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This study was completed to validate a virtual reality (VR) headset (HTC ViveTM, Taiwan) as a tool to measure postural sway using the position and orientation tracking capabilities built into the VR system. If validated, the headset could be a cost-effective tool for balance assessments. Unity was used to develop an optical flow environment for VR. Study participants were able to experience three different speeds of optical flow displayed through the HTC Vive headset. However, for this study, participants were shown a scene in the virtual environment that did not move, causing no optical flow for the participant. A force plate and VR headset recorded position measurements during each trial. The Pearson correlation coefficients between the headset and the force plate data measurements were calculated in MATLAB, along with the root-mean-squared and peak-to-peak values for each trial. Results show that correlations in the AP plane tended to be greater than 0.4 and correlation in the ML plane tended to be greater than 0.6. The VR headset may be used for postural control measurements in clinic. However, further development of software and testing protocols for balance assessments is needed.

BACKGROUND Accurately measuring postural sway is an important part of balance assessment and rehabilitation. While force plates give accurate measurements, their cost and space requirements make their use impractical in many situations. OBJECTIVE The work presented here is aimed at addressing this issue by validating a virtual reality (VR) headset as a relatively low-cost alternative for postural sway measurement. The HTC Vive (VR) headset has built-in sensors that allow for position and orientation tracking making it a potentially effective tool for balance assessments. METHODS Participants in this study were asked to stand upright on a force plate (Neurocom platform) while wearing the HTC ViveTM. Position data was collected from the headset and force plate simultaneously as participants experienced a custom-built VR environment that covered their entire field of view. The Intraclass Correlation Coefficient (ICC) was used to examined the test-retest reliability on the postural control variables, including normalized path length (NPL), root-mean-square (RMS), and peak-to-peak (P2P), computed from the VR position output and the center of pressure (COP) data from the force plate. Liner regression were used to investigate the correlation between the VR and force plate measurements. RESULTS Results showed that the test-retest reliability of VR headset was similar to COP in RMS and P2P, ranging from .285 to .636 in VR and .228 to .759. Linear regression between VR and COP measures showed significant correlation in RMS and P2P. CONCLUSIONS Based on our results, the VR headset has potential for use in postural control measurements. However, further development of software and testing protocols for balance assessments is needed.

Background Accurately measuring postural sway is an important part of balance assessment and rehabilitation. Although force plates give accurate measurements, their costs and space requirements make their use impractical in many situations. Objective The work presented in this paper aimed to address this issue by validating a virtual reality (VR) headset as a relatively low-cost alternative to force plates for postural sway measurement. The HTC Vive (HTC Corporation) VR headset has built-in sensors that allow for position and orientation tracking, making it a potentially effective tool for balance assessments. Methods Participants in this study were asked to stand upright on a force plate (NeuroCom; Natus Medical Incorporated) while wearing the HTC Vive. Position data were collected from the headset and force plate simultaneously as participants experienced a custom-built VR environment that covered their entire field of view. The intraclass correlation coefficient (ICC) was used to examine the test-retest reliability of the postural control variables, which included the normalized path length, root mean square (RMS), and peak-to-peak (P2P) value. These were computed from the VR position output data and the center of pressure (COP) data from the force plate. Linear regression was used to investigate the correlations between the VR and force plate measurements. Results Our results showed that the test-retest reliability of the RMS and P2P value of VR headset outputs (ICC: range 0.285-0.636) was similar to that of the RMS and P2P value of COP outputs (ICC: range 0.228-0.759). The linear regression between VR and COP measures showed significant correlations in RMSs and P2P values. Conclusions Based on our results, the VR headset has the potential to be used for postural control measurements. However, the further development of software and testing protocols for balance assessments is needed.