Documentdetail
ID kaart
oai:arXiv.org:2211.06951
Onderwerp
Electrical Engineering and Systems...Auteur
Ghuman, Purnoor Lyall, Tyama Mahboob, Usama Aamir, Alia Liu, XilinCategorie
wetenschappen: elektrotechniek en systeemkunde
Jaar
2022
vermelding datum
25-09-2023
Trefwoorden
parkinsonBeschrijving
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
Choice Between Partial Trajectories: Disentangling Goals from Beliefs
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