Key result
AI-enabled smartwatch detects 164 bpm irregular rhythm, prompting diagnosis and treatment of idiopathic fascicular VT.
Why the study?
The efficacy and safety of machine learning in healthcare have raised questions, making it important to assess how AI-enabled devices affect the detection of cardiac conditions.
Case Report (n=1)
AI-enabled smartwatches can potentially aid in the early detection of life-threatening arrhythmias like idiopathic ventricular tachycardia, prompting timely clinical intervention.
Answers are grounded in this paper and cite their sources.
May support early VT detection in symptomatic patients; hypothesis-generating and requires prospective validation.
Cardiovascular disease has become a huge burden to human health. Artificial intelligence (AI)-enabled smartwatches continuously monitor the heart rate, which potentially helps to diagnose unwarranted rhythm and irregularity problems such as tachycardia, bradycardia, and fibrillation. Deep learning (DL), convolutional neural networks (CNN), and support vector machines are various modalities of AI adopted in the field of cardiology extensively, starting from a single echocardiogram to cardiac imaging. Yet, the efficacy and safety of machine learning in healthcare have always raised valid questions for the manufacturers of various healthcare devices. It is thus challenging and promising to see how AI in medicine will affect human lives in tackling various medical conditions along with global threats such as pandemics. A case report on idiopathic ventricular tachycardia (VT) detected by an AI-aided smartwatch is presented in this paper.
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Kumar et al. (2023) conducted a case report in Idiopathic Ventricular Tachycardia (n=1). AI-enabled smartwatch (Fitbit Sense) was evaluated on Detection of ventricular tachycardia. An AI-enabled smartwatch successfully detected an irregular heart rate of 164 beats per minute, leading to the diagnosis and treatment of idiopathic fascicular ventricular tachycardia.
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