Key Points
Question
Is chronic peripheral vestibular hypofunction associated with enduring gait deficits?
Findings
In this cross-sectional study, 13 adults with chronic vestibular loss had mean stride lengths that were 0.17 m shorter and mean peak whole-body turning velocity that was 50.4°/s slower when compared with 17 healthy adults. Instrumented gait analysis detected deficits even when observational testing suggested low fall risk.
Meaning
The results of this study suggest that adults with chronic vestibular loss have clinically and functionally meaningful gait deficits.
Abstract
Importance
Regaining the ability to walk safely is a high priority for adults with vestibular loss. Thus, practitioners need comprehensive knowledge of vestibulopathic gait to design, provide, and/or interpret outcomes of interventions. To date, few studies have characterized the effects of vestibular loss on gait.
Objectives
To investigate the use of an instrumented 2-minute walk test in adults with vestibular loss, to further characterize vestibulopathic gait, and to assess whether those with chronic vestibular loss have enduring gait deficits.
Design, Setting, and Participants
This cross-sectional study, conducted between April 3, 2018, and June 27, 2019, recruited adults 20 to 79 years of age from an academic, tertiary, hospital-based, ambulatory care setting who were healthy or had confirmed unilateral or bilateral vestibular hypofunction. Of the 43 adults who were screened from convenience and referred samples, 2 declined, and 7 were excluded because of health conditions.
Exposures
The main exposure was the instrumented 2-minute walk test, which was conducted with participants using wearable inertial measurement units while they walked a 10-m path at their self-selected speed and turned 180° in their self-selected direction at either end.
Main Outcomes and Measures
The primary measures were spatiotemporal gait metrics (eg, stride length [SL] and peak whole-body turning velocity). Multivariate analysis of variance was used to assess between-group differences. Validity was assessed using the area under the curve from receiver operator characteristic analyses.
Results
Data from 17 healthy adults (mean [SD] age, 39.27 [11.20] years; 13 [76%] female) and 13 adults with vestibular loss (mean [SD] age, 60.50 [10.81] years; 6 [46%] female) were analyzed. Very large between-group differences were found for SL (left) (estimated marginal mean [SE] for healthy vs vestibular groups, 1.47 [0.04] m vs 1.31 [0.04] m; Cohen d, 1.35; 95% CI, 0.18-2.52), SL (right) (estimated marginal mean [SE] for healthy vs vestibular groups, 1.46 [0.04] m vs 1.29 [0.04] m; Cohen d, 1.44; 95% CI, 0.25-2.62), and peak turn velocity (estimated marginal mean [SE] for healthy vs vestibular groups, 240.17 [12.78]°/s vs 189.74 [14.70]°/s; Cohen d, 1.23; 95% CI, 0.07-2.40). The area under the curve was 0.79 (95% CI, 0.62-0.95) for SL (left), 0.81 (95% CI, 0.64-0.97) for SL (right), and 0.86 (95% CI, 0.72-0.99) for peak turn velocity.
Conclusions and Relevance
In this cross-sectional study, instrumented gait analysis had good discriminative validity and revealed persistent deficits in gait stability in those with chronic vestibular loss. The findings of this study suggest that these clinically and functionally meaningful deficits could be targets for vestibular rehabilitation.
This cross-sectional study investigates the use of an instrumented 2-minute walk test in adults with vestibular loss to assess whether those with chronic vestibular loss have enduring gait deficits.
Introduction
Vestibular disorders affect 5% to 10% of the general population1,2 and cause functional impairments in vision,3 balance,4 and gait.5 Although the effects of peripheral vestibular loss on balance6 and gaze stability7,8 are well documented, less attention has been devoted to its effect on gait.9,10,11 Greater understanding of vestibulopathic gait is needed because regaining the ability to walk safely is a high priority for patients.12
The functional effect of vestibular loss on walking is typically evaluated using observational assessments.12,13,14,15,16,17 Instrumented gait analysis in persons with vestibular loss is possible using pressure switches,5,18 3-dimensional motion capture systems,19,20,21 pressure mats,22,23 gyroscopes,24 and inertial measurement units (IMUs).25,26,27,28 Although many instrumented methods are not available in most clinical settings, wearable technologies29 are becoming more accessible.
The extent of vestibular loss, temporal aspects of recovery, and the role of central compensation12,30 are important considerations for interpreting vestibulopathic gait deficits. Abnormalities in the timing of spatiotemporal gait parameters18,24 and reduced gait velocity (GV)31 have been observed in the short term. Patients with subacute unilateral vestibular loss (UVL) who have undergone vestibular schwannoma resection have reduced peak head rotation amplitude and velocity as well as impaired head-trunk coordination while walking at their self-selected speed.27,28 Although some studies18,31 of adults with subacute UVL suggest that spatiotemporal gait parameters normalize during self-paced, linear gait in the light, deficits in fast walking and walking in the dark persist for at least 3 months after vestibular neurectomy.31 Furthermore, adults with chronic (>3 months) UVL and bilateral vestibular loss (BVL) have a clinically meaningful reduction in self-paced, linear walking speed of 0.22 to 0.25 m/s21,22 as well as imbalance during head turns and difficulty negotiating obstacles.22
Many patients32,33 are not referred for vestibular rehabilitation (VR) until the long-term recovery phase; thus, further characterization of vestibulopathic gait in patients more than 3 months after onset is needed. In addition, because the vestibular system influences gait by sensing linear and angular movement,9 specific attention to turning metrics is warranted.
The objectives of this study were to investigate the use of an instrumented 2-minute walk test (i2MWT) in adults with chronic vestibular loss, characterize spatiotemporal aspects of vestibulopathic gait, and compare the ability to detect persistent gait abnormalities using observational and IMU-based gait analysis. We hypothesized that GV and turning dynamics would discriminate adults with vestibular loss from healthy adults, that those with BVL would perform worse compared with those with UVL, and that IMU-based gait analysis would detect gait deficits even when observational testing does not.
Methods
This cross-sectional study was completed in an academic, tertiary, ambulatory care setting. Data were collected between April 3, 2018, and June 27, 2019, by 1 of the investigators (C.R.G.); all data were deidentified for the other authors. All participants provided written informed consent. All procedures were conducted in accordance with the provisions of the Declaration of Helsinki.34 The study was approved by the University of Wisconsin–Madison Health Sciences Institutional Review Board. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
We recruited adults who were 20 to 79 years of age; could speak English fluently; were able to function independently; had no neurologic, musculoskeletal, visual, or pain conditions that would preclude accurate testing; were able to stand for 20 minutes without sitting and walk 6.1 m without assistance; could withhold antivertigo, sedative, and narcotic or barbiturate medications and abstain from drinking alcohol for 48 hours before the study visit; and would not be pregnant while participating. All participants were required to have at least 75% of active range of motion in the lower extremities, normal bilateral lower-extremity strength,35 and normal bilateral lower-extremity sensation.36 Healthy participants without vestibular loss were recruited from the community. Adults with vestibular loss were recruited from outpatient clinics and were enrolled if they had a confirmed diagnosis of UVL or BVL (eAppendix 1 in the Supplement). All patients underwent a clinical examination, the noninstrumented dynamic visual acuity test (DVAT),3 the Sensory Organization Test (SOT),37 and the measures that follow (eAppendix 2 in the Supplement). Each participant received a stipend.
Self-report Measures
Participants completed the Activities-Specific Balance Confidence Scale (ABCS),38 Dizziness Handicap Inventory (DHI),39 Visual Vertigo Analog Scale (VVAS),40 and Vestibular Activities and Participation Measure (VAPM)41 within 48 hours of the start of the study visit. Only the mean or total scores are reported for the ABCS, DHI, VVAS, and VAPM. Healthy participants did not complete the disease-specific VAPM.
Gait Analyses
The Functional Gait Assessment (FGA)42 consists of 10 walking tasks, each scored on an ordinal scale of 0 to 3 points, with higher scores indicating better performance or better balance. The FGA was always completed before the i2MWT. The optimal total score is 30. The total score and gait speed, which was manually recorded during the first item of the FGA (walking, eyes open), are reported.
One trial of the i2MWT29 was conducted while participants wore 3 IMUs (IMU, version 1.0; IMU software, version 2.0; APDM Inc). One sensor was placed on the torso at the level of the fourth and fifth lumbar intervertebral disks using the manufacturer-provided strap. The remaining sensors were secured on the dorsum of each foot. Participants wore their preferred, flat-soled shoes and walked within a 10 × 0.4-m path at their preferred speed and turned 180° in their preferred direction at either end. The metrics of interest were GV in meters per second, cadence in steps per minute, double support as a percentage of the gait cycle, stride length (SL) in meters, turning angle in degrees, peak turn velocity (PTV) and mean turn velocity (MTV) in degrees per second, turn duration (TD) in milliseconds, and the number of steps to turn (eAppendix 2 in the Supplement). Gait cycles and the number of turns were also recorded.
Statistical Analysis
All analyses were conducted post hoc using R software, version 3.5 (R Foundation for Statistical Computing).43 The α level was 0.05. Between-group comparisons for age, sex, body mass index (calculated as weight in kilograms divided by height in meters squared), height in meters, and fall history were analyzed with 2-tailed t tests or χ2 tests. Demographic differences between subgroups were evaluated using analysis of variance with the Tukey honestly significant difference or a χ2 test. Equipment malfunction during the i2MWT led us to exclude data from 4 adults with vestibular loss.
Between-group and between-subgroup differences for the i2MWT, as well as secondary self-report and capacity-based measures, were examined with 1-way, multivariate analysis of variance controlling for age and sex. Effect sizes for specific i2MWT metrics were calculated using the Cohen d (with 0-0.2 indicating small, 0.3-0.5 indicating medium, 0.6-0.8 indicating large, and ≥0.9 indicating very large).44 In addition, z scores (SDs from the mean of healthy adults in this study) for the i2MWT metrics were calculated.45 The minimal detectable change for each i2MWT metric was calculated using 1.96 × √2 × SEM.46
The discriminative ability of SL, PTV, and the FGA total score was assessed with the area under the curve from receiver operator characteristic (ROC) curve analyses. The sensitivity and specificity (95% CI) for these metrics were calculated from contingency tables created based on their optimal ROC thresholds. The sensitivity and specificity of the FGA to detect a history of falls using a cutoff score of 22 of 30 was also assessed.47 The Pearson method was used to assess associations between PTV and self-report and other capacity-based measures.
Results
Population Characteristics
Data from 17 healthy adults (mean [SD] age, 39.27 [11.20] years; 13 [76%] female) and 13 adults with vestibular loss (mean [SD] age, 60.50 [10.81] years; 6 [46%] female) (whose onset ranged from 3 months to 12 years before enrollment) were analyzed (Table 1). Very large between-group differences were found for age (see above) and fall history (1 [6%] for healthy adults vs 5 [39%] for adults with vestibular loss). Mean (SD) height (1.72 [0.09] m for healthy adults vs 1.75 [0.08] m for adults with vestibular loss) and body mass index (25.96 [4.36] for healthy adults vs 26.16 [4.90] for adults with vestibular loss) were similar for both groups. Between-group and between-subgroup analyses for self-report and capacity-based measures, including the i2MWT, were performed while controlling for age and sex. The width of the CIs for each reported effect size suggests uncertainty about the precision of the estimates from this preliminary study.
Table 1. Study Population Characteristics.
Characteristic | Healthy participants (n = 17) | Participants with vestibular loss (n = 13) | ES (95% CI)a | UVL (n = 8) | BVL (n = 5) | ES (95% CI)b |
---|---|---|---|---|---|---|
Age, mean (SD), y | 39.27 (11.20) | 60.50 (10.81) | −1.93 (−2.81 to −1.06) | 61.66 (12.09) | 58.65 (9.39) | 0.08 (−1.03 to 1.20) |
Female sex, No. (%) | 13 (76) | 6 (46) | 0.76 (0.63 to 0.89) | 3 (38) | 3 (60) | NR |
BMI, mean (SD) | 25.96 (4.36) | 26.16 (4.90) | −0.04 (−0.76 to 0.68) | 25.35 (3.91) | 27.45 (6.48) | 0.22 (−0.90 to 1.34) |
Height, mean (SD), m | 1.72 (0.09) | 1.75 (0.08) | −0.37 (−1.09 to 0.36) | 1.74 (0.09) | 1.77 (0.06) | 0.10 (−1.02 to 1.22) |
History of falls, No. (%) | 1 (6) | 5 (39) | 1.07 (0.92 to 1.21) | 4 (50) | 1 (20) | NR |
Abbreviations: BVL, bilateral vestibular loss; BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); ES, effect size (Cohen d); NR, not reported because of small sample size for the χ2 statistic; UVL, unilateral vestibular loss.
These ESs are based on the t statistic from 2-tailed t tests.
These ESs are based on P values (adjusted using the Tukey method for honestly significant difference) from pairwise comparisons for adults with UVL vs those with BVL within 1-way analysis of variance.
Differences on Self-report and Capacity-Based Measures
Very large between-group differences in estimated marginal means (SEs) were found for the ABCS (16.52 [6.07]), DHI (−30.03 [6.78]), VVAS (−21.99 [7.99]), DVAT (horizontal: −3.05 [1.07]; vertical: −3.91 [1.03]), SOT (17.1 [6.72]), and FGA (4.72 [1.82]) (Table 2). Healthy adults had better results on all self-report and capacity-based measures vs adults with vestibular loss (ABCS: 98.99 [3.52] vs 82.47 [3.90]; DHI: 0.04 [3.93] vs 30.07 [4.36]; VVAS: −1.73 [4.64] vs 20.26 [5.14]; DVAT [horizontal]: 1.28 [0.62] vs 4.33 [0.69]; DVAT [vertical]: 0.8 [0.6] vs 4.71 [0.66]; SOT: 82.82 [3.9] vs 65.73 [4.32]; FGA: 28.86 [1.05] vs 24.14 [1.17]; gait speed: 1.43 [0.07] vs 1.26 [0.08]; gait cycles: 50.55 [1.88] vs 45.69 [2.21]; and number of turns: 15.66 [0.6] vs 13.68 [0.71]).
Table 2. Analysis of Between-Group Differences for Self-report and Capacity-Based Measures.
Variable | Estimated marginal mean (SE) | Estimated marginal mean (SE) difference [95% CI] | ES (95% CI) | |
---|---|---|---|---|
Healthy participants | Participants with vestibular loss | |||
ABCS (mean) | 98.99 (3.52) | 82.47 (3.90) | 16.52 (6.07) [4.05 to 29.00] | 1.47 (0.28 to 2.65) |
DHI (total) | 0.04 (3.93) | 30.07 (4.36) | −30.03 (6.78) [−43.98 to −16.09] | −2.39 (−3.69 to −1.09) |
VVAS (mean) | −1.73 (4.64) | 20.26 (5.14) | −21.99 (7.99) [−38.42 to −5.56] | −1.48 (−2.65 to −0.32) |
DVAT (horizontal) | 1.28 (0.62) | 4.33 (0.69) | −3.05 (1.07) [−5.25 to −0.84] | −1.53 (−2.72 to −0.34) |
DVAT (vertical) | 0.80 (0.60) | 4.71 (0.66) | −3.91 (1.03) [−6.02 to −1.80] | −2.06 (−3.31 to −0.80) |
SOT (composite) | 82.82 (3.90) | 65.73 (4.32) | 17.1 (6.72) [3.28 to 30.92] | 1.37 (0.20 to 2.55) |
FGA (total) | 28.86 (1.05) | 24.14 (1.17) | 4.72 (1.82) [0.98 to 8.45] | 1.40 (0.22 to 2.58) |
GS (FGA item 1), m/s | 1.43 (0.07) | 1.26 (0.08) | 0.18 (0.13) [−0.08 to 0.44] | 0.76 (−0.37 to 1.89) |
NC (i2MWT) | 50.55 (1.88) | 45.69 (2.21) | 4.86 (2.85) [−1.01 to 10.72] | 0.63 (−0.15 to 1.42) |
NT (i2MWT) | 15.66 (0.60) | 13.68 (0.71) | 1.98 (0.91) [0.11 to 3.85] | 0.81 (0.01 to 1.60) |
Abbreviations: ABCS, Activities-Specific Balance Confidence Scale; DHI, Dizziness Handicap Inventory; DVAT, noninstrumented dynamic visual acuity test (lines lost compared with static visual acuity); ES, effect size (Cohen d); FGA, Functional Gait Assessment; GS, gait speed; i2MWT, instrumented 2-minute walk test; NC, number of gait cycles (i2MWT); NT, number of turns (i2MWT); SOT, Sensory Organization Test; VAPM, Vestibular Activities and Participation Measure; VVAS, Visual Vertigo Analog Scale.
Very large differences in estimated marginal means (SEs) were found between healthy adults and those with UVL for the DHI (−26.09 [7.62]), VVAS (−18.77 [9.1]), and vertical DVAT (−2.28 [0.95]) (Table 3). Differences in estimated marginal means (SEs) between healthy adults and those with BVL for the ABCS (24.92 [6.16]), DHI (−34.21 [7.71]), VVAS (−25.38 [9.21]), DVAT (horizontal: −5.00 [0.96]; vertical: −5.64 [0.96]), SOT (28.72 [6.19]), and FGA (8.39 [1.47]) were very large (Table 3). The differences for the ABCS (16.34 [6.16]), DVAT (horizontal: −3.81 [0.96]; vertical: −3.36 [0.96]), SOT (22.63 [6.19]), and FGA (7.16 [1.47]) between adults with UVL and those with BVL were very large (Table 3). Small to large differences were found for gait speed (effect size, 0.76; 95% CI, −0.37 to 1.89), gait cycles (effect size, 0.63; 95% CI, −0.15 to 1.42), and number of turns (effect size, 0.81; 95% CI, 0.01-1.60) (Table 2 and Table 3).
Table 3. Analysis of Between-Subgroup Differences for Self-report and Capacity-Based Measures.
Variable | Estimated marginal mean (SE) | Estimated marginal mean (SE) difference [95% CI] | ES (95% CI) | |
---|---|---|---|---|
Healthy participants | Participants with vestibular loss | |||
Healthy vs UVL | ||||
ABCS (mean) | 98.02 (3.15) | 89.44 (4.26) | 8.58 (6.09) [−6.59 to 23.74] | 0.86 (−0.42 to 2.14) |
DHI (total) | 0.52 (3.94) | 26.61 (5.34) | −26.09 (7.62) [−45.07 to −7.1) | −2.08 (−3.48 to −0.69) |
VVAS (mean) | −1.34 (4.70) | 17.44 (6.37) | −18.77 (9.1) [−41.43 to 3.88] | −1.26 (−2.55 to 0.04) |
DVAT (horizontal) | 1.51 (0.49) | 2.7 (0.66) | −1.19 (0.94) [−3.55 to 1.16] | −0.77 (−2.04 to 0.50) |
DVAT (vertical) | 1.00 (0.49) | 3.28 (0.66) | −2.28 (0.95) [−4.64 to 0.08] | −1.46 (−2.79 to −0.14) |
SOT (composite) | 81.48 (3.16) | 75.38 (4.28) | 6.09 (6.11) [−9.13 to 21.31] | 0.61 (−0.66 to 1.87) |
FGA (total) | 28.43 (0.75) | 27.2 (1.02) | 1.23 (1.45) [−2.39 to 4.86] | 0.52 (−0.75 to 1.78) |
GS (FGA item 1), m/s | 1.43 (0.07) | 1.29 (0.10) | 0.14 (0.14) [−0.22 to 0.50] | 0.6 (−0.66 to 1.87) |
NC (i2MWT) | 48.32 (2.48) | 51.31 (3.36) | −2.99 (4.8) [−14.96 to 8.97] | −0.38 (−1.64 to 0.88) |
NT (i2MWT) | 15.21 (0.85) | 14.13 (1.15) | 1.08 (1.64) [−3.01 to 5.16] | 0.40 (−0.86 to 1.66) |
Healthy vs BVL | ||||
ABCS (mean) | 98.02 (3.15) | 73.1 (4.81) | 24.92 (6.16) [9.56 to 40.27] | 2.49 (1.03 to 3.95) |
DHI (total) | 0.52 (3.94) | 34.73 (6.02) | −34.21 (7.71) [−53.42 to −14.99] | −2.73 (−4.23 to −1.23) |
VVAS (mean) | −1.34 (4.7) | 24.05 (7.18) | −25.38 (9.21) [−48.32 to −2.45] | −1.7 (−3.04 to −0.35) |
DVAT (horizontal) | 1.51 (0.49) | 6.51 (0.75) | −5.00 (0.96) [−7.38 to −2.62] | −3.22 (−4.8 to −1.65) |
DVAT (vertical) | 1.00 (0.49) | 6.64 (0.75) | −5.64 (0.96) [−8.03 to −3.25] | −3.62 (−5.27 to −1.97) |
SOT (composite) | 81.48 (3.16) | 52.75 (4.82) | 28.72 (6.19) [13.32 to 44.13] | 2.86 (1.34 to 4.38) |
FGA (total) | 28.43 (0.75) | 20.04 (1.15) | 8.39 (1.47) [4.72 to 12.06] | 3.51 (1.88 to 5.14) |
GS (FGA item 1), m/s | 1.43 (0.07) | 1.22 (0.11) | 0.21 (0.15) [−0.15 to 0.58] | 0.89 (−0.40 to 2.19) |
NC (i2MWT) | 48.32 (2.48) | 44.19 (3.79) | 4.13 (4.86) [−7.98 to 16.24] | 0.52 (−0.76 to 1.80) |
NT (i2MWT) | 15.21 (0.85) | 14.86 (1.29) | 0.35 (1.66) [−3.79 to 4.48] | 0.13 (−1.14 to 1.40) |
UVL vs BVL | ||||
ABCS (mean) | 89.44 (4.26) | 73.1 (4.81) | 16.34 (6.16) [1.88 to 30.79] | 1.63 (0.35 to 2.92) |
DHI (total) | 26.61 (5.34) | 34.73 (6.02) | −8.12 (7.71) [−26.22 to 9.98] | −0.65 (−1.86 to 0.56) |
VVAS (mean) | 17.44 (6.37) | 24.05 (7.18) | −6.61 (9.21) [−28.21 to 14.99] | −0.44 (−1.64 to 0.76) |
DVAT (horizontal) | 2.70 (0.66) | 6.51 (0.75) | −3.81 (0.96) [−6.05 to −1.56] | −2.45 (−3.85 to −1.06) |
DVAT (vertical) | 3.28 (0.66) | 6.64 (0.75) | −3.36 (0.96) [−5.61 to −1.11] | −2.16 (−3.51 to −0.81) |
SOT (composite) | 75.38 (4.28) | 52.75 (4.82) | 22.63 (6.19) [8.12 to 37.14] | 2.26 (0.89 to 3.62) |
FGA (total) | 27.20 (1.02) | 20.04 (1.15) | 7.16 (1.47) [3.70 to 10.61[ | 3.00 (1.52 to 4.48) |
GS (FGA item 1), m/s | 1.29 (0.10) | 1.22 (0.11) | 0.07 (0.15) [−0.27 to 0.41] | 0.29 (−0.91 to 1.49) |
NC (i2MWT) | 51.31 (3.36) | 44.19 (3.79) | 7.12 (4.86) [−4.28 to 18.52] | 0.90 (−0.32 to 2.13) |
NT (i2MWT) | 14.13 (1.15) | 14.86 (1.29) | −0.73 (1.66) [−4.62 to 3.17] | −0.27 (−1.47 to 0.93) |
Abbreviations: ABCS, Activities-Specific Balance Confidence Scale; BVL, bilateral vestibular loss; DHI, Dizziness Handicap Inventory; DVAT, noninstrumented dynamic visual acuity test (lines lost compared with static visual acuity); ES, effect size (Cohen d); FGA, Functional Gait Assessment; GS, gait speed; i2MWT, instrumented 2-minute walk test; NC, number of gait cycles (i2MWT); NT, number of turns (i2MWT); SOT, Sensory Organization Test; UVL, unilateral vestibular loss; VAPM, Vestibular Activities and Participation Measure; VVAS, Visual Vertigo Analog Scale.
Between-Group Differences on the i2MWT
Analyzing values for GV, cadence, and SL that were normalized to height48 did not alter the conclusions to be drawn; thus, only the analysis of the raw values for these metrics are reported (Table 4). Adults with vestibular loss had estimated marginal means (SEs) indicating slower GV (1.25 [0.07] m/s), shorter SL bilaterally (left: 1.31 [0.04] meters; right: 1.29 [0.04] meters), slower PTV (189.74 [14.17]°/s), and longer TD (1180 [89] milliseconds) compared with healthy adults; however, post hoc analysis revealed that the very large between-group difference in age influenced these results. Even after age and sex were controlled for, the effect sizes for the between-group differences for GV (0.98; 95% CI, −0.16 to 2.12), SL (left: 1.35; 95% CI, 0.18-2.52; right: 1.44; 95% CI, 0.25-2.62), TD (−0.97; 95% CI, −2.12 to 0.17]), and PTV (1.23; 95% CI, 0.07-2.40) were very large. The z scores indicate that the performance of the group with vestibular loss differed from the healthy group by more than 1 SD (eg, −1.05 for SL [left], −1.13 for SL [right], and −1.23 for PTV). Between-group differences for each i2MWT metric (eg, mean [SD], −0.64 [1.24] m for SL [left], 0.16 [0.07] m for SL [right], and 50.43 [22.03]°/s for PTV) exceeded the respective minimal detectable change values calculated from this population (eg, 0.01 m for SL [left], 0.01 m for SL [right], and 4.72°/s for PTV).
Table 4. Analysis of Between-Group Differences for i2MWT Metrics.
Variable | Estimated marginal mean (SE) | Estimated marginal mean (SE) difference [95% CI] | ES (95% CI) | MDC | |
---|---|---|---|---|---|
Healthy participants | Participants with vestibular loss | ||||
GV, m/s | 1.45 (0.06) | 1.25 (0.07) | 0.20 (0.11) [−0.03 to 0.42] | 0.98 (−0.16 to 2.12) | 0.02 |
Cadence, SPM | 117.23 (3.35) | 112.82 (3.72) | 4.41 (5.78) [−7.48 to 16.29] | 0.41 (−0.70 to 1.53) | 1.11 |
DS | 19.18 (0.72) | 19.82 (0.80) | −0.64 (1.24) [−3.20 to 1.91] | −0.28 (−1.39 to 0.83) | 0.25 |
SL (left), m | 1.47 (0.04) | 1.31 (0.04) | 0.16 (0.07) [0.03 to 0.30] | 1.35 (0.18 to 2.52) | 0.01 |
SL (right), m | 1.46 (0.04) | 1.29 (0.04) | 0.17 (0.06) [0.04 to 0.30] | 1.44 (0.25 to 2.62) | 0.01 |
TA, ° | 180.7 (1.87) | 180.75 (2.07) | −0.05 (3.22) [−6.67 to 6.57] | −0.01 (−1.12 to 1.10) | 0.58 |
TD, ms | 929 (81) | 1180 (89) | −250 (139) [−536 to 35] | −0.97 (−2.12 to 0.17) | 0.26 |
PTV, °/s | 240.17 (12.78) | 189.74 (14.17) | 50.43 (22.03) [5.13 to 95.72] | 1.23 (0.07 to 2.40) | 4.72 |
MTV, °/s | 198 (11.44) | 165.58 (12.69) | 32.41 (19.72) [−8.13 to 72.95] | 0.89 (−0.25 to 2.02) | 3.93 |
TNS | 3.27 (0.15) | 3.47 (0.16) | −0.2 (0.25) [−0.73 to 0.32] | −0.43 (−1.55 to 0.68) | 0.04 |
Abbreviations: DS, double support; ES, effect size (Cohen d); GV, gait velocity; i2MWT, instrumented 2-minute walk test; MDC, minimal detectable change; MTV, mean turn velocity; PTV, peak turn velocity; SL, stride length; SPM, steps per minute; TA, turn angle; TD, turn duration; TNS, number of steps to turn.
Between-Subgroup Differences on the i2MWT
Very large estimated marginal mean (SE) differences were found between healthy adults and those with UVL for GV (0.21 [0.12] m/s), SL (0.18 [0.08] m [left] and 0.17 [0.07] [right]), and PTV 46.58 (25.31)°/s). The estimated marginal mean (SE) differences between healthy adults and those with BVL were very large for SL (0.15 (0.08) [left] and 0.17 [0.07] [right], TD (−445 [141] milliseconds), PTV (54.49 [25.62]°/s), and MTV (55.95 [20.82]°/s). Very large estimated marginal mean (SE) differences were found between adults with UVL and those with BVL for turning angle (7.88 [3.16]°), TD (−378 [132] milliseconds), and MTV (45.82 [19.61]°/s) (Table 5).
Table 5. Analysis of Between-Subgroup Differences for i2MWT Metrics.
Variable | Estimated marginal mean (SE) | Estimated marginal mean (SE) difference [95% CI] | ES (95% CI) | |
---|---|---|---|---|
Healthy | Unilateral | |||
Healthy vs UVL | ||||
GV, m/s | 1.45 (0.06) | 1.24 (0.09) | 0.21 (0.12) [−0.10 to 0.52] | 1.04 (−0.25 to 2.33) |
Cadence, SPM | 117.30 (3.44) | 112.31 (4.66) | 4.98 (6.65) [−11.58 to 21.55] | 0.46 (−0.80 to 1.72) |
DS | 19.19 (0.74) | 19.76 (1.00) | −0.57 (1.43) [−4.13 to 2.99] | −0.24 (−1.50 to 1.01) |
SL (left), m | 1.47 (0.04) | 1.3 (0.05) | 0.18 (0.08) [−0.01 to 0.36] | 1.41 (0.09 to 2.73) |
SL (right), m | 1.46 (0.04) | 1.29 (0.05) | 0.17 (0.07) [−0.01 to 0.35] | 1.41 (0.09 to 2.73) |
TA, ° | 180.23 (1.71) | 184.11 (2.32) | −3.88 (3.32) [−12.14 to 4.38] | −0.71 (−1.98 to 0.56) |
TD, ms | 952 (72) | 1018 (97) | −67 (139) [−413 to 280] | −0.29 (−1.55 to 0.97) |
PTV, °/s | 239.70 (13.08) | 193.11 (17.72) | 46.58 (25.31) [−16.46 to 109.62] | 1.12 (−0.18 to 2.42) |
MTV, °/s | 195.27 (10.63) | 185.14 (14.40) | 10.13 (20.57) [−41.10 to 61.36] | 0.30 (−0.96 to 1.56) |
TNS | 3.27 (0.15) | 3.46 (0.21) | −0.19 (0.29) [−0.92 to 0.54] | −0.39 (−1.65 to 0.87) |
Healthy vs BVL | ||||
GV, m/s | 1.45 (0.06) | 1.27 (0.10) | 0.18 (0.13) [−0.13 to 0.49] | 0.88 (−0.42 to 2.17) |
Cadence, SPM | 117.30 (3.44) | 113.50 (5.25) | 3.80 (6.73) [−12.97 to 20.57] | 0.35 (−0.93 to 1.62) |
DS | 19.19 (0.74) | 19.91 (1.13) | −0.72 (1.45) [−4.33 to 2.88] | −0.31 (−1.58 to 0.96) |
SL (left), m | 1.47 (0.04) | 1.32 (0.06) | 0.15 (0.08) [−0.04 to 0.34] | 1.23 (−0.08 to 2.55) |
SL (right), m | 1.46 (0.04) | 1.29 (0.06) | 0.17 (0.07) [−0.02 to 0.35] | 1.40 (0.07 to 2.74) |
TA, ° | 180.23 (1.71) | 176.23 (2.62) | 4.00 (3.36) [−4.37 to 12.36] | 0.73 (−0.55 to 2.02) |
TD, ms | 952 (72) | 1396 (110) | −445 (141) [−795 to −94] | −1.95 (−3.34 to −0.56) |
PTV, °/s | 239.70 (13.08) | 185.21 (19.98) | 54.49 (25.62) [−9.32 to 118.30] | 1.31 (−0.01 to 2.64) |
MTV, °/s | 195.27 (10.63) | 139.32 (16.24) | 55.95 (20.82) [4.09 to 107.80] | 1.66 (0.30 to 3.01) |
TNS | 3.27 (0.15) | 3.49 (0.23) | −0.22 (0.30) [−0.96 to 0.52] | −0.46 (−1.73 to 0.82) |
UVL vs BVL | ||||
GV, m/s | 1.24 (0.09) | 1.27 (0.10) | −0.03 (0.12) [−0.33 to 0.26] | −0.16 (−1.36 to 1.03) |
Cadence, SPM | 112.31 (4.66) | 113.50 (5.25) | −1.18 (6.34) [−16.97 to 14.61] | −0.11 (−1.30 to 1.09) |
DS | 19.76 (1.00) | 19.91 (1.13) | −0.15 (1.36) [−3.55 to 3.24] | −0.06 (−1.26 to 1.13) |
SL (left), m | 1.30 (0.05) | 1.32 (0.06) | −0.02 (0.07) [−0.20 to 0.16] | −0.18 (−1.38 to 1.02) |
SL (right), m | 1.29 (0.05) | 1.29 (0.06) | 0 (0.07) [−0.17 to 0.17] | −0.01 (−1.2 to 1.19) |
TA, ° | 184.11 (2.32) | 176.23 (2.62) | 7.88 (3.16) [0 to 15.76] | 1.45 (0.18 to 2.71) |
TD, ms | 1018 (97) | 1396 (110) | −378 (132) [−708 to −48] | −1.66 (−2.95 to −0.37) |
PTV, °/s | 193.11 (17.72) | 185.21 (19.98) | 7.91 (24.13) [−52.18 to 68.00] | 0.19 (−1.01 to 1.39) |
MTV, °/s | 185.14 (14.40) | 139.32 (16.24) | 45.82 (19.61) [−3.02 to 94.65] | 1.36 (0.10 to 2.62) |
TNS | 3.46 (0.21) | 3.49 (0.23) | −0.03 (0.28) [−0.72 to 0.67] | −0.06 (−1.26 to 1.13) |
Abbreviations: BVL, bilateral vestibular loss; DS, double support; ES, effect size (Cohen d); GV, gait velocity; i2MWT, instrumented 2-minute walk test; MTV, mean turn velocity; PTV, peak turn velocity; SL, stride length; SPM, steps per minute; TA, turn angle; TD, turn duration; TNS, number of steps to turn; UVL, unilateral vestibular loss.
Validity of Specific i2MWT Metrics
The results of the post hoc analysis of age and sex influenced the selection of i2MWT metrics to be analyzed for discriminative ability. The area under the curve was 0.79 (95% CI, 0.62-0.95; 1.46 m) for SL (left), 0.81 (95% CI, 0.64-0.97; 1.42 m) for SL (right), 0.86 (95% CI, 0.72-0.99; 229.5°/s) for PTV, and 0.89 (95% CI, 0.77-1.00; 27 of 30 points) for the FGA. The sensitivity for these metrics to detect vestibular dysfunction was 100% (95% CI, 75%-100%) for SL (left), 100% (95% CI, 75%-100%) for SL (right), 100% (95% CI, 75%-100%) for PTV, and 69% (95% CI, 39%-91%), and 100% (80%, 100%) for the FGA, and the specificity was 53% (95% CI, 29%-77%) for SL (left), 59% (95% CI, 33%-88%) for SL (right), 71% (95% CI, 44%-90%) for PTV, and 100% (95% CI, 80%-100%) for the FGA. When evaluating the ability to detect a history of falls using an FGA total score of 22 of 30,48 the sensitivity was 38% (95% CI, 14%-68%) and the specificity was 100% (95% CI, 80%-100%).
Assessment of the concurrent validity of SL and PTV revealed large to very large effect sizes for correlations with self-report measures: ABCS mean score (SL [left]: 0.87; 95% CI, 0.08-1.67; SL [right]: 1.01; 95% CI, 0.19-1.82; PTV: 1.39; 95% CI, 0.5-2.27), DHI total score (SL [left]: −1.06; 95% CI, −1.89 to −0.24; SL [right]: −1.22; 95% CI, −2.07 to −0.37; PTV: 1.39; 95% CI, 0.5-2.27), VVAS mean score (SL [left]: −0.87; 95% CI, −1.67 to −0.08; SL [right]: −0.77; 95% CI, −1.55 to 0.01; PTV: −0.82; 95% CI, −1.61 to −0.03). Similarly, large to very large effect sizes were found for correlations of SL and PTV with capacity-based measures: DVAT horizontal and vertical (SL [left]: −0.85; 95% CI, −1.64 to −0.06; SL [right]: −0.95; 95% CI, −1.76 to −0.15), DVAT horizontal (PTV: −1.62; 95% CI, −2.56 to −0.69), DVAT vertical (PTV: −1.54; 95% CI, −2.46 to −0.62), SOT composite score (SL [left]: 1.19; 95% CI, 0.34-2.03; SL [right]: 1.39; 95% CI, 0.50-2.27; PTV: 1.62; 95% CI, 0.69-2.56), and the FGA total score (SL [left]: 1.39; 95% CI, 0.50-2.27; SL [right]: 1.58; 95% CI, 0.65-2.51; PTV: 1.85; 95% CI, 0.86-2.85) (eTable 1 in the Supplement).
Description of the Data at the Individual Level
Healthy Adults
One healthy adult reported visually induced dizziness on the VVAS. Performance was above the optimal thresholds from the ROC analyses for SL (left and right) for 47% of healthy participants and PTV for 70% of healthy participants (eTable 2 in the Supplement).
Adults With Vestibular Loss
For self-report measures, 30% of individuals with vestibular loss scored higher than the normal cutoff score (80%) on the ABCS,38 54% scored mild disability or worse (30 of 100) on the DHI,49 54% had visually induced dizziness (abnormal VVAS score),50 24% scored mild activity limitations and participation restrictions (≤1.0) on the VAPM,41 and 38% scored higher than the falls risk cutoff score (22 of 30) on the FGA.47 On the i2MWT, none of the adults with vestibular loss had values above the ROC thresholds for SL (left), SL (right), and PTV. Thus, all those with FGA total scores greater than 22 of 30 had abnormal SL (bilaterally) and PTV. In addition, 46% had PTV of less than 180°/s9 (eTable 3 in the Supplement).
Discussion
In this cross-sectional study, many adults with chronic vestibular loss had persistent deficits, particularly for SL and PTV while walking at their self-selected speed. Both SL and PTV discriminated healthy adults from adults with vestibular loss; however, turn angle, TD, and MTV differentiated adults with UVL from those with BVL. In addition, instrumented gait analysis detected persistent deficits in walking, even when observational gait testing suggested the person may be at low risk of falling.
This study’s findings of persistent gait impairments during prolonged walking extend those of prior studies19,20,21,31 in which forward gait was assessed in adults with vestibular loss who walked a straight path 10 m or shorter. In addition, the data regarding whole-body turning dynamics add to the small body of work in adults with vestibular loss that has documented gait deficits during yaw-plane head movements,25 head-trunk incoordination while performing selected tasks from the FGA,27 and reduced active head movements during community ambulation.28 Furthermore, this study’s findings are consistent with those of prior studies22,23 that documented deficits in spatiotemporal aspects of gait when adults with imbalance attributable to vestibular loss or other causes performed complex gait tasks while walking on a pressure mat.
The mean GV of adults with chronic vestibular loss in this study is consistent with that reported in prior studies.22,51 The difference in GV between the groups in this study exceeds the range for the minimal clinically important difference for gait speed of 0.10 to 0.20 m/s52; however, the older age of the adults with vestibular loss contributed to their reduced GV.
The reduction in SL and lower PTV of adults with vestibular loss suggests that vestibular loss may have a lasting effect on gait stability. Although the minimal clinically important difference has not been established for SL and PTV from the i2MWT, the observed effect sizes were very large.
Compared with adults who do not fall, those who fall have a very large reduction in SL.53 In addition, SL that is normalized to height has 93% sensitivity and 53% specificity as a marker of recurrent falls in community-dwelling older adults.54 Further research is needed to determine whether SL is a marker for falls risk in adults with vestibular loss.
The lingering deficits in the turning dynamics of adults with vestibular loss are functionally meaningful. The PTV for half of adults with chronic vestibular loss, particularly those with BVL, was far below 180°/s.9 Although we did not dictate which direction participants should turn, lesion localization does not appear to affect which direction adults with vestibular loss choose to turn.28 This study’s data suggest that many adults with chronic vestibular loss have adapted to turn at speeds that help them avoid imbalance or to reduce the impact of oscillopsia on gait.55 In addition, the moderate associations of PTV with balance-related confidence, visual acuity during movement, and gait-related balance suggest that turning dynamics may play a role in fall risk for adults with vestibular loss. Spatiotemporal gait metrics obtained during straight walking and turning are similarly associated with future falls.56 Evidence from community-dwelling older adults demonstrates that prospective fallers turn less frequently, more slowly, and with less consistency in turning angle than individuals who do not fall.57 Self-limiting turning speed may reduce the risk of falls for adults with vestibular loss58 but may also result in insufficient vestibular stimulation to drive central compensation.28
Clear associations between the gait abnormalities detected with the i2MWT and fall risk have not been determined. Half of the adults with vestibular loss who reported at least 1 fall in the prior 6 months had total scores above the only established cutoff score (22 of 30 points) for fall risk on the FGA.47 In addition, gait abnormalities were detected with IMUs for all adults with vestibular loss who reported a fall and all adults with vestibular loss who had a total FGA score greater than 22 of 30. On the basis of this threshold, the FGA total score had poor sensitivity for detecting a history of falls in this population. Thus, the study data suggest that observational gait analysis alone may not be sufficient for documenting the potentially serious association of vestibular loss with gait.
Psychometric Properties of IMU-Based and Observational Gait Analyses
Gait analysis with IMUs has good to excellent reliability for healthy, young adults while they are walking on a treadmill, on a split-belt treadmill, and over ground.59 In addition, gait analysis using IMUs for the Timed Up and Go test has fair to good reliability in adults with vestibular loss.26 Validity is improved when IMUs are placed on the dorsum of the foot, as was the case in this study, rather than on the lower shank.59 The preliminary findings of good to excellent discriminative validity for SL and PTV from the i2MWT extend prior work26 indicating that IMU-based gait data collected during the Timed Up and Go test discriminate adults with vestibular loss based on fall history. Furthermore, these data suggest that peak whole-body turning velocity has moderate to strong concurrent validity with self-report and capacity-based measures of balance function.
Considerations for Interpreting Gait Analysis in Adults With Vestibular Loss
At the group level, these data are consistent with previous studies that reported reduced GV20,22,23,31 and increased fall risk14,15,17 for adults with vestibular loss. However, the results of the current study also agree with others who found that GV was normal for age and sex in 33% of adults with UVL and 39% of those with BVL at the start of VR.32 In addition, the current study data agree with these same authors,32 who also reported that 21% of adults with UVL and 22% of those with BVL scored above the threshold for increased fall risk based on observational gait analysis at their baseline assessment for VR.33 Therefore, although some generalizations regarding vestibulopathic gait may be possible, practitioners should always consider the specific data gathered from each patient, particularly because customized VR programs lead to superior outcomes compared with generic exercises.60
Considerations for the Recovery of Gait Function
Central vestibular compensation is idiosyncratic61; however, adaptive changes in locomotor patterns or increased coordination of the head and trunk may contribute to the recovery of gait after vestibular loss.62 Before undergoing ablative procedures, persons with Meniere disease, who experience a gradual loss of vestibular function over time, appear to benefit from compensatory strategies that reduce errors in turning angle63 and walking trajectory.31 However, gait deficits associated with turning angle,63 walking trajectory,31 and head-trunk coordination27,28 are present in the immediate postoperative period. The current study data indicate that significant deficits persist long after the onset of vestibular loss.
Beyond central vestibular compensation, gait deficits can be addressed through walking exercises, which are an important component of VR.12 More specific characterization of vestibulopathic gait using IMU-based methods may provide practitioners with further insight into designing effective interventions. The current study data indicate that gait stability and turning dynamics should be targets of VR for adults with chronic vestibular loss. Preliminary evidence suggests that spatiotemporal gait parameters normalize when persons with vestibular loss are exposed to noisy galvanic vestibular stimulation64 or complete paced walking tasks with a metronome set at 2.0 Hz.19 Interventions may need to be sex specific given that men with age-related vestibular loss increase their gait speed, whereas affected women decrease their speed.13
Limitations
This study has limitations. It was a cross-sectional study, and although the effect sizes for specific gait metrics were very large, the analyses presented here were completed post hoc, and the sample size, particularly for each vestibular loss subgroup, was small. The minimal detectable change values from these preliminary results will be useful for planning future work. The group of adults with vestibular loss was older than the group of healthy adults, and this very large difference in age contributed to the very large effect sizes for GV and TD. Thus, future studies should enroll age-matched participants. The instrumented gait analysis was conducted with 3 IMUs; a more complete characterization of vestibulopathic gait is possible if additional sensors are used. Associations between persistent gait deficits and risk of falls and between IMU-based gait analysis and observational gait tests should be explored further.
Conclusions
These results suggest that adults with chronic UVL and BVL have enduring clinically and functionally meaningful deficits in gait stability and turning dynamics. Both SL and PTV may have good criterion validity, and turn angle, TD, and mean velocity also distinguish adults with BVL from those with UVL. Practitioners should target gait stability and turning dynamics when designing customized VR for those with chronic vestibular loss who have persistent deficits.
References
- 1.Neuhauser HK, von Brevern M, Radtke A, et al. Epidemiology of vestibular vertigo: a neurotologic survey of the general population. Neurology. 2005;65(6):898-904. doi: 10.1212/01.wnl.0000175987.59991.3d [DOI] [PubMed] [Google Scholar]
- 2.Mendel B, Bergenius J, Langius-Eklöf A. Dizziness: a common, troublesome symptom but often treatable. J Vestib Res. 2010;20(5):391-398. doi: 10.3233/VES-2010-0370 [DOI] [PubMed] [Google Scholar]
- 3.Longridge NS, Mallinson AI. The Dynamic Illegible E-test: a technique for assessing the vestibulo-ocular reflex. Acta Otolaryngol. 1987;103(5-6):273-279. doi: 10.3109/00016488709107283 [DOI] [PubMed] [Google Scholar]
- 4.Black FO, Wall C III, Nashner LM. Effects of visual and support surface orientation references upon postural control in vestibular deficient subjects. Acta Otolaryngol. 1983;95(3-4):199-201. doi: 10.3109/00016488309130936 [DOI] [PubMed] [Google Scholar]
- 5.Ishikawa K, Edo M, Terada N, Okamoto Y, Togawa K. Gait analysis in patients with vertigo. Eur Arch Otorhinolaryngol. 1993;250(4):229-232. doi: 10.1007/BF00171530 [DOI] [PubMed] [Google Scholar]
- 6.Horak FB. Postural compensation for vestibular loss. Ann N Y Acad Sci. 2009;1164:76-81. doi: 10.1111/j.1749-6632.2008.03708.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Herdman SJ, Schubert MC, Das VE, Tusa RJ. Recovery of dynamic visual acuity in unilateral vestibular hypofunction. Arch Otolaryngol Head Neck Surg. 2003;129(8):819-824. doi: 10.1001/archotol.129.8.819 [DOI] [PubMed] [Google Scholar]
- 8.Herdman SJ, Hall CD, Schubert MC, Das VE, Tusa RJ. Recovery of dynamic visual acuity in bilateral vestibular hypofunction. Arch Otolaryngol Head Neck Surg. 2007;133(4):383-389. doi: 10.1001/archotol.133.4.383 [DOI] [PubMed] [Google Scholar]
- 9.Baloh RW, Kerber KA. Clinical Neurophysiology of the Vestibular System. 4th ed. Oxford University Press; 2011. [Google Scholar]
- 10.Herdman SJ. Vestibular rehabilitation. Curr Opin Neurol. 2013;26(1):96-101. doi: 10.1097/WCO.0b013e32835c5ec4 [DOI] [PubMed] [Google Scholar]
- 11.Bronstein A, Brandt T, Woollacott M, Nutt JG. Clinical Disorders of Balance, Posture, and Gait. 2nd ed. Arnold Press and Oxford University Press; 2004. [Google Scholar]
- 12.Hall CD, Herdman SJ, Whitney SL, et al. Vestibular rehabilitation for peripheral vestibular hypofunction: an evidence-based clinical practice guideline: from the American Physical Therapy Association Neurology Section. J Neurol Phys Ther. 2016;40(2):124-155. doi: 10.1097/NPT.0000000000000120 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Layman AJ, Li C, Simonsick E, Ferrucci L, Carey JP, Agrawal Y. Association between saccular function and gait speed: data from the Baltimore Longitudinal Study of Aging. Otol Neurotol. 2015;36(2):260-266. doi: 10.1097/MAO.0000000000000544 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Brown KE, Whitney SL, Wrisley DM, Furman JM. Physical therapy outcomes for persons with bilateral vestibular loss. Laryngoscope. 2001;111(10):1812-1817. doi: 10.1097/00005537-200110000-00027 [DOI] [PubMed] [Google Scholar]
- 15.Gill-Body KM, Beninato M, Krebs DE. Relationship among balance impairments, functional performance, and disability in people with peripheral vestibular hypofunction. Phys Ther. 2000;80(8):748-758. doi: 10.1093/ptj/80.8.748 [DOI] [PubMed] [Google Scholar]
- 16.Badke MB, Shea TA, Miedaner JA, Grove CR. Outcomes after rehabilitation for adults with balance dysfunction. Arch Phys Med Rehabil. 2004;85(2):227-233. doi: 10.1016/j.apmr.2003.06.006 [DOI] [PubMed] [Google Scholar]
- 17.Marchetti GF, Lin CC, Alghadir A, Whitney SL. Responsiveness and minimal detectable change of the dynamic gait index and functional gait index in persons with balance and vestibular disorders. J Neurol Phys Ther. 2014;38(2):119-124. doi: 10.1097/NPT.0000000000000015 [DOI] [PubMed] [Google Scholar]
- 18.Ishikawa K, Edo M, Yokomizo M, Terada N, Okamoto Y, Togawa K. Analysis of gait in patients with peripheral vestibular disorders. ORL J Otorhinolaryngol Relat Spec. 1994;56(6):325-330. doi: 10.1159/000276685 [DOI] [PubMed] [Google Scholar]
- 19.Tucker CA, Ramirez J, Krebs DE, Riley PO. Center of gravity dynamic stability in normal and vestibulopathic gait. Gait Posture. 1998;8(2):117-123. doi: 10.1016/S0966-6362(98)00030-7 [DOI] [PubMed] [Google Scholar]
- 20.Krebs DE, Goldvasser D, Lockert JD, Portney LG, Gill-Body KM. Is base of support greater in unsteady gait? Phys Ther. 2002;82(2):138-147. doi: 10.1093/ptj/82.2.138 [DOI] [PubMed] [Google Scholar]
- 21.Seidel B, Krebs DE. Base of support is not wider in chronic ataxic and unsteady patients. J Rehabil Med. 2002;34(6):288-292. doi: 10.1080/165019702760390392 [DOI] [PubMed] [Google Scholar]
- 22.Marchetti GF, Whitney SL, Blatt PJ, Morris LO, Vance JM. Temporal and spatial characteristics of gait during performance of the Dynamic Gait Index in people with and people without balance or vestibular disorders. Phys Ther. 2008;88(5):640-651. doi: 10.2522/ptj.20070130 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Schmidheiny A, Swanenburg J, Straumann D, de Bruin ED, Knols RH. Discriminant validity and test re-test reproducibility of a gait assessment in patients with vestibular dysfunction. BMC Ear Nose Throat Disord. 2015;15:6. doi: 10.1186/s12901-015-0019-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Kim SC, Kim JY, Lee HN, et al. A quantitative analysis of gait patterns in vestibular neuritis patients using gyroscope sensor and a continuous walking protocol. J Neuroeng Rehabil. 2014;11:58. doi: 10.1186/1743-0003-11-58 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Cohen HS, Mulavara AP, Peters BT, Sangi-Haghpeykar H, Bloomberg JJ. Tests of walking balance for screening vestibular disorders. J Vestib Res. 2012;22(2):95-104. doi: 10.3233/VES-2012-0443 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Sankarpandi SK, Baldwin AJ, Ray J, Mazzà C. Reliability of inertial sensors in the assessment of patients with vestibular disorders: a feasibility study. BMC Ear Nose Throat Disord. 2017;17:1. doi: 10.1186/s12901-017-0034-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Paul SS, Dibble LE, Walther RG, Shelton C, Gurgel RK, Lester ME. Characterization of head-trunk coordination deficits after unilateral vestibular hypofunction using wearable sensors. JAMA Otolaryngol Head Neck Surg. 2017;143(10):1008-1014. doi: 10.1001/jamaoto.2017.1443 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Paul SS, Dibble LE, Walther RG, Shelton C, Gurgel RK, Lester ME. Reduced purposeful head movements during community ambulation following unilateral vestibular loss. Neurorehabil Neural Repair. 2018;32(4-5):309-316. doi: 10.1177/1545968318770271 [DOI] [PubMed] [Google Scholar]
- 29.Mancini M, King L, Salarian A, Holmstrom L, McNames J, Horak FB. Mobility lab to assess balance and gait with synchronized body-worn sensors. J Bioeng Biomed Sci. 2011;(suppl 1):007. doi: 10.4172/2155-9538.S1-007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Halmagyi GM, Weber KP, Curthoys IS. Vestibular function after acute vestibular neuritis. Restor Neurol Neurosci. 2010;28(1):37-46. [DOI] [PubMed] [Google Scholar]
- 31.Borel L, Harlay F, Lopez C, Magnan J, Chays A, Lacour M. Walking performance of vestibular-defective patients before and after unilateral vestibular neurotomy. Behav Brain Res. 2004;150(1-2):191-200. doi: 10.1016/S0166-4328(03)00257-2 [DOI] [PubMed] [Google Scholar]
- 32.Herdman SJ, Hall CD, Delaune W. Variables associated with outcome in patients with unilateral vestibular hypofunction. Neurorehabil Neural Repair. 2012;26(2):151-162. doi: 10.1177/1545968311407514 [DOI] [PubMed] [Google Scholar]
- 33.Herdman SJ, Hall CD, Maloney B, Knight S, Ebert M, Lowe J. Variables associated with outcome in patients with bilateral vestibular hypofunction: preliminary study. J Vestib Res. 2015;25(3-4):185-194. doi: 10.3233/VES-150556 [DOI] [PubMed] [Google Scholar]
- 34.World Medical Association . World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191-2194. doi: 10.1001/jama.2013.281053 [DOI] [PubMed] [Google Scholar]
- 35.Bohannon RW, Bubela DJ, Magasi SR, Wang YC, Gershon RC. Sit-to-stand test: performance and determinants across the age-span. Isokinet Exerc Sci. 2010;18(4):235-240. doi: 10.3233/IES-2010-0389 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Feng Y, Schlosser FJ, Sumpio BE. The Semmes Weinstein monofilament examination as a screening tool for diabetic peripheral neuropathy. J Vasc Surg. 2009;50(3):675-682, e671. doi: 10.1016/j.jvs.2009.05.017 [DOI] [PubMed] [Google Scholar]
- 37.Mirka A, Black FO. Clinical application of dynamic posturography for evaluating sensory integration and vestibular dysfunction. Neurol Clin. 1990;8(2):351-359. doi: 10.1016/S0733-8619(18)30360-8 [DOI] [PubMed] [Google Scholar]
- 38.Powell LE, Myers AM. The Activities-specific Balance Confidence (ABC) Scale. J Gerontol A Biol Sci Med Sci. 1995;50A(1):M28-M34. doi: 10.1093/gerona/50A.1.M28 [DOI] [PubMed] [Google Scholar]
- 39.Jacobson GP, Newman CW. The development of the Dizziness Handicap Inventory. Arch Otolaryngol Head Neck Surg. 1990;116(4):424-427. doi: 10.1001/archotol.1990.01870040046011 [DOI] [PubMed] [Google Scholar]
- 40.Dannenbaum E, Chilingaryan G, Fung J. Visual vertigo analogue scale: an assessment questionnaire for visual vertigo. J Vestib Res. 2011;21(3):153-159. doi: 10.3233/VES-2011-0412 [DOI] [PubMed] [Google Scholar]
- 41.Alghwiri AA, Whitney SL, Baker CE, et al. The development and validation of the vestibular activities and participation measure. Arch Phys Med Rehabil. 2012;93(10):1822-1831. doi: 10.1016/j.apmr.2012.03.017 [DOI] [PubMed] [Google Scholar]
- 42.Wrisley DM, Marchetti GF, Kuharsky DK, Whitney SL. Reliability, internal consistency, and validity of data obtained with the functional gait assessment. Phys Ther. 2004;84(10):906-918. doi: 10.1093/ptj/84.10.906 [DOI] [PubMed] [Google Scholar]
- 43.R. Version 3.5. R Foundation for Statistical Computing; 2020.
- 44.Sullivan GM, Feinn R. Using effect size-or why the P value is not enough. J Grad Med Educ. 2012;4(3):279-282. doi: 10.4300/JGME-D-12-00156.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. 2nd ed. Prentice-Hall; 2000. [Google Scholar]
- 46.Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231-240. doi: 10.1519/15184.1 [DOI] [PubMed] [Google Scholar]
- 47.Wrisley DM, Kumar NA. Functional gait assessment: concurrent, discriminative, and predictive validity in community-dwelling older adults. Phys Ther. 2010;90(5):761-773. doi: 10.2522/ptj.20090069 [DOI] [PubMed] [Google Scholar]
- 48.Schwesig R, Leuchte S, Fischer D, Ullmann R, Kluttig A. Inertial sensor based reference gait data for healthy subjects. Gait Posture. 2011;33(4):673-678. doi: 10.1016/j.gaitpost.2011.02.023 [DOI] [PubMed] [Google Scholar]
- 49.Whitney SL, Wrisley DM, Brown KE, Furman JM. Is perception of handicap related to functional performance in persons with vestibular dysfunction? Otol Neurotol. 2004;25(2):139-143. [DOI] [PubMed] [Google Scholar]
- 50.Dannenbaum E, Chilingarian G, Fung J. Validity and responsiveness of the Visual Vertigo Analogue Scale. J Neurol Phys Ther. 2019;43(2):117-121. doi: 10.1097/NPT.0000000000000261 [DOI] [PubMed] [Google Scholar]
- 51.Hall CD, Herdman SJ. Reliability of clinical measures used to assess patients with peripheral vestibular disorders. J Neurol Phys Ther. 2006;30(2):74-81. doi: 10.1097/01.NPT.0000282571.55673.ed [DOI] [PubMed] [Google Scholar]
- 52.Bohannon RW, Glenney SS. Minimal clinically important difference for change in comfortable gait speed of adults with pathology: a systematic review. J Eval Clin Pract. 2014;20(4):295-300. doi: 10.1111/jep.12158 [DOI] [PubMed] [Google Scholar]
- 53.MacAulay RK, Allaire TD, Brouillette RM, et al. Longitudinal assessment of neuropsychological and temporal/spatial gait characteristics of elderly fallers: taking it all in stride. Front Aging Neurosci. 2015;7:34. doi: 10.3389/fnagi.2015.00034 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Rodríguez-Molinero A, Herrero-Larrea A, Miñarro A, et al. The spatial parameters of gait and their association with falls, functional decline and death in older adults: a prospective study. Sci Rep. 2019;9(1):8813. doi: 10.1038/s41598-019-45113-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Bronstein AM. Vision and vertigo: some visual aspects of vestibular disorders. J Neurol. 2004;251(4):381-387. doi: 10.1007/s00415-004-0410-7 [DOI] [PubMed] [Google Scholar]
- 56.Gulley E, Ayers E, Verghese J. A comparison of turn and straight walking phases as predictors of incident falls. Gait Posture. 2020;79:239-243. doi: 10.1016/j.gaitpost.2020.05.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Leach JM, Mellone S, Palumbo P, Bandinelli S, Chiari L. Natural turn measures predict recurrent falls in community-dwelling older adults: a longitudinal cohort study. Sci Rep. 2018;8(1):4316. doi: 10.1038/s41598-018-22492-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Herdman SJ, Blatt P, Schubert MC, Tusa RJ. Falls in patients with vestibular deficits. Am J Otol. 2000;21(6):847-851. [PubMed] [Google Scholar]
- 59.Washabaugh EP, Kalyanaraman T, Adamczyk PG, Claflin ES, Krishnan C. Validity and repeatability of inertial measurement units for measuring gait parameters. Gait Posture. 2017;55:87-93. doi: 10.1016/j.gaitpost.2017.04.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Black FO, Angel CR, Pesznecker SC, Gianna C. Outcome analysis of individualized vestibular rehabilitation protocols. Am J Otol. 2000;21(4):543-551. [PubMed] [Google Scholar]
- 61.Lacour M, Dutheil S, Tighilet B, Lopez C, Borel L. Tell me your vestibular deficit, and I’ll tell you how you’ll compensate. Ann N Y Acad Sci. 2009;1164:268-278. doi: 10.1111/j.1749-6632.2008.03731.x [DOI] [PubMed] [Google Scholar]
- 62.Patten C, Horak FB, Krebs DE. Head and body center of gravity control strategies: adaptations following vestibular rehabilitation. Acta Otolaryngol. 2003;123(1):32-40. doi: 10.1080/003655402000028036 [DOI] [PubMed] [Google Scholar]
- 63.Péruch P, Borel L, Gaunet F, Thinus-Blanc G, Magnan J, Lacour M. Spatial performance of unilateral vestibular defective patients in nonvisual versus visual navigation. J Vestib Res. 1999;9(1):37-47. [PubMed] [Google Scholar]
- 64.Wuehr M, Nusser E, Decker J, et al. Noisy vestibular stimulation improves dynamic walking stability in bilateral vestibulopathy. Neurology. 2016;86(23):2196-2202. doi: 10.1212/WNL.0000000000002748 [DOI] [PubMed] [Google Scholar]
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