Evidence map›Paper›PMID 34696071›Full record

ArticleSensors (Basel, Switzerland)2021

Validation of 3-Space Wireless Inertial Measurement Units Using an Industrial Robot.

Jaime Hislop, Mats Isaksson, John McCormick, Chris Hensman

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Adaptive Lifting Index (Sensors (Basel, Switzerland) · 2024
    Article
  4. Article
  5. Article
  6. 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

4 authors.

Jaime HislopDepartment of Mechanical Engineering and Product Design Engineering, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0002-2023-8601
Mats IsakssonDepartment of Mechanical Engineering and Product Design Engineering, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0003-3047-6811
John McCormickCentre for Transformative Media Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Chris HensmanDepartment of Surgery, Monash University, Clayton, VIC 3168, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inertial Measurement Units (IMUs) are beneficial for motion tracking as, in contrast to most optical motion capture systems, IMU systems do not require a dedicated lab. However, IMUs are affected by electromagnetic noise and may exhibit drift over time; it is therefore common practice to compare their performance to another system of high accuracy before use. The 3-Space IMUs have only been validated in two previous studies with limited testing protocols. This study utilized an IRB 2600 industrial robot to evaluate the performance of the IMUs for the three sensor fusion methods provided in the 3-Space software. Testing consisted of programmed motion sequences including 360° rotations and linear translations of 800 mm in opposite directions for each axis at three different velocities, as well as static trials. The magnetometer was disabled to assess the accuracy of the IMUs in an environment containing electromagnetic noise. The Root-Mean-Square Error (RMSE) of the sensor orientation ranged between 0.2° and 12.5° across trials; average drift was 0.4°. The performance of the three filters was determined to be comparable. This study demonstrates that the 3-Space sensors may be utilized in an environment containing metal or electromagnetic noise with a RMSE below 10° in most cases.

Indexed as

RoboticsBiomechanical PhenomenaMotioncomplementary filtergradient descent filterInertial Measurement Unit (IMU)Kalman filtersensor fusionsensor validation

Identifiers

PMID34696071
PMCPMC8537168

What OpenQuestion holds

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LicenceCC BY
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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.