Ambulation Difficulty, Gait, Unsteady, Fall, Position Sense Disorders
Conditions
Brief summary
The aging population is at an exceptionally high risk of debilitating falls, contributing significantly to reduced independence and quality of life. It remains extremely challenging to screen for falls risk, and programs designed to mitigate falls risk have only modestly influenced the sizeable portion of the aging population experiencing one or more falls annually. Balance control in standing and walking depends on integrating reliable sensory feedback and on planning and executing appropriate motor responses. Walking balance control is especially dynamic, requiring active and coordinated adjustments in posture (i.e., trunk stabilization) and foot placement from step to step. Accordingly, using a custom, immersive virtual environment, the investigators have shown that sensory (i.e., optical flow) perturbations, especially when applied during walking, elicit strong and persistent motor responses to preserve balance. Exciting pilot data suggest that these motor responses are remarkably more prevalent in old age, presumably governed by an increased reliance on vision for balance control. Additional pilot data suggest that prolonged exposure to these perturbations may effectively condition successful balance control strategies. Founded on these recent discoveries, and leveraging the increase reliance on vision for balance control in old age, the investigators stand at the forefront of a potentially transformative new approach for more effectively identifying and mitigating age-related falls risk. The investigator's overarching hypothesis is that optical flow perturbations, particularly when applied during walking, can effectively identify balance deficits due to aging and falls history and can subsequently condition the neuromechanics of successful balance control via training.
Detailed description
Specific Aim 1. Investigate sensory, motor, and cognitive-motor mechanisms governing susceptibility to optical flow perturbations. Aging increases the reliance on vision for balance control. However, central and peripheral mechanisms underlying aging and falls history effects on the susceptibility to optical flow perturbations are unclear. Hypothesis 1: Entrainment to optical flow perturbations will correlate most strongly with visual dependence and decreased somatosensory function, alluding to an age-associated process of multi-sensory reweighting. Methods: Multivariate models will quantify the extent to which strategically-selected sensory (i.e., visual dependence via rod/frame test, somatosensory function), motor (i.e., rate of torque development, timed sit-to-stand) and cognitive-motor (i.e., interference) mechanisms underlie inter-individual differences in susceptibility to perturbations. Specific Aim 2. Estimate the efficacy of prolonged optical flow perturbations to condition the neuromechanics of walking balance control in older adult fallers. Pilot data from young adults suggests that prolonged exposure to optical flow perturbations may condition reactive strategies used to successfully control walking balance. The investigator's premise is that dynamic perturbation training can improve resilience to unexpected balance disturbances. Here, the investigators conduct a preliminary test of the effects of training with optical flow perturbations on walking balance in older adult fallers. Hypothesis 2: (a) Older adults with a history of falls will adapt to prolonged exposure to perturbations, conditioning their step to step adjustments in walking balance control, and (b) improving their response to unexpected balance challenges following training. Methods: In two 20 min sessions, on different days in a randomized cross-over design, older adults with a history of falls will walk with (treatment session) and without (control session) prolonged exposure to optical flow perturbations. The investigators will assess time-dependent changes in the neuromechanics of walking balance during training and after-effects via gait variability, dynamic stability, and performance on a series of real-world like targeting and obstacle avoidance tasks.
Interventions
Continuous mediolateral (i.e., side-to-side) 20-minute perturbations of optical flow that elicit the visual perception of lateral imbalance via virtual reality during treadmill walking.
Usual treadmill walking without optical flow perturbations
Sponsors
Study design
Masking description
No Masking
Intervention model description
In two 20 min sessions, on different days in a randomized cross-over design, older adults will walk with (treatment session) and without (control session) prolonged exposure to optical flow perturbations.
Eligibility
Inclusion criteria
* Be able to walk without an assistive aid (i.e., walker, cane) * Have the full capacity to provide informed consent OLDER NON-FALLERS * Age 65+ years * No history of falls\* in the prior 12 months OLDER ADULTS WITH A HISTORY OF FALLS * Age 65+ years * History of one or more falls\* in the prior 12 months * For the purposes of this study, falls counted towards the self-reported total will be defined as per the Kellogg International Work Group - a fall is unintentionally coming to the ground or some lower level and other than as a consequence of sustaining a violent blow, loss of consciousness, sudden onset of paralysis as in stroke or an epileptic seizure
Exclusion criteria
* Current lower extremity injury or fracture * Taking medication that causes dizziness * Have a leg prosthesis * Prisoners * Individuals clearly lacking the capacity to provide informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Postural Sway After 10 Min of Walking | Baseline, 10 minutes | Magnitude of side-to-side postural sway |
| Change in Kinematic Variability After 10 Min of Walking | Baseline, 10 minutes | Magnitude of step-to-step corrections in step width measured in cm |
| Change in Foot Placement Targeting Accuracy After 10 Min of Walking | Baseline, 10 minutes | Accuracy of performing foot placement targeting task. i.e., distance between heel marker at initial contact and target line (measured using three-dimensional motion capture during walking). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in Cognitive-motor Interference Accuracy After 10 Min of Walking | Baseline, 10 minutes | Accuracy performing an auditory stroop test (cognitive dual-task) |
| Change in Cognitive-motor Interference Response Time After 10 Min of Walking | Baseline, 10 minutes | Response time in performing an auditory stroop test (cognitive dual-task) |
| Change in Margin of Stability Variability After 10 Min of Walking | Baseline, 10 minutes | Change in step-to-step fluctuations in margin of stability (the distance between the lateral boundary of the foot and the body's center of mass, measured in cm) |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| All Participants Older adults will walk during exposure to optical flow perturbations
Optical flow perturbations: Continuous mediolateral (i.e., side-to-side) 20-minute perturbations of optical flow that elicit the visual perception of lateral imbalance via virtual reality.
Normal walking | 14 |
| Total | 14 |
Baseline characteristics
| Characteristic | All Participants |
|---|---|
| Age, Categorical <=18 years | 0 Participants |
| Age, Categorical >=65 years | 14 Participants |
| Age, Categorical Between 18 and 65 years | 0 Participants |
| Ethnicity (NIH/OMB) Hispanic or Latino | 0 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 14 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants |
| History of Falls | 4 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants |
| Race (NIH/OMB) Black or African American | 1 Participants |
| Race (NIH/OMB) More than one race | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants |
| Race (NIH/OMB) White | 13 Participants |
| Region of Enrollment United States | 14 Participants |
| Sex: Female, Male Female | 9 Participants |
| Sex: Female, Male Male | 5 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk |
|---|---|---|
| deaths Total, all-cause mortality | 0 / 14 | 0 / 14 |
| other Total, other adverse events | 0 / 14 | 0 / 14 |
| serious Total, serious adverse events | 0 / 14 | 0 / 14 |
Outcome results
Change in Foot Placement Targeting Accuracy After 10 Min of Walking
Accuracy of performing foot placement targeting task. i.e., distance between heel marker at initial contact and target line (measured using three-dimensional motion capture during walking).
Time frame: Baseline, 10 minutes
Population: Data could not be collected because motion capture markers tracking the location of the targeting device were too often obstructed to be able to reliably estimate foot placement targeting accuracy.
Change in Kinematic Variability After 10 Min of Walking
Magnitude of step-to-step corrections in step width measured in cm
Time frame: Baseline, 10 minutes
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Intervention | Change in Kinematic Variability After 10 Min of Walking | 0.55 cm | Standard Deviation 0.35 |
| Normal Walking (Control) | Change in Kinematic Variability After 10 Min of Walking | 0.00 cm | Standard Deviation 0.01 |
Change in Postural Sway After 10 Min of Walking
Magnitude of side-to-side postural sway
Time frame: Baseline, 10 minutes
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Intervention | Change in Postural Sway After 10 Min of Walking | -2.39 cm | Standard Deviation 1.1 |
| Normal Walking (Control) | Change in Postural Sway After 10 Min of Walking | -0.01 cm | Standard Deviation 0.59 |
Change in Cognitive-motor Interference Accuracy After 10 Min of Walking
Accuracy performing an auditory stroop test (cognitive dual-task)
Time frame: Baseline, 10 minutes
Population: Data could not be collected because noise from the treadmill motor interfered with the collection of auditory stroop test responses.
Change in Cognitive-motor Interference Response Time After 10 Min of Walking
Response time in performing an auditory stroop test (cognitive dual-task)
Time frame: Baseline, 10 minutes
Population: Data could not be collected because noise from the treadmill motor interfered with the collection of auditory stroop test responses.
Change in Margin of Stability Variability After 10 Min of Walking
Change in step-to-step fluctuations in margin of stability (the distance between the lateral boundary of the foot and the body's center of mass, measured in cm)
Time frame: Baseline, 10 minutes
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Intervention | Change in Margin of Stability Variability After 10 Min of Walking | -1.02 cm | Standard Deviation 0.99 |
| Normal Walking (Control) | Change in Margin of Stability Variability After 10 Min of Walking | 0.16 cm | Standard Deviation 0.26 |