More than 1/3 of adults in the United States seek medical attention for vestibular disorders and hearing loss; disorders that can triple one's fall risk and have a profound effect on one's participation in activities of daily living. Hearing loss has been shown to reduce balance performance and could be one modifiable risk factor for falls. Patients with vestibular hypofunction tend to avoid busy, hectic, visually complex, and loud environments because these environments provoke dizziness and imbalance. While the visual impact on balance is well known, less is known about the importance of sounds. In search for a possible mechanism to explain a relationship between hearing and balance control, some studies suggested that sounds may serve as an auditory anchor, providing spatial cues for balance, similar to vision. However, the majority of these studies tested healthy adults' response to sounds with blocked visuals. It is also possible that a relationship between hearing loss and balance problems is navigated via an undetected vestibular deficit. By understanding the role of auditory input in balance control, falls may be prevented in people with vestibular disorders and hearing loss. Therefore, there is a critical need for a systematic investigation of balance performance in response to simultaneous visual and auditory perturbations, similar to real-life situations. To answer this need, the investigators used recent advances in virtual reality technology and developed a Head Mounted Display (HMD) protocol of immersive environments, combining specific manipulations of visuals and sounds, including generated sounds (i.e., white noise) and real-world recorded sounds (e.g., a train approaching a station). This research will answer the following questions: (1) Are sounds used for balance and if yes, via what mechanism? (2) Do individuals with single-sided hearing loss have a balance problem even without any vestibular issues? (3) Are those with vestibular loss destabilized by sounds? To address these questions, the following specific aims will be investigated in individuals with unilateral peripheral vestibular hypofunction (n=45), individuals with single-sided deafness (n=45), and age-matched controls (n=45): Aim 1: Establish the role of generated and natural sounds in postural control in different visual environments; Aim 2: Determine the extent to which a static white noise can improve balance within a dynamic visual environment.
Introduction: Aim 1 is to establish the role of generated and natural sounds in postural control given the visual environment and sensory loss. For that the investigators will measure postural sway in individuals with unilateral peripheral vestibular hypofunction (n=45), individuals with SSD (n=45) and age-matched controls (n=45). They will be tested in an immersive virtual reality environment displaying an abstract 3-wall display of stars or a subway station. Within each environment, we will compare changes in postural sway in response to visual (static, dynamic) and auditory perturbations (no sound, dynamic sound, i.e., rhythmic white noise in the stars environment or natural sounds, such as moving trains, in the subway environment). Aim 2 is to determine the extent to which a static white noise can improve balance (reduce postural sway) within a dynamic visual environment in individuals with and without sensory loss. To accomplish this aim, the 3 groups of participants will be tested within the same visual environment but here we will compare their sway within a sound-free dynamic visual environment to that with static white noise. System: Visuals were designed in C# language using standard Unity Engine version 2018.1.8f1(64-bit) (©Unity Tech., San Francisco, CA, USA). The scenes will be delivered via an HTC Vive headset (Taoyuan City, Tai-wan) controlled by a Dell Alienware laptop 15 R3 (Round Rock, TX, USA). The Vive has built-in positional track-ing operating at 60Hz and a refresh rate at 90 Hz. Sounds will be delivered via Bose (Bose Corporation, Fram-ingham, MA, USA) QuietComfort 35 wireless headphones II with active noise cancellation and 360º spatial audio. The process of creating auditory cues included over 20 hours of sound field recording based on the targeted scenes and their intensity levels in New York City. Auditory cues were captured with the Sennheiser Ambeo microphone in first order Ambisonics format. The background sounds merged with a sound design process which involved simulating the detailed environmental sounds that exist within the natural environment to develop a real-world sonic representation. The audio files were processed in Wwise and integrated into Unity. Postural sway will be recorded at 100 Hz by Qualisys software for a Kistler 5233A force-platform (Winterthur, Switzer-land). Data Collection: Potentially eligible participants will complete a demographics form and go through the following diagnostic screening at the Ear Institute: Caloric Test, Video Head Impulse Test (vHIT), Ocular / Cervical Vestibular Evoked Myogenic Potential, and Audiogram. Visual and somatosensory screening will be done at the Ear Institute as well. This first session is expected to take 2.5 hours to complete. Participants will receive questionnaires to complete at home or on the next session. The Dizziness Handicap Inventory (DHI) was designed to identify difficulties that a patient may be experiencing because of dizziness. The Activities-Specific Balance Confidence (ABC) is a measure of confidence in performing various ambulatory activities without falling or feeling 'unsteady'. The State-Trait Anxiety Inventory (STAI) assesses the severity of anxiety symptoms and a generalized tendency to be anxious. The Speech, Spatial and Quality of Hearing 12-item Scale (SSQ12) is a valid, short version of the original SSQ which provides insights on day-to-day hearing loss impact. The virtual reality protocol (testing by the PI at the NYU Human Performance Laboratory) includes 12 conditions: 2 environments (an abstract display of stars, a subway station) X 2 visuals (moving, static) X 3 sounds (dynamic, none, static white noise) each repeated 3 times for a total of 36 trials. It will be randomized and completed over 1-2 sessions, as needed of up to 90 minutes each. Sounds will be played at the highest level that is comfortable to the participant. Scenes are 60 seconds long. Throughout all sessions, the patients will complete the Simulator Sickness Questionnaire, used to monitor participants' symptoms. Data Analysis: For each of the 3 measures of interest and for each environment, we will fit a linear mixed effects model. Each model will include main effects of group, visual condition, and auditory condition, as well as all 2 and 3-way interactions. The models will also control for caloric and Video Head Impulse Test (vHIT) test results as well as Age Related Hearing Loss and age. For aim 1, we will assess the significance of contrasts between no sounds / dynamic sounds for the different visual conditions and groups. For aim 2, the same will be done for contrasts between no sounds / static sounds. These models estimate the difference in visual weighting and reweighting between the groups, maximizing the information we can obtain from the data by accounting for the inherent multi-level study design (person, conditions, repetitions). Since each person completes various trials for each condition, the linear mixed effects model accounts for these sources of variability. P-values for the fixed effects will be calculated using the Satterthwaite approximation for the degrees of freedom for the T-distribution80. In addition, we will descriptively explore the relationship between DP, area, self-reported outcomes (DHI, ABC, STAI, SSQ12), and age.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
107
Within each scene there will be 2 levels of visual input (static or dynamic) combined with 3 levels of sounds (static, none or dynamic). Postural responses to each combination will be evaluated in order to assess the role of generated and natural sounds in postural control and whether static sounds can improve balance within dynamic virtual environments.
New York Eye and Ear Infirmary of Mount Sinai
New York, New York, United States
New York University Physical Therapy Department
New York, New York, United States
Root Mean Square Velocity Anterior-posterior [AP] in cm/s (RMSV)
RMSV is defined the difference in position between two data points divided by the average time interval, with the velocities at each point squared then summed. The square root of this sum is then divided by the number of data points. Higher values reflect more postural sway. This will be calculated as an average across repetitions where participants saw a moving subway environment (dynamic visuals) combined with real-recorded sounds (moving sounds). Higher RMSV indicated less postural stability. This metric is calculated from center-of-pressure data collected by a force platform. Participants were standing on foam placed on the force platform.
Time frame: Will be measured during all 60 seconds scenes
Root Mean Square Velocity in the Medio-lateral Direction in cm/s (RMSV)
RMSV is defined the difference in position between two data points divided by the average time interval, with the velocities at each point squared then summed. The square root of this sum is then divided by the number of data points. Higher values reflect more postural sway. This will be calculated as an average across repetitions where participants saw a moving subway environment (dynamic visuals) combined with real-recorded sounds (moving sounds). Higher RMSV indicated less postural stability. This metric is calculated from center-of-pressure data collected by a force platform. Participants were standing on foam placed on the force platform.
Time frame: measured during all 60 seconds scenes
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