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Citation |
Llamas C, González MA, Hernandez C, Vegas J. J. Biomed. Inform. 2016; 63: 249-258. |
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Affiliation |
Departamento de Informática, Universidad de Valladolid. Electronic address: jvegas@infor.uva.es. |
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Copyright |
(Copyright © 2016, Elsevier Publishing) |
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DOI |
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PMID |
27593165 |
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Abstract |
Nearly every practical improvement in modelling human motion is well founded in a properly designed collection of data or datasets. These datasets must be made publicly available for the community could validate and accept them. It is reasonable to concede that a collective, guided enterprise could serve to devise solid and substantial datasets, as a result of a collaborative effort, in the same sense as the open software community does. In this way datasets could be complemented, extended and expanded in size with, for example, more individuals, samples and human actions. For this to be possible some commitments must be made by the collaborators, being one of them sharing the same data acquisition platform. In this paper, we offer an affordable open source hardware and software platform based on inertial wearable sensors in a way that several groups could cooperate in the construction of datasets through common software suitable for collaboration. Some experimental results about the throughput of the overall system are reported showing the feasibility of acquiring data from up to 6 sensors with a sampling frequency no less than 118Hz. Also, a proof-of-concept dataset is provided comprising sampled data from 12 subjects suitable for gait analysis. Language: en |