Evidence map›Paper›PMID 35271156›Full record

ArticleSensors (Basel, Switzerland)2022

The Microsoft HoloLens 2 Provides Accurate Measures of Gait, Turning, and Functional Mobility in Healthy Adults.

Mandy Miller Koop, Anson B Rosenfeldt, Kelsey Owen, Amanda L Penko, Matthew C Streicher, Alec Albright, Jay L Alberts

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mandy Miller KoopDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Anson B RosenfeldtDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Kelsey OwenDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Amanda L PenkoDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Matthew C StreicherDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Alec AlbrightDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Jay L AlbertsDepartment of Biomedical Engineering, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.

Funding

Department of Defence W81XWH-19-1-0685
6 · The paper itself

Abstract

Augmented-reality (AR) headsets, such as the Microsoft HoloLens 2 (HL2), have the potential to be the next generation of wearable technology as they provide interactive digital stimuli in the context of ecologically-valid daily activities while containing inertial measurement units (IMUs) to objectively quantify the movements of the user. A necessary precursor to the widespread utilization of the HL2 in the fields of movement science and rehabilitation is the rigorous validation of its capacity to generate biomechanical outcomes comparable to gold standard outcomes. This project sought to determine equivalency of kinematic outcomes characterizing lower-extremity function derived from the HL2 and three-dimensional (3D) motion capture systems (MoCap). Sixty-six healthy adults completed two lower-extremity tasks while kinematic data were collected from the HL2 and MoCap: (1) continuous walking and (2) timed up-and-go (TUG). For all the continuous walking metrics (cumulative distance, time, number of steps, step and stride length, and velocity), equivalence testing indicated that the HL2 and MoCap were statistically equivalent (error ≤ 5%). The TUG metrics, including turn duration and turn velocity, were also statistically equivalent between the two systems. The accurate quantification of gait and turning using a wearable such as the HL2 provides initial evidence for its use as a platform for the development and delivery of gait and mobility assessments, including the in-person and remote delivery of highly salient digital movement assessments and rehabilitation protocols.

Indexed as

GaitWearable Electronic DevicesAdultBiomechanical PhenomenaHumansMovementWalkingaugmented realitygaitHoloLens 2timed up-and-goturningvalidation

Identifiers

PMID35271156
PMCPMC8914774

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.