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Contribution for newspaper or weekly magazine . 2016
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https://doi.org/10.1109/embc.2...
Article . 2016 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2016
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Wearable embroidered muscle activity sensing device for the human upper leg

Authors: Roger B. Ribas Manero; Ali Shafti; Brendan Michael; Jug-Raj Grewal; J. Ll. Ribas Fernandez; Kaspar Althoefer; Matthew J. Howard 0001;

Wearable embroidered muscle activity sensing device for the human upper leg

Abstract

Within the last decade, running has become one of the most popular physical activities in the world. Although the benefits of running are numerous, there is a risk of Running Related Injuries (RRI) of the lower extremities. Electromyography (EMG) techniques have previously been used to study causes of RRIs, but the complexity of this technology limits its use to a laboratory setting. As running is primarily an outdoors activity, this lack of technology acts as a barrier to the study of RRIs in natural environments. This study presents a minimally invasive wearable muscle sensing device consisting of jogging leggings with embroidered surface EMG (sEMG) electrodes capable of recording muscle activity data of the quadriceps group. To test the use of the device, a proof of concept study consisting of $N=2$ runners performing a set of $5km$ running trials is presented in which the effect of running surfaces on muscle fatigue, a potential cause of RRIs, is evaluated. Results show that muscle fatigue can be analysed from the sEMG data obtained through the wearable device, and that running on soft surfaces (such as sand) may increase the likelihood of suffering from RRIs.

Preprint submitted to IEEE-EMBC 2016

Country
United Kingdom
Keywords

FOS: Computer and information sciences, Wearables, Electromyography, Textiles, Computer Science - Human-Computer Interaction, 610, Monitoring, Ambulatory, Running surfaces, Quadriceps Muscle, Running, Human-Computer Interaction (cs.HC), Running related injuries, Thigh, Muscle Fatigue, Humans

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
Green