The Validity of a Mixed Reality-Based Automated Functional Mobility Assessment

Ruopeng Sun, Roberto G. Aldunate, Jacob J. Sosnoff

Research output: Contribution to journalArticlepeer-review


Functional mobility assessments (i.e., Timed Up and Go) are commonly used clinical tools for mobility and fall risk screening in older adults. In this work, we proposed a new Mixed Reality (MR)-based assessment that utilized a Microsoft HoloLensTM headset to automatically lead and track the performance of functional mobility tests, and subsequently evaluated its validity in comparison with reference inertial sensors. Twenty-two healthy adults (10 older and 12 young adults) participated in this study. An automated functional mobility assessment app was developed, based on the HoloLens platform. The mobility performance was recorded with the headset built-in sensor and reference inertial sensor (Opal, APDM) taped on the headset and lower back. The results indicate that the vertical kinematic measurements by HoloLens were in good agreement with the reference sensor (Normalized RMSE ~ 10%, except for cases where the inertial sensor drift correction was not viable). Additionally, the HoloLens-based test completion time was in perfect agreement with the clinical standard stopwatch measure. Overall, our preliminary investigation indicates that it is possible to use an MR headset to automatically guide users (without severe mobility deficit) to complete common mobility tests, and this approach has the potential to provide an objective and efficient sensor-based mobility assessment that does not require any direct research/clinical oversight.
Original languageEnglish (US)
Article number2183
Issue number9
StatePublished - May 11 2019


  • mixed reality headset
  • mobility assessment
  • wearable sensor
  • fall risk
  • aging
  • Mixed reality headset
  • Mobility assessment
  • Wearable sensor
  • Aging
  • Fall risk

ASJC Scopus subject areas

  • Analytical Chemistry
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering
  • Biochemistry


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