detalle del documento
IDENTIFICACIÓN
oai:arXiv.org:2211.06951
Tema
Electrical Engineering and Systems...Autor
Ghuman, Purnoor Lyall, Tyama Mahboob, Usama Aamir, Alia Liu, XilinCategoría
ciencias: ingeniería eléctrica y ciencia de sistemas
Año
2022
fecha de cotización
25/9/2023
Palabras clave
parkinsonResumen
Parkinson's disease is a common neurological disease, entailing a multitude of motor deficiency symptoms.
In this project, we developed a device with an uploaded edge machine learning algorithm that can detect the onset of freezing of gait symptoms in a Parkinson's patient.
The algorithm achieved an accuracy of 83.7% in a validation using data from ten patients.
The model was deployed in a microcontroller Arduino Nano 33 BLE Sense Board model and validated in real-time operation with data streamed to the microcontroller from a computer.
Ghuman, Purnoor,Lyall, Tyama,Mahboob, Usama,Aamir, Alia,Liu, Xilin, 2022, ECE496Y Final Report: Edge Machine Learning for Detecting Freezing of Gait in Parkinson's Patients
Optimal Sensing of Momentum Kicks with a Feedback-Controlled Nanomechanical Resonator
sensing momentum kicks resonator
Shared genetic aetiology of Alzheimer’s disease and age-related macular degeneration by APOC1 and APOE genes
gene diagnostic based analysis amd ad apoe apoc1 identified genes pleiotropy
