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A Soft Exoskeleton Glove for Hand Bilateral Training via Surface EMG - PubMed
Source: pubmed.ncbi.nlm.nih.gov
Article summary:
1. A soft exoskeleton glove (SExoG) system has been developed for hand bilateral training via surface electromyography (sEMG) signals from the non-paretic hand.
2. A customization method of geometrical parameters of soft actuators was presented, and their structure was redesigned to support four hand motions (extension, rest, spherical grip, and fist).
3. A two-step hybrid model combining the neural network and the state exclusion algorithm was proposed to recognize four hand motions via sEMG signals from the healthy limb with a mean accuracy of 98.7%.
Article analysis:
The article is generally reliable and trustworthy in its reporting of the development of a soft exoskeleton glove (SExoG) system for hand bilateral training via surface electromyography (sEMG) signals from the non-paretic hand. The authors provide detailed information on the design and implementation of the SExoG system, as well as a comprehensive description of their experiments and results. The article also includes figures that illustrate key points in an easy-to-understand manner.
The article does not appear to have any major biases or one-sided reporting, as it presents both sides equally by providing evidence for its claims and exploring counterarguments where necessary. Furthermore, there is no promotional content or partiality present in the article. The authors also note potential risks associated with using such a device, such as discomfort due to pressure on the wearer's hands.
In conclusion, this article is reliable and trustworthy in its reporting on the development of a soft exoskeleton glove for hand bilateral training via surface EMG signals from non-paretic hands.