Heart Rate Health Classification in Patients During Physical Activities Using K-Nearest Neighbors

Cardiovascular diseases, encompassing a range of disorders affecting the heart and blood vessels, are the leading cause of death worldwide. The fact that cardiovascular diseases account for at least 32% of all global deaths per year is a significant indicator of its impact. This emphasizes the urgency of early detection approaches, enabling patients to receive faster diagnoses and earlier treatment. In this report, the authors utilize the K-Nearest Neighbors method to classify patients' health conditions from electrocardiogram (ECG) data during sitting, walking, and running activities. The objective is to enhance the accuracy of heart rate and arrhythmia detection while contributing to global heart disease prevention efforts. The results of the K-Nearest Neighbors classification demonstrate excellent performance, with an accuracy of 91.9%, precision of 90%, recall of 90%, and an F1-score of 90%.