Evidence map›Paper›PMID 34300390›Full record

ArticleSensors (Basel, Switzerland)2021

Ultra-Wideband Indoor Positioning and IMU-Based Activity Recognition for Ice Hockey Analytics.

Robbe Vleugels, Ben Van Herbruggen, Jaron Fontaine, Eli De Poorter

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 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

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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

4 authors.

Robbe VleugelsIDLab, Department of Information Technology, Ghent University-imec, 9000 Ghent, Belgium.
Ben Van HerbruggenIDLab, Department of Information Technology, Ghent University-imec, 9000 Ghent, Belgium.ORCID 0000-0001-8900-4881
Jaron FontaineIDLab, Department of Information Technology, Ghent University-imec, 9000 Ghent, Belgium.ORCID 0000-0001-5942-9440
Eli De PoorterIDLab, Department of Information Technology, Ghent University-imec, 9000 Ghent, Belgium.ORCID 0000-0002-0214-5751

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, gathering statistics and information for ice hockey training purposes mostly happens by hand, whereas the automated systems that do exist are expensive and difficult to set up. To remedy this, in this paper, we propose and analyse a wearable system that combines player localisation and activity classification to automatically gather information. A stick-worn inertial measurement unit was used to capture acceleration and rotation data from six ice hockey activities. A convolutional neural network was able to distinguish the six activities from an unseen player with a 76% accuracy at a sample frequency of 100 Hz. Using unseen data from players used to train the model, a 99% accuracy was reached. With a peak detection algorithm, activities could be automatically detected and extracted from a complete measurement for classification. Additionally, the feasibility of a time difference of arrival based ultra-wideband system operating at a 25 Hz update rate was determined. We concluded that the system, when the data were filtered and smoothed, provided acceptable accuracy for use in ice hockey. Combining both, it was possible to gather useful information about a wide range of interesting performance measures. This shows that our proposed system is a suitable solution for the analysis of ice hockey.

Indexed as

HockeyAccelerationRotationactivity recognitioncarbon fiber compositeconvolutional neural network (CNN)ice hockeyIMUindoor localizationmachine learningultra-wideband (UWB)wearable

Identifiers

PMID34300390
PMCPMC8309498

What OpenQuestion holds

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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.