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Portable Holter with Cloud-Based Learning Analytics for Real-Time Health Monitoring | ||
| Journal of Biomedical Physics and Engineering | ||
| مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 24 تیر 1404 اصل مقاله (1.42 M) | ||
| نوع مقاله: Technical Note | ||
| نویسندگان | ||
| Abdi Dharma* 1؛ Poltak Sihombing1؛ Syahril Efendi1؛ Herman Mawengkang2؛ Arjon Turnip3 | ||
| 1Department of Computer Science, Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Medan, Indonesia | ||
| 2Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Sumatera Utara, Medan, Indonesia | ||
| 3Department of Electrical Engineering, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Bandung, Indonesia | ||
| چکیده | ||
| The increasing prevalence of cardiovascular diseases underscores the need for efficient and user-friendly tools to monitor heart health. Traditional Holter monitors, while effective, are often bulky and inconvenient, limiting their use in real-world scenarios. This study introduces the Smart Portable Holter, a wireless device designed for real-time cardiac monitoring, enabling early detection of heart irregularities with enhanced accuracy and user convenience. The device captures continuous electrocardiogram signals and transmits them to a secure cloud platform for processing. Machine learning models, including Random Forest and Extreme Gradient Boosting (XGBoost), analyze the data to detect cardiac events. The system’s performance was evaluated using real-world datasets, emphasizing accuracy and reliability in identifying cardiac arrhythmias. The Smart Portable Holter delivers an impressive 98% accuracy in detecting cardiac events. Its compact and wireless design enhances user comfort, allowing for seamless wear throughout the day. Coupled with advanced analytics, it offers detailed, time-stamped records that empower both users and healthcare professionals. These features facilitated early diagnosis and supported personalized treatment planning for patients with varying cardiac conditions. The Smart Portable Holter represents a significant advancement in cardiac care, combining portability, real-time analytics, and high diagnostic accuracy. By empowering patients and healthcare providers with actionable insights, it fosters proactive heart health management and contributes to improved clinical outcomes. | ||
| کلیدواژه‌ها | ||
| Electrocardiogram؛ Early Diagnosis؛ Cardiac Arrhythmias؛ Holter Monitoring؛ XGBoost؛ Arrhythmias, Cardiac؛ Machine Learning | ||
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آمار تعداد مشاهده مقاله: 8 تعداد دریافت فایل اصل مقاله: 1 |
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