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All Journal International Journal of Electrical and Computer Engineering
Sri, Pali Ramya
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Computer Science & IT Electrical & Electronics Engineering

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Prediction of peripheral arterial disease through non-invasive diagnostic approach Mummaneni, Sobhana; Katakam, Lalitha Devi; Sri, Pali Ramya; Lingamallu, Mounika; Ch, Smitha Chowdary; Indira, D.N.V.S.L.S
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5782-5791

Abstract

Peripheral arterial disease (PAD) is a cardiovascular condition caused by arterial blockages and poor blood circulation, increasing the risk of severe complications such as stroke, heart attack, and limb ischemia. Early and accurate detection is essential to prevent disease progression and improve patient outcomes. This study introduces a non-invasive diagnostic method using laser doppler flowmetry (LDF), electrocardiography (ECG), and photoplethysmography (PPG) to assess vascular health. LDF measures microvascular blood flow, ECG evaluates heart rate variability, and PPG captures pulse waveform characteristics. Key physiological features such as blood flow variability, pulse transit time, and hemodynamic responses are extracted and analyzed using machine learning. Random forest and XGBoost models are employed and combined using ensemble learning to classify individuals into non-PAD, moderate PAD, and severe PAD categories. A comparative evaluation shows that the ensemble model delivers superior classification accuracy. This integrated system offers a fast, reliable screening tool that supports early PAD detection and intervention. By combining multimodal signal analysis with machine learning, the approach enhances diagnostic precision and provides a scalable solution for preventive cardiovascular care.
Co-Authors Ch, Smitha Chowdary Indira, D.N.V.S.L.S Katakam, Lalitha Devi Lingamallu, Mounika Mummaneni, Sobhana