title: Cognitive tasks during walking affect cerebral blood flow signal features in middle cerebral arteries and their correlation to gait characteristics.
abstract: Gait is a complex process involving both cognitive and sensory ability and is strongly impacted by the environment. In this paper, we propose to study of the impact of a cognitive task during gait on the cerebral blood flow velocity, the blood flow signal features and the correlation of gait and blood flow features through a dual task methodology. Both cerebral blood flow velocity and gait characteristics of eleven participants with no history of brain or gait conditions were recorded using transcranial Doppler on mid-cerebral artery while on a treadmill. The cognitive task was induced by a backward counting starting from 10,000 with decrement of 7. Central blood flow velocity raw and envelope features were extracted in both time, frequency and time-scale domain; information-theoretic metrics were also extracted and statistical significances were inspected. A similar feature extraction was performed on the stride interval signal. Statistical differences between the cognitive and baseline trials, between the left and right mid-cerebral arteries signals and the impact of the antropometric variables where studied using linear mixed models. No statistical differences were found between the left and right mid-cerebral arteries flows or the baseline and cognitive state gait features, while statistical differences for specific features were measured between cognitive and baseline states. These statistical differences found between the baseline and cognitive states show that cognitive process has an impact on the cerebral activity during walking. The state was found to have an impact on the correlation between the gait and blood flow features.
authors.affiliation: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA. arthur.gatouillat@insa-lyon.fr.
authors.forename: Arthur
authors.initials: A
authors.lastname: Gatouillat
authors.affiliation: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA. heloisebleton@gmail.com.
authors.forename: Héloïse
authors.initials: H
authors.lastname: Bleton
authors.affiliation: Department of Physical Therapy, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA. jessievs@pitt.edu.
authors.forename: Jessie
authors.initials: J
authors.lastname: VanSwearingen
authors.affiliation: Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA. ksp9@pitt.edu.
authors.forename: Subashan
authors.initials: S
authors.lastname: Perera
authors.affiliation: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA. swt5@pitt.edu.
authors.forename: Scott
authors.initials: S
authors.lastname: Thompson
authors.affiliation: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA. traci.c.smith@gmail.com.
authors.forename: Traci
authors.initials: T
authors.lastname: Smith
authors.affiliation: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA. esejdic@ieee.org.
authors.forename: Ervin
authors.initials: E
authors.lastname: Sejdić
mesh_terms: D001921:Brain / Q000098:blood supply*; D003071:Cognition / Q000502:physiology*; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging / Q000502:physiology*; D015233:Models, Statistical; D017585:Ultrasonography, Doppler, Transcranial; D016138:Walking / Q000502:physiology*; D055815:Young Adult