Preliminary evaluation of a self-guided fall risk assessment tool for older adults

Sun, Ruopeng; Paramathayalan, Vignesh R.; Ratnam, Rama; Jain, Sanjiv; Morrow, Daniel G.; Sosnoff, Jacob J.

doi:10.1016/j.archger.2019.01.022

Cited by 13 publications

(20 citation statements)

References 21 publications

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“…The acceleration and gyroscope data from the Opal sensor was recorded at 128 Hz, and the gravity was corrected after the orientation estimation using an extended Kalman filter provided by APDM. Both the HoloLens and Opal data were segmented and synced to each task, resampled at 30 Hz and low-pass filtered (4th order Butterworth) with a cutoff frequency at 5 Hz [25,26,27].…”

Section: Methodsmentioning

confidence: 99%

“…Finally, time-aligned VT kinematic data (displacement, velocity, and acceleration) profiles were derived from Opal and HoloLens using numerical integration and differentiation accordingly. The VT data were also used to calculate the following performance features: (1) the STS duration: the time between the initiation of the first chair rising and the completion of the last chair descending [25,26]. (2) the STS mean duration of the sitting and standing phase [25,26].…”

Section: Methodsmentioning

confidence: 99%

“…The VT data were also used to calculate the following performance features: (1) the STS duration: the time between the initiation of the first chair rising and the completion of the last chair descending [25,26]. (2) the STS mean duration of the sitting and standing phase [25,26]. (3) The maximum acceleration and velocity during STS.…”

Section: Methodsmentioning

confidence: 99%

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

Sun

Sosnoff

2019

Sensors

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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

Sun

Sosnoff

2019

Sensors

Self Cite

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“…The remaining five studies correctly identified themselves as either a "virtual environment" (Liu, 2010;Fasilis et al, 2018;Lokka et al, 2018), a video game (Studenski et al, 2010) and a virtual avatar (Sun et al, 2019). This review categorized 35 studies as non-immersive VR but, only seven of these studies did not include the phrasing "Immersive VR" or "virtual reality" in their interventions.…”

Section: Virtual Reality Characteristicsmentioning

confidence: 99%

“…Regardless of age, active navigation can benefit recognition hits in a navigation task, compared to passive navigation. However, active navigation also increases the number of false recognition hits made by older adults (compared with younger adults) Sun et al (2019) System Usability Scale-10 item scale…”

Section: • Active Navigationmentioning

confidence: 99%

A Scoping Review of Augmented/Virtual Reality Health and Wellbeing Interventions for Older Adults: Redefining Immersive Virtual Reality

Carroll

Hopper

Farrelly

et al. 2021

Front. Virtual Real.

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Augmented and virtual reality (AR/VR) technologies are regularly used in psychology research to complement psychological interventions and to enable an individual to feel as if they are in an environment other than that of their immediate surroundings. A scoping review was performed to identify how AR/VR was being used with older adult populations to impact their physical and mental health. The review also sought to determine whether the terminology used in AR/VR research was consistent. The results show that 65 studies have been published in the last 20 years that meet the inclusion criteria (virtual/augmented reality) technology to impact older adults’ physical/mental health and wellbeing. Participants included healthy, physically, and cognitively impaired, and emotionally vulnerable older adults. We argue that over 70% of the studies included in this review were mislabeled as VR and only six papers included fully immersive VR/AR. The remaining studies use less immersive variants of virtual reality with their populations, and only one study made use of AR, which prompted the suggestion of a new definition for virtual reality. This paper also calls for an updated taxonomy of augmented and virtual reality definitions to address the lack of consistency found in studies that identify themselves as AR/VR when they are using less immersive technical set-ups, including displaying non-interactive videos on 2D screens.

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A multifactorial fall risk assessment system for older people utilizing a low-cost, markerless Microsoft Kinect

Kim

Xiong

2023

Ergonomics

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Background: Falls among older people are a major public health concern due to their high prevalence and serious consequences. Accurate, convenient, and cost-effective assessment of fall risk is an essential rst step for effective fall intervention and prevention. This study aims to develop a multifactorial fall risk assessment system for older people using a low-cost, markerless Microsoft Kinect.Methods: A Kinect-based test battery was designed and implemented in Unity3D to comprehensively assess major fall risk factors on physiological, psychological, and integrated functions. A follow-up experiment was conducted with 102 community-dwelling Korean older women to assess their fall risks and to investigate their prospective falls during a 6month follow-up period. The participants were divided into a high fall risk group (N=22) and a low fall risk group (N=80) based on prospective falls. Based on 11 variables with signi cant differences between the two groups, random forestbased machine learning classi cation models were further constructed to classify the fall risk.Results: Experimental results showed that the high fall risk group performed signi cantly worse on the Kinect-based test battery, especially in Sit to Stand 5 times (STS5), Choice Stepping Reaction Test (CSRT), and Fall E cacy Scale (FES).The random forest classi cation model achieved average classi cation accuracy of 84.7% with 83.3% sensitivity and 86.1% speci city. In addition, the individual's performance was computed as the percentile value of a normative database so that de ciencies can be clearly visualized and targeted for intervention.Conclusion: These ndings indicate that the developed low-cost, markerless Kinect-based multifactorial fall risk assessment system can not only accurately screen out 'at risk' older individuals, but also identify potential fall risk factors. The developed system has good potential for effective fall intervention and prevention.

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Preliminary evaluation of a self-guided fall risk assessment tool for older adults

Cited by 13 publications

References 21 publications

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

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

A Scoping Review of Augmented/Virtual Reality Health and Wellbeing Interventions for Older Adults: Redefining Immersive Virtual Reality

A multifactorial fall risk assessment system for older people utilizing a low-cost, markerless Microsoft Kinect

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