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Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review

Overview of attention for article published in Sports Medicine, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review
Published in
Sports Medicine, February 2018
DOI 10.1007/s40279-018-0878-4
Pubmed ID
Authors

Martin O’Reilly, Brian Caulfield, Tomas Ward, William Johnston, Cailbhe Doherty

Abstract

Analysis of lower limb exercises is traditionally completed with four distinct methods: (1) 3D motion capture; (2) depth-camera-based systems; (3) visual analysis from a qualified exercise professional; and (4) self-assessment. Each method is associated with a number of limitations. The aim of this systematic review is to synthesise and evaluate studies which have investigated the capacity for inertial measurement unit (IMU) technologies to assess movement quality in lower limb exercises. A systematic review of studies identified through the databases of PubMed, ScienceDirect and Scopus was conducted. Articles written in English and published in the last 10 years which investigated an IMU system for the analysis of repetition-based targeted lower limb exercises were included. The quality of included studies was measured using an adapted version of the STROBE assessment criteria for cross-sectional studies. The studies were categorised into three groupings: exercise detection, movement classification or measurement validation. Each study was then qualitatively summarised. From the 2452 articles that were identified with the search strategies, 47 papers are included in this review. Twenty-six of the 47 included studies were deemed as being of high quality. Wearable inertial sensor systems for analysing lower limb exercises is a rapidly growing field of research. Research over the past 10 years has predominantly focused on validating measurements that the systems produce and classifying users' exercise quality. There have been very few user evaluation studies and no clinical trials in this field to date.

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The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 250 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 250 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 42 17%
Student > Ph. D. Student 40 16%
Student > Bachelor 24 10%
Researcher 15 6%
Student > Doctoral Student 14 6%
Other 33 13%
Unknown 82 33%
Readers by discipline Count As %
Sports and Recreations 48 19%
Engineering 34 14%
Medicine and Dentistry 18 7%
Nursing and Health Professions 14 6%
Computer Science 12 5%
Other 28 11%
Unknown 96 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 March 2019.
All research outputs
#1,973,501
of 24,601,689 outputs
Outputs from Sports Medicine
#1,379
of 2,852 outputs
Outputs of similar age
#42,270
of 335,382 outputs
Outputs of similar age from Sports Medicine
#39
of 59 outputs
Altmetric has tracked 24,601,689 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,852 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 54.7. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 335,382 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.