Automated Author Profile

Santiago, Lorenna Marques de Melo

Current S-Index

0.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.3

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

13.5%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Influence of treadmill training in dual-task gait in people with Parkinson's Disease: a case report

The loss in the automaticity of gait hinders the performance of concurrent activities - Dual Task (DT) - in individuals with Parkinson's disease (PD). One hypothesis for the negative interference of DT on gait is related to the limitation of attention resources in the brain for different activities. When the automation of a task occurs, the negative interference of DT on the gait can be minimized. Because the treadmill promotes automaticity of a better locomotion pattern, due to the repetition that promotes motor learning, the study sought to investigate whether treadmill training can improve the performance of gait on DT in people with PD. Three individuals were evaluated in the on-phase of the antiparkinsonian medication regarding the kinematics (Qualisys Motion Capture System) while in gait, simultaneously performing cognitive activities. Subsequently, the subjects performed a 20-minute workout on the treadmill and were reassessed during gait in cognitive activities. There were increases in the length of the cycle (p=0.01), the length of the step (p=0.01) and in total swing time (p=0.03), and a decrease in the total length of support (p=0.03). These results indicate that treadmill training can promote improvement in the performance of DT on gait in individuals with PD. Longitudinal studies with this focus of research are needed.

Authors

  • Sousa, Angélica Vieira Cavalcanti de ;
  • Santiago, Lorenna Marques de Melo ;
  • Silva, Raphaella Elias de Oliveira da ;
  • Oliveira, Daniel Antunes de ;
  • Galvão, Élida Rayanne Viana Pinheiro ;
  • Lindquist, Ana Raquel Rodrigues
0 Citations0 Mentions13% FAIR0.3 Dataset Index
10.6084/m9.figshare.20015239.v1January 2022

Influence of treadmill training in dual-task gait in people with Parkinson's Disease: a case report

The loss in the automaticity of gait hinders the performance of concurrent activities - Dual Task (DT) - in individuals with Parkinson's disease (PD). One hypothesis for the negative interference of DT on gait is related to the limitation of attention resources in the brain for different activities. When the automation of a task occurs, the negative interference of DT on the gait can be minimized. Because the treadmill promotes automaticity of a better locomotion pattern, due to the repetition that promotes motor learning, the study sought to investigate whether treadmill training can improve the performance of gait on DT in people with PD. Three individuals were evaluated in the on-phase of the antiparkinsonian medication regarding the kinematics (Qualisys Motion Capture System) while in gait, simultaneously performing cognitive activities. Subsequently, the subjects performed a 20-minute workout on the treadmill and were reassessed during gait in cognitive activities. There were increases in the length of the cycle (p=0.01), the length of the step (p=0.01) and in total swing time (p=0.03), and a decrease in the total length of support (p=0.03). These results indicate that treadmill training can promote improvement in the performance of DT on gait in individuals with PD. Longitudinal studies with this focus of research are needed.

Authors

  • Sousa, Angélica Vieira Cavalcanti de ;
  • Santiago, Lorenna Marques de Melo ;
  • Silva, Raphaella Elias de Oliveira da ;
  • Oliveira, Daniel Antunes de ;
  • Galvão, Élida Rayanne Viana Pinheiro ;
  • Lindquist, Ana Raquel Rodrigues
0 Citations0 Mentions13% FAIR0.3 Dataset Index
10.6084/m9.figshare.20015239January 2022