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A structured overview of trends and technologies used in dynamic hand orthoses

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, June 2016
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Title
A structured overview of trends and technologies used in dynamic hand orthoses
Published in
Journal of NeuroEngineering and Rehabilitation, June 2016
DOI 10.1186/s12984-016-0168-z
Pubmed ID
Authors

Ronald A. Bos, Claudia J.W. Haarman, Teun Stortelder, Kostas Nizamis, Just L. Herder, Arno H.A. Stienen, Dick H. Plettenburg

Abstract

The development of dynamic hand orthoses is a fast-growing field of research and has resulted in many different devices. A large and diverse solution space is formed by the various mechatronic components which are used in these devices. They are the result of making complex design choices within the constraints imposed by the application, the environment and the patient's individual needs. Several review studies exist that cover the details of specific disciplines which play a part in the developmental cycle. However, a general collection of all endeavors around the world and a structured overview of the solution space which integrates these disciplines is missing. In this study, a total of 165 individual dynamic hand orthoses were collected and their mechatronic components were categorized into a framework with a signal, energy and mechanical domain. Its hierarchical structure allows it to reach out towards the different disciplines while connecting them with common properties. Additionally, available arguments behind design choices were collected and related to the trends in the solution space. As a result, a comprehensive overview of the used mechatronic components in dynamic hand orthoses is presented.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 269 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 <1%
Unknown 268 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 52 19%
Student > Ph. D. Student 42 16%
Student > Bachelor 35 13%
Researcher 24 9%
Student > Doctoral Student 17 6%
Other 27 10%
Unknown 72 27%
Readers by discipline Count As %
Engineering 116 43%
Medicine and Dentistry 19 7%
Nursing and Health Professions 14 5%
Computer Science 10 4%
Neuroscience 8 3%
Other 23 9%
Unknown 79 29%