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Analysis of correlation between an accelerometer-based algorithm for detecting parkinsonian gait and UPDRS subscales

Autor
Rodríguez, A.; Sama, A.; Perez, C.; Rodriguez-Martin, D.; Alcaine, S.; Mestre, B.; Quispe, P.; Giuliani, B.; Vainstein, G.; Browne, P.; Sweeney, D.; Moreno, J.; Bayés, À.; Lewy, H.; Costa, A.; Annicchiarico, R.; Counihan, T.; ÓLaighin, G.; Cabestany, J.
Tipus d'activitat
Article en revista
Revista
Frontiers in Neurology
Data de publicació
2017-09-01
Volum
8
Pàgina inicial
1
Pàgina final
6
DOI
https://doi.org/10.3389/fneur.2017.00431 Obrir en finestra nova
Projecte finançador
Personal Health Device for the Remote and Autonomous Management of
Repositori
http://hdl.handle.net/2117/108053 Obrir en finestra nova
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585138/ Obrir en finestra nova
URL
http://journal.frontiersin.org/article/10.3389/fneur.2017.00431/full Obrir en finestra nova
Resum
Background: Our group earlier developed a small monitoring device, which uses accelerometer measurements to accurately detect motor fluctuations in patients with Parkinson’s (On and Off state) based on an algorithm that characterizes gait through the frequency content of strides. To further validate the algorithm, we studied the correlation of its outputs with the motor section of the Unified Parkinson’s Disease Rating Scale part-III (UPDRS-III). Method: Seventy-five patients suffering from ...
Citació
Rodríguez, A., Sama, A., Perez, C., Rodriguez-Martin, D., Alcaine, S., Mestre, B., Quispe, P., Giuliani, B., Vainstein, G., Browne, P., Sweeney, D., Moreno, J., Bayés, À., Lewy, H., Costa, A., Annicchiarico, R., Counihan, T., ÓLaighin, G., Cabestany, J. Analysis of correlation between an accelerometer-Based algorithm for Detecting Parkinsonian gait and UPDRS subscales. "Frontiers in Neurology", 1 Setembre 2017, vol. 8, p. 1-6.
Paraules clau
Accelerometers, Gait, Objective monitoring, Parkinson's disease, UPDRS
Grup de recerca
CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma
ISSET - Integrated Smart Sensors and Health Technologies

Participants

Arxius