Influence de la microgravité simulée sur les afférences cutanées plantaires et sur les afférences proprioceptives du muscle soleus de rat

Le modèle animal de Morey est très utilisé pour mimer les conditions (HH) d'Hypodynamie (absence de charge corporelle) et d'Hypokinésie (réduction de l'activité motrice) établies au cours d'un vol spatial. L'HH entraîne le développement d'une plasticité musculaire caractérisée par une atrophie, des pertes de forces, des modifications des cinétiques de contraction, et des changements en protéines (isoformes des Chaînes Lourdes de Myosines, MHC). L'origine de ces modifications n'est pas connue, bien qu'il soit suggéré un rôle joué par le manque de messages afférents. Notre travail s'est focalisé chez le rat sur les récepteurs cutanés plantaires et les fuseaux neuromusculaires (FNM) du muscle soleus. En HH, les mécanorécepteurs cutanés plantaires ne sont plus stimulés. Leur réactivation compense partiellement l'atrophie et les pertes de forces musculaires. Ce protocole pourrait donc constituer un moyen de contre mesure non invasif utilisable pour l'homme en vol spatial. Avant d'étudier l'activité des FNM (propriocepteur sensible à l'étirement musculaire en normo-gravité), nous avons défini les critères permettant de différencier les décharges des fibres afférentes Ia de celles des fibres II sur l'animal normal. Après HH, leurs réponses sont augmentées lors d'étirements en rampe et sinusoïdaux. L'étirement musculaire serait donc mieux perçu par les fuseaux et aurait pour origine des modifications dans les propriétés biomécaniques du muscle soleus. Ceci pourrait expliquer les modifications de la posture et de la locomation observées après HH. L'HH entraîne aussi des changements d'expression des isoformes de MHC I, slow-tonic, et [alpha]-cardiac au niveau des fibres intrafusales à sacs nucléaires. Ceci est la conséquence de changements d'activité de l'innervation motrice des FNM (axones [gamma] et [bêta]).LILLE1-BU (590092102) / SudocSudocFranceF

Dynamic Channel Modeling at 2.4 GHz for On-Body Area Networks

In wireless body area networks, on-body radio propagation channels are typically time-varying, because of the frequent body movements. The dynamic local body scattering dominates the temporal and spatial properties of the on-body channels. The influence varies largely depending on the distribution of the channels and the modes of body movements. In this paper, we present some major achievements on the dynamic onbody channel modeling at 2.4 GHz under the framework of the COST 2100 action. Results of two complementary measurement campaigns are presented: a geometry-based one on a single subject, and a scenario-based one covering different subjects. Statistical models including the Doppler spectrum and the spatial correlation of on-body channels are presented. An analytical model is also introduced to offer a time-space description of the on-body channels, which is validated by the geometry-based measurement campaign

Impact of MU-MIMO on passive Wi-Fi radars: threat or opportunity?

Passive Radars are devices that make use of existingcommunication signals for wireless channel sensing. On the otherhand, Wi-Fi has become the main gateway that connects devicesto the internet. Recently, IEEE established the WLAN SensingTask Group whose purpose is to study the feasibility of Wi-Fi-based environment sensing, where some of the technologiesshare similarities with Passive Radars. In the meantime, Multi-User Multiple-Input Multiple-Output (MU-MIMO) technologyis introduced to the Wi-Fi standard. It is designed to improvethe spatial efficiency of the wireless channel by simultaneouslytransmitting directive Wi-Fi signals to users. This paper aimsat quantifying the impact of MU-MIMO signals on Passive Wi-Fi-based Radar-like sensing. First, based on the position of theclient devices and the channel geometry, the radiation pattern ofthe AP is derived. While the wireless channel is illuminated bydirective radio waves, the magnitude of the Poynting vector isobtained at a local point target, which then reflects the incidentradio waves. Finally, the signal power seen by a sensing deviceis computed under the influence of a multipath channel. Ournumerical analyses focus on an urban street, and we show thatMU-MIMO can be seen as; i) an opportunity, since the vicinityof client devices are better illuminated, or ii) a threat, since theremaining parts of the street do not receive sufficient amount ofpower for channel sensing applications.info:eu-repo/semantics/inPres

A multi-antenna super-resolution passive Wi-Fi radar algorithm: Combined model order selection and parameter estimation

In recent years, Wi-Fi has become the main gateway that connects users to the internet. Considering the availability ofWi-Fi signals, and their suitability for channel estimation, IEEE established the Wi-Fi Sensing (WS) Task Group whose purposeis to study the feasibility of Wi-Fi-based environment sensing. However, Wi-Fi signals are transmitted over limited bandwidthswith a relatively small number of antennas in bursts, fundamentally limiting the range, Angle-of-Arrival and speed resolutions.This paper presents a super-resolution algorithm to perform the parameter estimation in a quasi-monostatic WS scenario. Theproposed algorithm, RIVES, estimates the range, Angle-of-Arrival and speed parameters with Vandermonde decomposition ofHankel matrices. To estimate the size of the signal subspace, RIVES uses a novel Model Order Selection method which eliminatesspurious noise targets based on their distance to the noise and signal subspaces. Various scenarios with multiple targets aresimulated to show the robustness of RIVES. In order to prove its accuracy, real-life indoor experiments are conducted with humantargets by using Software Defined Radios.info:eu-repo/semantics/publishe

Impact of MU-MIMO on Passive Wi-Fi Sensing: Threat or Opportunity?

Passive Radars are devices that make use of existing communication signals for wireless channel sensing. On the other hand, Wi-Fi, standardized under IEEE 802.11, has become the main gateway that connects devices to the internet. Recently, IEEE established the WLAN Sensing Task Group whose purpose is to study the feasibility of Wi-Fi-based environment sensing within the 802.11 framework, by combining radar and localization technologies. In the meantime, Multi-User Multiple-Input Multiple-Output (MU-MIMO) technology is introduced to the Wi-Fi standard. It is designed to improve the spatial efficiency of the wireless channel by simultaneously transmitting directive Wi-Fi signals to users. This paper aims at quantifying the impact of MU-MIMO signals on Passive Wi-Fi-based Radar-like sensing. First, based on the position of the client devices and the channel geometry, the radiation pattern of the AP is derived. While the wireless channel is illuminated by directive radio waves, the magnitude of the Poynting vector is obtained at a local point target, which then reflects the incident radio waves. Finally, the signal power seen by a sensing device is computed under the influence of a multipath channel. Our numerical analyses focus on an urban street, and we show that MU-MIMO can be seen as; i) an opportunity, since the vicinity of client devices are better illuminated, or ii) a threat, since the remaining parts of the street do not receive sufficient amount of power for channel sensing applications

Passive Wi-Fi-based Radars with 802.11ax MU-MIMO Signals: AoD Estimation with a Single Antenna

Passive Wi-Fi based Radar (PWR) is a device that makes use of existing Wi-Fi signals to detect/track targets in the environment. Therefore, the radar processing at the PWR largely depends on the Wi-Fi signal and its characteristics. In the latest amendment of the Wi-Fi standard, namely 802.11ax, Multi-User Multiple-Input Multiple-Output (MU-MIMO) technology is used to improve the spatial efficiency of the wireless channel by precoding the transmitted signal for each user. However, from the PWR perspective, precoding affects the signal power that illuminates a given target depending on its Angle-of-Departure (AoD). In this paper, we first quantify the impact of precoded signals on PWR processing. Then, we show that it is possible to recover the AoD of well-illuminated targets by using a PWR equipped with a single-antenna. To do so, a three-step-scheme, which works by exploiting the MU-MIMO synchronization and precoded signal transmission, is proposed. The accuracy of the proposed method, as well as its shortcomings are shown through numerical analyses

Impact of inter-body scattering on people counting with Wi-Fi sensing

We investigate the interactions between human bodies exposed to an incident electric field from a sensing-enabled Wi-Fi access point, to assess how it could affect people counting in the framework of Wi-Fi sensing. We model people with dieletric cylindrical shells with a thickness slightly higher than the electromagnetic skin depth. The electric field scattered by people is computed using the two-dimensional method of moments for electromagnetic scattering, accelerated using an iterative GMRES solver with Adaptive Cross Approximation and a block-Jacobi preconditionner. That scattered field is used to derive channel transfer functions that are combined to obtain a range-Doppler map. The presence of several ghost targets even in simple cases is highlighted, and could hinder people counting. When two people are aligned in front of the sensing-enabled Wi-Fi access point, the first blocking the line-of-sight of the second, it is shown that the field passing through the first person and reflected on the second person is sufficiently strong to detect it. We quantify the corresponding attenuation.info:eu-repo/semantics/publishe

High resolution 802.11ax-based passive radar for human movement monitoring

Passive Radars, based on the emerging 802.11ax Wi-Fi standard, are considered for indoor human movement detection. Since the Wi-Fi access points transmit multiple frames in bursts, the FFT-based Doppler estimation techniques fail due to the limited duration of the bursts. Therefore, super resolution techniques are examined for low Doppler frequency estimation based on a small number of frames. An algorithm is proposed which uses ESPRIT in an iterative fashion. The performance of the algorithm is numerically analysed, compared to theoretical bounds, and validated experimentally.info:eu-repo/semantics/publishe

Impact of Inter-body Scattering on People Counting with Wi-Fi Sensing

We investigate the interactions between human bodies exposed to an incident electric field from a sensing-enabled Wi-Fi access point, to assess how it could affect people counting in the framework of Wi-Fi sensing. We model people with dieletric cylindrical shells with a thickness slightly higher than the electromagnetic skin depth. The electric field scattered by people is computed using the two-dimensional method of moments for electromagnetic scattering, accelerated using an iterative GMRES solver with Adaptive Cross Approximation and a block-Jacobi preconditionner. That scattered field is used to derive channel transfer functions that are combined to obtain a range-Doppler map. The presence of several ghost targets even in simple cases is highlighted, and could hinder people counting. When two people are aligned in front of the sensing-enabled Wi-Fi access point, the first blocking the line-of-sight of the second, it is shown that the field passing through the first person and reflected on the second person is sufficiently strong to detect it. We quantify the corresponding attenuation