Mostra el registre d'ítem simple
A trajectory-driven 3D channel model for human activity recognition
dc.contributor.author | Abdelgawwad, Ahmed Abdelmonem |
dc.contributor.author | Català Mallofré, Andreu |
dc.contributor.author | Pätzold, Matthias |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2021-10-01T09:13:48Z |
dc.date.available | 2021-10-01T09:13:48Z |
dc.date.issued | 2021-07-28 |
dc.identifier.citation | Abdelgawwad, A.; Catala, A.; Pätzold, M. A trajectory-driven 3D channel model for human activity recognition. "IEEE access", 28 Juliol 2021, vol. 9, p. 103393-103406. |
dc.identifier.issn | 2169-3536 |
dc.identifier.uri | http://hdl.handle.net/2117/352866 |
dc.description.abstract | This paper concerns the design, analysis, and simulation of a 3D non-stationary channel model fed with inertial measurement unit (IMU) data. The work in this paper provides a framework for simulating the micro-Doppler signatures of indoor channels for human activity recognition by using radiofrequency-based sensing technologies. The major human body segments, such as wrists, ankles, torso, and head, are modelled as a cluster of moving point scatterers. We provide expressions for the time variant (TV) speed and TV angles of motion based on 3D trajectories of the moving person. Moreover, we present mathematical expressions for the TV Doppler shifts and TV path gains associated with each moving point scatterer. Furthermore, a model of the non-stationary time variant channel transfer function (TV-CTF) is provided, which takes into account the effects caused by a moving person as well as fixed objects, such as furniture, walls, and ceiling. The micro-Doppler signatures of the moving person is extracted from the TV-CTF by employing the concept of the spectrogram, whose expression is also provided in closed form. Our model is confirmed by channel state information (CSI) measurements taken during walking, falling, and sitting activities. The proposed channel model is fed with IMU data that has been collected. We evaluate the micro-Doppler signature of the model and CSI measurements. The results show a good agreement between the spectrograms and the TV mean Doppler shifts of our IMU-driven channel model and the measured CSI. The proposed model enables a paradigm shift from traditional experimental-based approaches to future simulation-based approaches for the design of human activity recognition systems. |
dc.description.sponsorship | This work was supported in part by the WiCare Project under Grant 261895/F20, and in part by the Research Council of Norway (RCN). |
dc.format.extent | 14 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.rights | Attribution 4.0 International |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject.lcsh | Human activity recognition |
dc.subject.lcsh | Human-centered computing |
dc.subject.other | Human activity recognition |
dc.subject.other | Non-stationary fading channels |
dc.subject.other | Channel state information |
dc.subject.other | Channel transfer function |
dc.subject.other | Spectrogram |
dc.subject.other | Time-variant Doppler power characteristics |
dc.subject.other | Micro-Doppler signature |
dc.subject.other | Channel measurements |
dc.subject.other | Inertial measurement units |
dc.subject.other | Internet of Things |
dc.subject.other | Wireless sensing |
dc.title | A trajectory-driven 3D channel model for human activity recognition |
dc.type | Article |
dc.subject.lemac | Reconeixement de formes (Informàtica) |
dc.subject.lemac | Computació centrada en humans |
dc.subject.lemac | Doppler, Efecte |
dc.identifier.doi | 10.1109/ACCESS.2021.3098951 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9492038 |
dc.rights.access | Open Access |
local.identifier.drac | 32062036 |
dc.description.version | Postprint (published version) |
local.citation.author | Abdelgawwad, A.; Catala, A.; Pätzold, M. |
local.citation.publicationName | IEEE access |
local.citation.volume | 9 |
local.citation.startingPage | 103393 |
local.citation.endingPage | 103406 |
Fitxers d'aquest items
Aquest ítem apareix a les col·leccions següents
-
Articles de revista [1.391]