0% Complete
صفحه اصلی
/
سی و دومین کنفرانس بین المللی مهندسی برق
Non-contact Radar Technology and Machine Learning for Automated Sleep Apnea-Hypopnea Syndrome Detection
نویسندگان :
ُSaman Faridsoltani
1
Mohaddeseh Sadeghi
2
Zahra Rahmani
3
Somayyeh Chamaani
4
1- دانشگاه خواجه نصیر الدین طوسی
2- دانشگاه صنعتی خواجه نصیرالدین طوسی
3- دانشگاه صنعتی خواجه نصیرالدین طوسی
4- دانشگاه صنعتی خواجه نصیرالدین طوسی
کلمات کلیدی :
Sleep Apnea-Hypopnea Syndrome،Impulse-radio ultra-wideband radar،Variational mode decomposition،APNIWAVE database،Random forest
چکیده :
Sleep Apnea-Hypopnea Syndrome (SAHS) is a prevalent sleep disorder that significantly affecting patients' quality of life, often going undetected due to its appearance during sleep. The current gold standard for SAHS detection, polysomnogram, is costly and inconvenient for long-term monitoring. This paper introduces a novel method using non-contact Impulse-Radio Ultra-Wideband (IR-UWB) radar and machine learning to automatically detect apnea-hypopnea events. Initially, after selecting the appropriate target range bins from each radar data, the Variational Mode Decomposition (VMD) method is applied to reconstruct de-noised respiratory signals. Then, twenty time-frequency domain features are extracted from each signal, and the most optimal features are opted using the automatic Sequential Forward Feature Selection (SFFS) method. Finally, the selected features are fed into three different classifiers to distinguish between three events: normal, apnea, and others. The APNIWAVE database is used to assess the proposed SAHS detection approach. The results demonstrate an accuracy of 99.5% (with a sensitivity of 99.7%, specificity of 99.5%, and F1-score of 99.5%) in per-segment classification using a Random Forest (RF) classifier. Our method can be employed to create an affordable and reliable system for monitoring SAHS in a household setting.
لیست مقالات
لیست مقالات بایگانی شده
Design, MATLAB Simulation, and Implementation of a Single Inductor Double Output DC-to-DC Converter with Digital Control
Arya Hosseini - Amin Siahchehreh - Samad Sheikhaei
Design and Modelling of a Modified Controller for D-STATCOM Considering Parametric Uncertainties and Unmodeled Dynamics
Majid Arabahmadi - Hossein Khaligh - Amirhossein Moghani - Ali Mosallanejad
Sensor Faults Diagnosis in T-S Fuzzy Discrete Descriptor Systems Using Design a New Unknown Input Observer
Masoud Shafiee - Amir Abolfazl Suratgar - Mehdi Mirshahi
A New Gradient Driver with only a Single DC Voltage Source For Using In MRI Systems
Amirabbas Naghipour Shahrbabaki - Reza Beiranvand
The Effect of Optimal PMU Placement in Power System State Estimation considering the Seasonal Load Curve
Seyed Hamed Mir Mohammad Ali Roudaki - Mehrdad Abedi - Iraj Pourkeivani
Electronic properties of 2D perovskites NMA2PbBr4 and NEA2PbBr4 for PeLED applications: first principle approach
Samad Shokouhi - Seyedeh bita Saadatmand - Vahid Ahmadi
Optimal Energy Management of EVs in intelligent parking lots with Considering solar panels
Noorallah Yavari - Fatemeh Jahanbani Ardakani - Alireza Sedighi Anaraki
Optimal Scheduling of Active Distribution Networks with High Penetration of Plug-in Electric vehicles and Renewables Using Grasshopper Optimization Algorithm
Seyyed Hadi Mousavi - Varahram Janatifar - Arya Abdolahi - Mitra Sarhangzadeh
The Conduction Mechanism in Micron-Thick ZnO Layers Grown on Si Substrates by Spray Pyrolysis
Mohsen Gharesi - Alireza Karimpour - Reza Razmand - Faramarz Hossein-Babaei
Primary Frequency Support in Clustered Unit Commitment with Battery Energy Storage and High Renewable Penetration
Abbas Abdollahi-Veshvaee - Turaj Amraee
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 40.4.2