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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comprehensive measurement of stroke gait characteristics with a single accelerometer in the laboratory and community: a feasibility, validity and reliability study
|
|---|---|
| Published in |
Journal of NeuroEngineering and Rehabilitation, December 2017
|
| DOI | 10.1186/s12984-017-0341-z |
| Pubmed ID | |
| Authors |
Sarah A. Moore, Aodhan Hickey, Sue Lord, Silvia Del Din, Alan Godfrey, Lynn Rochester |
| Abstract |
Application of objective measurement of stroke gait with accelerometer-based wearable technology and associated algorithms is increasing, despite reports questioning the accuracy of this technique in quantifying specific stroke-related gait impairments. The aim of this study is to determine the feasibility, validity and reliability of a low-cost open-source system incorporating algorithms and a single tri-axial accelerometer-based wearable to quantify gait characteristics in the laboratory and community post-stroke. Twenty-five participants with stroke wore the wearable (AX3, Axivity) on the lower back during a laboratory 2 minute continuous walk (preferred pace) on two occasions a week apart and continuously in the community for two consecutive 7 day periods. Video, instrumented walkway (GaitRite) and an OPAL accelerometer-based wearable were used as laboratory references. Feasibility of the proposed system was good. The system was valid for measuring step count (ICC 0.899). Inherent differences in gait quantification between algorithm and GaitRite resulted in difficulties comparing agreement between the different systems. Agreement was moderate-excellent (ICC 0.503-0.936) for mean and variability gait characteristics vs. OPAL. Agreement was moderate-poor between the system and OPAL for asymmetry characteristics. Moderate-excellent reliability (ICC 0.534-0.857) was demonstrated for 11/14 laboratory measured gait characteristics. Community test-retest reliability was good-excellent (ICC 0.867-0.983) for all except one (ICC 0.699) of the 19 gait characteristics. The proposed system is a low-cost, reliable tool for quantifying gait post-stroke with multiple potential applications. Further refinement to optimise gait quantification algorithms for certain gait characteristics including gait asymmetry is required. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 50% |
| United States | 2 | 20% |
| Australia | 2 | 20% |
| Unknown | 1 | 10% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 50% |
| Members of the public | 4 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 145 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 18% |
| Student > Master | 21 | 14% |
| Student > Bachelor | 19 | 13% |
| Researcher | 16 | 11% |
| Student > Doctoral Student | 12 | 8% |
| Other | 19 | 13% |
| Unknown | 32 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 22 | 15% |
| Nursing and Health Professions | 19 | 13% |
| Medicine and Dentistry | 16 | 11% |
| Neuroscience | 13 | 9% |
| Sports and Recreations | 12 | 8% |
| Other | 18 | 12% |
| Unknown | 45 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 17 February 2018.
All research outputs
#5,582,000
of 23,372,952 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#314
of 1,307 outputs
Outputs of similar age
#108,199
of 443,970 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#8
of 22 outputs
Altmetric has tracked 23,372,952 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,307 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done well, scoring higher than 75% 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 443,970 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 75% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.