Wearable inertial sensors to recognize basic human motion: What technology for what activity?
| dc.rights.license | open | en_US |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | DELLA-LIBERA, Vincent | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | LLARIA, Alvaro
ORCID: 0000-0002-0348-6419 IDREF: 259161004 | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | TERRASSON, Guillaume
ORCID: 0000-0002-3468-5883 IDREF: 136426158 | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | CUREA, Octavian
ORCID: 0000-0002-5030-2088 IDREF: 68259131 | |
| dc.date.accessioned | 2023-04-11T15:51:19Z | |
| dc.date.available | 2023-04-11T15:51:19Z | |
| dc.date.issued | 2020 | |
| dc.date.conference | 2020-06-10 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/172955 | |
| dc.description.abstractEn | Cyber-Physical Systems (CPS) are more and more present in many domains such as Industry 4.0, Smart Farming and Smart Healthcare Systems, among others, mainly due to the advantages offered by the combination of embedded electronics and data processing methods, inherent to CPS. An application field for which the characteristics of CPS are well adapted is the animal or human activity recognition, that can be useful to detect health troubles of the individuals under study. In this frame, this paper evaluates the adequation of different combinations of inertial sensors, together with an Artificial Neural Network based algorithm, to recognize basic human motion. The obtained experimental results are analyzed to corroborate if devices embedding different sensors, like Inertial Measurement Units, offer better performances than accelerometers when recognizing locomotion movements. | |
| dc.language.iso | EN | en_US |
| dc.subject.en | Cyber-Physical Systems | |
| dc.subject.en | Wearable inertial sensors | |
| dc.subject.en | Inertial measurement unit | |
| dc.subject.en | Human activity recognition | |
| dc.subject.en | Artificial neural network | |
| dc.subject.en | Smart Healthcare | |
| dc.title.en | Wearable inertial sensors to recognize basic human motion: What technology for what activity? | |
| dc.type | Communication dans un congrès avec actes | en_US |
| dc.identifier.doi | 10.1109/ICPS48405.2020.9274718 | en_US |
| dc.subject.hal | Sciences de l'ingénieur [physics]/Electronique | en_US |
| dc.subject.hal | Informatique [cs]/Réseau de neurones [cs.NE] | en_US |
| bordeaux.page | 344-349 | en_US |
| bordeaux.hal.laboratories | ESTIA - Recherche | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | Bordeaux INP | en_US |
| bordeaux.institution | Bordeaux Sciences Agro | en_US |
| bordeaux.conference.title | 3rd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) | en_US |
| bordeaux.title.proceeding | Proceedings of the 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS) | en_US |
| bordeaux.conference.city | Tampere | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.import.source | hal | |
| hal.identifier | hal-03038210 | |
| hal.version | 1 | |
| hal.export | false | |
| workflow.import.source | hal | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2020&rft.spage=344-349&rft.epage=344-349&rft.au=DELLA-LIBERA,%20Vincent&LLARIA,%20Alvaro&TERRASSON,%20Guillaume&CUREA,%20Octavian&rft.genre=proceeding |
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