TY - GEN
T1 - Age-sensitive differences in single and dual walking tasks from footprint floor sensor data
AU - Costilla-Reyes, Omar
AU - Scully, Patricia
AU - Ozanyan, Krikor B.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/21
Y1 - 2017/12/21
N2 - Gait can provide insights of executive function decline. We present experiments and methodology for analysing age-sensitive differences in changes of walking patterns on 3 volunteers from three age groups: a young adult, an adult and a mature adult, by using an original footprint imaging floor sensor. The effect of cognitive load tasks in spatio-temporal walking patterns of the volunteers is captured in the experiments. Classification models based on Support Vector Machines (SVM) are applied to raw gait sensor data activities, including single tasks, such as normal and fast walk, as well as dual tasks. For single tasks, we report classifications with a top F-score of 93.36 ± 5.56. Competitive classification performance was obtained for the fine-grained walking variability in the dual task experiments.
AB - Gait can provide insights of executive function decline. We present experiments and methodology for analysing age-sensitive differences in changes of walking patterns on 3 volunteers from three age groups: a young adult, an adult and a mature adult, by using an original footprint imaging floor sensor. The effect of cognitive load tasks in spatio-temporal walking patterns of the volunteers is captured in the experiments. Classification models based on Support Vector Machines (SVM) are applied to raw gait sensor data activities, including single tasks, such as normal and fast walk, as well as dual tasks. For single tasks, we report classifications with a top F-score of 93.36 ± 5.56. Competitive classification performance was obtained for the fine-grained walking variability in the dual task experiments.
KW - dual task analysis
KW - floor sensor system
KW - machine learning
KW - spatio-temporal gait analysis
UR - https://www.scopus.com/pages/publications/85044292791
U2 - 10.1109/ICSENS.2017.8234299
DO - 10.1109/ICSENS.2017.8234299
M3 - Conference Publication
AN - SCOPUS:85044292791
T3 - Proceedings of IEEE Sensors
SP - 1
EP - 3
BT - IEEE SENSORS 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE SENSORS Conference, ICSENS 2017
Y2 - 30 October 2017 through 1 November 2017
ER -