Evidence map›Paper›PMID 27854288›Full record

ArticleSensors (Basel, Switzerland)2016

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements.

Halim Tannous, Dan Istrate, Aziz Benlarbi-Delai, Julien Sarrazin, Didier Gamet, Marie Christine Ho Ba Tho, Tien Tuan Dao

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Halim TannousSorbonne University, Université de Technologie de Compiègne, CNRS, UMR 7338 Biomechanics and Bioengineering, 60200 Compiègne, France. halim.tannous@utc.fr.
Dan IstrateSorbonne University, Université de Technologie de Compiègne, CNRS, UMR 7338 Biomechanics and Bioengineering, 60200 Compiègne, France. mircea-dan.istrate@utc.fr.
Aziz Benlarbi-DelaiSorbonne University, Université Pierre et Marie Curie, L2E, Place Jussieu, 75252 Paris, France. aziz.benlarbi_delai@upmc.fr.
Julien SarrazinSorbonne University, Université Pierre et Marie Curie, L2E, Place Jussieu, 75252 Paris, France. julien.sarrazin@upmc.fr.
Didier GametSorbonne University, Université de Technologie de Compiègne, CNRS, UMR 7338 Biomechanics and Bioengineering, 60200 Compiègne, France. didier.gamet@utc.fr.
Marie Christine Ho Ba ThoSorbonne University, Université de Technologie de Compiègne, CNRS, UMR 7338 Biomechanics and Bioengineering, 60200 Compiègne, France. marie-christine.ho-ba-tho@utc.fr.
Tien Tuan DaoSorbonne University, Université de Technologie de Compiègne, CNRS, UMR 7338 Biomechanics and Bioengineering, 60200 Compiègne, France. tien-tuan.dao@utc.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject's movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

Indexed as

Biosensing TechniquesHumansMusculoskeletal Physiological PhenomenaRehabilitationexergameshome-based functional rehabilitationmulti-sensor fusionorientation estimation

Identifiers

PMID27854288
PMCPMC5134573

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Registered trials

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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.