Machine Learning-Based Peripheral Artery Disease Identification Using Laboratory-Based Gait Data
Ali Al-Ramini1, Mahdi Hassan2,3, Farahnaz Fallahtafti2,3
1Mechanical Engineering Department, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.
Sensors (Basel, Switzerland)
|October 14, 2022
Summary
Machine learning models can identify peripheral artery disease (PAD) using gait analysis. This approach accurately detects PAD through biomechanical data, aiding early diagnosis and treatment.
Area of Science:
- Biomechanics
- Machine Learning
- Medical Diagnostics
Background:
- Peripheral artery disease (PAD) stems from atherosclerosis, impairing leg blood flow and altering muscle function and gait.
- Underdiagnosis of PAD delays treatment, leading to poorer clinical outcomes.
Purpose of the Study:
- To develop machine learning (ML) models for early identification of individuals with PAD.
- To establish ML as a tool for distinguishing PAD patients from healthy individuals.
Main Methods:
- Utilized overground walking biomechanics data from PAD patients and healthy controls.
- Gait signatures analyzed included joint angles, torques, powers, and ground reaction forces (GRF).
- Developed classification models using Neural Networks and Random Forest algorithms.
Main Results:
- ML models achieved 89% accuracy in classifying PAD using all gait variables.
- Models using only GRF variables reached 87% accuracy.
- GRF-based ML models provided the most informative data for PAD classification.
Conclusions:
- ML models can effectively classify individuals with and without PAD based on gait signatures.
- Gait analysis combined with ML shows promise for early PAD detection.
- GRF features are particularly valuable for ML-based PAD classification.
Related Concept Videos
01:21Peripheral Arterial Disease II: Clinical Manifestations and Diagnostic Evaluation
25
Clinical manifestationsPeripheral Arterial Disease (PAD) manifests through a range of symptoms, from the characteristic intermittent claudication to atypical presentations and severe complications in advanced stages. Intermittent claudication, a hallmark symptom of PAD, presents as exercise-induced muscle pain that typically resolves within minutes of rest. This pain is reproducible and stems from inadequate blood flow, leading to the accumulation of lactic acid produced during anaerobic...
25
01:30Peripheral Artery Disease I: Introduction
23
Peripheral artery disease (PAD) predominantly results from atherosclerosis, which involves the accumulation of fatty deposits, or plaques, within the walls of arteries. This causes them to narrow and harden, significantly reducing blood flow. PAD predominantly affects the legs, particularly the arteries supplying the thighs and calves. In rare cases, it may involve other arteries, including those in the arms.Etiology of PAD:The principal cause of PAD is atherosclerosis, which results from fatty...
23
01:27Peripheral Artery Disease III: Interprofessional Care
21
Peripheral Artery Disease (PAD) is characterized by narrowed arteries that diminish blood flow to the extremities. Effective management of PAD requires an interprofessional approach involving various healthcare professionals. The critical aspects of interprofessional care for PAD patients focus on risk factor modification, drug therapy, exercise therapy, nutrition therapy, critical limb ischemia care, and interventional radiology and surgical procedures.The primary treatment goal for PAD...
21
01:26Peripheral Artery Disease IV: Nursing Management
24
The nursing management of a patient with peripheral artery disease (PAD) begins with a thorough assessment of the patient’s health history and clinical manifestations.AssessmentHealth History: Evaluate the patient’s history of hypertension, hyperlipidemia, family history of cardiovascular issues, and lifestyle factors such as dietary patterns, smoking, and physical activity.Physical Examination:Assess the affected extremity for decreased or absent peripheral pulses,...
24