Gait
Conditions
Keywords
Gait analysis, Control group, Healthy, Reference data, Kinematics, Kinetics, EMG, Dual-tasking
Brief summary
The aim of this study is to collect a large set of norm/control data on an instrumented treadmill (the Gait Real-time Analysis Interactive Lab - GRAIL) at the university hospital of Ghent for the purpose of clinical studies as well as for clinical interpretation. We hypothesize that this norm/control data will provide reference data of the normal gait patterns in the healthy population such that we can then use it to identify gait abnormalities in populations with pathology. The following data will be collected on the GRAIL while subjects walk at different gait speeds: 3D kinematics, kinetics, and EMG. Additionally, 3D kinematics, kinetics, and EMG data will be collected when performing either a cognitive (Stroop Color and Word Test) or motor (requiring arm swing) dual-task while walking at comfortable walking speed.
Interventions
OTHERWalking on an instrumented treadmill
Participants will be asked to walk at different gait velocities for 1 minute. The treadmill speed will be increased incrementally at 0.1m/s intervals until just before running.
OTHERWalking on an instrumented treadmill while dual-tasking
Participants aged between 6 and 17 years will be asked to walk at comfortable walking speed while playing either a cognitive (Stroop Color and Word Test) or motor (requiring arm swing) game.
Sponsors
University Ghent
University Hospital, Ghent
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
6 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
\- Healthy participants
Exclusion criteria
* They suffer from neurological disorder * Have balance problems * Take medications that affect gait and balance * Have undergone surgical procedures on the lower limbs in the past * Experience pain in their lower limbs or back at the time of test taking.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| EMG | single point assessment in 1 day | Muscle activity of 32 lower and upper limb muscles (micorvolts) |
| Kinetics | single point assessment in 1 day | 3D kinetics of lower limb joints while walking (Nm) |
| Kinematics | single point assessment in 1 day | 3D kinematics of lower and upper limb joints while walking (degrees) |
| Spatiotemporal parameters | single point assessment in 1 day | Spatial parameters (m) |
| EMG synergies | single point assessment in 1 day | Synergy analysis will be carried using the EMG data (variance accounted for -VAF) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Gait deviation index | single point assessment in 1 day | Based on kinematics, the lower-limb gait deviations will be calculated (degrees) |
| Game result (cognitive task) | single point assessment in 1 day | Score (% correct) |
| Game result (motor task) | single point assessment in 1 day | Score (% correct) |
Other
| Measure | Time frame | Description |
|---|---|---|
| Developmental Coordination Disorder Questionnaire (DCDQ) | single point assessment in 1 day | Brief parent questionnaire to screen for coordination disorders in children |
| M-ABC-2 | single point assessment in 1 day | Standardized tool to indentify motor functioning in children |
| segment lengths (cm) | single point assessment in 1 day | anthropometric data |
| weight | single point assessment in 1 day | anthropometric data |
| height (cm) | single point assessment in 1 day | anthropometric data |
| Demographic data | single point assessment in 1 day | Gender, age |
Countries
Belgium
Contacts
Primary ContactAnke Van Bladel, PhD
Outcome results
None listed