The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Quantum-SVM (SVM) for Parkinson's Disease Prediction Using Wearable IoT Sensors
|
|
Author(s): N. Jagadish Kumar (SRM Institute of Science and Technology, India), Chin-Shiuh Shieh (National Kaohsiung University of Science and Technology, Taiwan), Mong-Fong Horng (National Kaohsiung University of Science and Technology, Taiwan), G. Elangovan (SRM Institute of Science and Technology, India)and K. Rajkumar (SRM Institute of Science and Technology, India)
Copyright: 2026
Pages: 34
Source title:
Enhancing Autonomous and Adaptive Systems With AI and IoT
Source Author(s)/Editor(s): Ben Othman Soufiene (King Faisal University, Saudi Arabia)
DOI: 10.4018/979-8-3373-3146-1.ch013
Purchase
|
Abstract
The amalgamation of wearable IoT sensors with QSVM technology is transforming the early identification and ongoing surveillance of Parkinson's Disease (PD). This chapter examines the enhancement of PD diagnostics through quantum machine learning by evaluating real-time kinematic data from various sensors. Traditional models such as Classical SVM, RF, and DNN encounter difficulties due to the intricacy and high dimensionality of time-series sensor data. QSVM, employing Variational Quantum Circuits, optimizes feature extraction and classification, thereby diminishing computational requirements while improving accuracy. In benchmark evaluations, QSVM attained an accuracy of 97.2%, exceeding that of Classical SVM, RF, and DNN, and concurrently decreasing computational time by 35%. The efficacy of QSVM, in conjunction with edge computing and federated learning, has the potential to revolutionize personalized, privacy-centric healthcare. Notwithstanding the constraints of quantum hardware, QSVM presents significant promise in enhancing PD diagnosis and advancing intelligent healthcare.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|