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Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, December 2017
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Title
Manual physical balance assistance of therapists during gait training of stroke survivors: characteristics and predicting the timing
Published in
Journal of NeuroEngineering and Rehabilitation, December 2017
DOI 10.1186/s12984-017-0337-8
Pubmed ID
Authors

Juliet A. M. Haarman, Erik Maartens, Herman van der Kooij, Jaap H. Buurke, Jasper Reenalda, Johan S. Rietman

Abstract

During gait training, physical therapists continuously supervise stroke survivors and provide physical support to their pelvis when they judge that the patient is unable to keep his balance. This paper is the first in providing quantitative data about the corrective forces that therapists use during gait training. It is assumed that changes in the acceleration of a patient's COM are a good predictor for therapeutic balance assistance during the training sessions Therefore, this paper provides a method that predicts the timing of therapeutic balance assistance, based on acceleration data of the sacrum. Eight sub-acute stroke survivors and seven therapists were included in this study. Patients were asked to perform straight line walking as well as slalom walking in a conventional training setting. Acceleration of the sacrum was captured by an Inertial Magnetic Measurement Unit. Balance-assisting corrective forces applied by the therapist were collected from two force sensors positioned on both sides of the patient's hips. Measures to characterize the therapeutic balance assistance were the amount of force, duration, impulse and the anatomical plane in which the assistance took place. Based on the acceleration data of the sacrum, an algorithm was developed to predict therapeutic balance assistance. To validate the developed algorithm, the predicted events of balance assistance by the algorithm were compared with the actual provided therapeutic assistance. The algorithm was able to predict the actual therapeutic assistance with a Positive Predictive Value of 87% and a True Positive Rate of 81%. Assistance mainly took place over the medio-lateral axis and corrective forces of about 2% of the patient's body weight (15.9 N (11), median (IQR)) were provided by therapists in this plane. Median duration of balance assistance was 1.1 s (0.6) (median (IQR)) and median impulse was 9.4Ns (8.2) (median (IQR)). Although therapists were specifically instructed to aim for the force sensors on the iliac crest, a different contact location was reported in 22% of the corrections. This paper presents insights into the behavior of therapists regarding their manual physical assistance during gait training. A quantitative dataset was presented, representing therapeutic balance-assisting force characteristics. Furthermore, an algorithm was developed that predicts events at which therapeutic balance assistance was provided. Prediction scores remain high when different therapists and patients were analyzed with the same algorithm settings. Both the quantitative dataset and the developed algorithm can serve as technical input in the development of (robot-controlled) balance supportive devices.

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Mendeley readers

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The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 109 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 17%
Student > Bachelor 17 16%
Researcher 13 12%
Student > Ph. D. Student 11 10%
Other 4 4%
Other 13 12%
Unknown 32 29%
Readers by discipline Count As %
Engineering 18 17%
Nursing and Health Professions 16 15%
Medicine and Dentistry 12 11%
Sports and Recreations 5 5%
Neuroscience 5 5%
Other 20 18%
Unknown 33 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 December 2017.
All research outputs
#17,921,555
of 23,009,818 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#947
of 1,291 outputs
Outputs of similar age
#305,842
of 438,131 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#23
of 26 outputs
Altmetric has tracked 23,009,818 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,291 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 438,131 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.