocardial infarction (MI) is the myocardial necrosis caused by persistent ischemia and hypoxia of coronary arteries. People do not realize that they are suffering from MI until they have a heart attack. Early MI detection plays a vital role in symptom relief and improvement in the performance of daily activities. However, conventional MI detection methods require expensive and inconvenient medical tests, e.g., intrusive blood tests or wear electrocardiogram (ECG) sensors, which can only be performed in medical institutions. In this paper, we introduce a contactless and non-intrusive MI detection method based on wireless sensing that monitors abnormalities in heartbeats. Specifically, we present Health-Radio, a radar-based system towards early MI detection. Health-Radio extracts heart rate variability (HRV) from the RF signals reflected from users. In particular, with our carefully designed signal processing algorithms, Health-Radio is able to not only obtain heartbeat signals when the user is stationary, but also tolerate interference when the user is performing certain activities, e.g., eating, reading and browsing the Internet. We have recruited 30 MI patients from the Central Hospital of Wuhan, China, and 30 healthy university students to conduct comprehensive evaluations of the performance of Health-Radio. The experiment results show that Health-Radio can achieve a median MI detection accuracy of 81.2 percent when the users are stationary, which is comparable to ECG-based MI detection. Even when the users are not stationary, Health-Radio can still achieve a median detection accuracy of 66.5 percent. Health-Radio is promising in providing a new paradigm for smart-home healthcare in the future.
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Zhang et al. (2020) studied this question.
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