scholarly journals A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson’s Disease Patients

Sensors ◽  
2017 ◽  
Vol 17 (4) ◽  
pp. 827 ◽  
Author(s):  
Daniel Rodríguez-Martín ◽  
Carlos Pérez-López ◽  
Albert Samà ◽  
Andreu Català ◽  
Joan Moreno Arostegui ◽  
...  
Sensors ◽  
2013 ◽  
Vol 13 (10) ◽  
pp. 14079-14104 ◽  
Author(s):  
Daniel Rodríguez-Martín ◽  
Carlos Pérez-López ◽  
Albert Samà ◽  
Joan Cabestany ◽  
Andreu Català

2004 ◽  
Vol 51 (8) ◽  
pp. 1434-1443 ◽  
Author(s):  
A. Salarian ◽  
H. Russmann ◽  
F.J.G. Vingerhoets ◽  
C. Dehollain ◽  
Y. Blanc ◽  
...  

2018 ◽  
Vol 139 ◽  
pp. 119-131 ◽  
Author(s):  
Julià Camps ◽  
Albert Samà ◽  
Mario Martín ◽  
Daniel Rodríguez-Martín ◽  
Carlos Pérez-López ◽  
...  

2007 ◽  
Vol 26 (2) ◽  
pp. 200-207 ◽  
Author(s):  
Steven T. Moore ◽  
Hamish G. MacDougall ◽  
Jean-Michel Gracies ◽  
Helen S. Cohen ◽  
William G. Ondo

2019 ◽  
Vol 13 (1) ◽  
pp. 10-16
Author(s):  
Laura Carolina Rozo Hoyos ◽  
Juan Pablo Pulgarín González ◽  
Paula Andrea Morales Fandiño ◽  
Jonathan Gallego Londoño

The episodes of Freezing of Gait (FOG) are a recurring symptom in people suffering from advanced stages of Parkinson's disease (PD). These are severe occurrences because they may cause falls to the patients, generating further traumas and concussions. In order to solve this yet ineffectively treated issue, this article describes the research that developed a device capable of predicting freezing episodes. On this project a wearable device was developed, which was able to predict freezing episodes based on the calculation of a freezing index (FI) determined by the signals obtained from an inertial measurement unit (IMU). This device was tested in three Patients and signals corresponding to normal gait and simulated Parkinson gait were taken. The results showed that FI obtained from Parkinson gait were much higher than those from a normal gait, validating this parameter as a key aspect in FOG prediction.      


2004 ◽  
Vol 43 (8) ◽  
pp. 685-692 ◽  
Author(s):  
Naoshi SAITO ◽  
Teiji YAMAMOTO ◽  
Yoshihiro SUGIURA ◽  
Saori SHIMIZU ◽  
Masaru SHIMIZU

Author(s):  
Tetiana Biloborodova ◽  
Inna Skarga-Bandurova ◽  
Oleksandr Berezhnyi ◽  
Maksym Nesterov ◽  
Illia Skarha-Bandurov

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