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Method Article

Measuring the Kinematics of Daily Living Movements with Motion Capture Systems in Virtual Reality

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DOI:

10.3791/57284

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April 5th, 2018

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In This Article

Summary

We designed a virtual reality test to assess instrumental activities of daily living (IADL) with a motion capture system. We propose a detailed kinematic analysis to interpret the participant's various movements, including trajectory, moving distance, and time to completion to evaluate IADL capabilities.

Abstract

The inability to complete instrumental activities of daily living (IADL) is a precursor to various neuropsychological diseases. Questionnaire-based assessments of IADL are easy to use but prone to subjective bias. Here, we describe a novel virtual reality (VR) test to assess two complex IADL tasks: handling financial transactions and using public transportation. While a participant performs the tasks in a VR setting, a motion capture system traces the position and orientation of the dominant hand and head in a three-dimensional Cartesian coordinate system. Kinematic raw data are collected and converted into 'kinematic performance measures,' i.e., motion trajectory, moving distance, and time to completion. Motion trajectory is the path of a particular body part (e.g., dominant hand or head) in space. Moving distance refers to the total distance of the trajectory, and time to completion is how long it took to complete an IADL task. These kinematic measures could discriminate patients with cognitive impairment from healthy controls. The development of this kinematic measuring protocol allows detection of early IADL-related cognitive impairments.

Introduction

Instrumental activities of daily living (IADL), such as handling financial transactions, using public transportation, and cooking, are medical markers since they require multiple neuropsychological functions1. Impaired IADL capabilities are thus considered precursors to neurological diseases, such as mild cognitive impairment (MCI) and dementia2. Gold's comprehensive review of IADL tasks3 indicated that more cognitively demanding tasks, such as managing finances and using public transportation, were the earliest predictor of MCI and dementia.

To date, the most commo....

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Protocol

All experimental procedures described here were approved by the Institutional Review Board of Hanyang University, according to the Declaration of Helsinki (HYI-15-029-2). 6 healthy controls (4 males and 2 females) and 6 MCI patients (3 males and 3 females) were recruited from a tertiary medical center, Hanyang University Hospital.

1. Recruit Participants

  1. Recruit MCI patients (i.e., impaired IADL capabilities) and healthy controls (i.e., normal IADL capabilities) aged between 70 - 80 years.
  2. With the help of a neurologist with more than 10 years of clinical experience, review the patients' medical h....

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Results

CSV files from "Task 1: Withdraw money" were analyzed using the statistical software R to calculate the dominant hand trajectory, moving distance, and time to completion. The trajectory of the dominant hand movement is visualized (Figure 6). The moving distance of the dominant hand is calculated by summing the total distances between sequential hand positions while performing Task 1. The distance between positions is the Euclidian distance. Time to completion.......

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Discussion

We detailed a kinematic measuring protocol of daily living movements with motion capture systems in an immersive VR environment. First, the experimental setting guided to how to set up, prepare, and familiarize participants with the immersive VR environment. Second, we developed two standardized IADL tasks in VR. Third, Step 3 and Step 5 in the Protocol section are the most critical steps to minimize VR sickness. When setting up the motion capture systems in the virtual environment (Step 3), it is important to mount the .......

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Disclosures

The authors declare no conflicts of interest.

Acknowledgements

K.S. and A.L. contribute equally. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2016R1D1A1B03931389).

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
ComputerN/AN/AComputer requirements:                                                            - Single socket H3 (LGA 1150) supports
- Intel® Xeon® E3-1200 v3, 4th gen. Core i7/i5/i3 processors
- Intel® C226 Express PCH
- Up to 32GB DDR3 ECC/non-ECC 1600MHz UDIMM in 4 sockets
- Dual Gigabit Ethernet LAN ports
- 8x SATA3 (6Gbps)
- 2x PCI-E 3.0 x16, 3x PCI-E 2.0 x1, and 2x PCI 5V 32-bit slots
- 6x USB 3.0 (2 rear + 4 via headers)
- 10x USB 2.0 (4 rear + 6 via headers)
- HD Audio 7.1 channel connector by Realtek ALC1150
- 1x DOM power connector and 1x SPDIF Out Header
- 800W High Efficiency Power Supply
- Intel Xeon E3-1230v3
- DDR3 PC12800 8GB ECC
- WD 1TB BLUE WD 10EZEX  3.5"
- NVIDIA QUADRO K5000 & SYNC
Stereoscopic 3D ProjectorBarcoF35 AS3D WUXGAResolution:
- WQXGA (2,560 x 1,600)
- Panorama (2,560 x 1,080)
- WUXGA (1,920 x 1,200), 1080p (1,920 x 1,080)
Stereoscopic GlassesVolfoniEdge 1.2For further information, visit http://volfoni.com/en/edge-1-2/
Motion Capture SystemsNaturalPoint OptiTrack17WFor further information, visit http://optitrack.com/products/prime-17w/
OptiTrack (Motion capture software)NaturalPoint OptiTrackMotive 2.0For further information, visit https://optitrack.com/downloads/motive.html
MiddleVR (Middleware software)MiddleVRMiddleVR For UnityFor further information, visit http://www.middlevr.com/middlevr-for-unity/
VRDaemon (Middleware software)MiddleVRMiddleVR For UnityFor further information, visit http://www.middlevr.com/middlevr-for-unity/
Unity3D (Game engine)Unity TechnologiesPersonalFor further information, visit https://unity3d.com/unity

References

  1. Reppermund, S., et al. Impairment in instrumental activities of daily living with high cognitive demand is an early marker of mild cognitive impairment: the Sydney Memory and Ageing Study. Psychol. Med. 43 (11), 2437-2445 (2013).
  2. Graf, C.

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