Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PhD : selection by topics

Combined analysis of kinematic, brain activity and oculometric parameters related to handwriting with supervised machine learning models for dysgraphia diagnosis tool in children

Département Systèmes

Laboratoire Signaux et Systèmes de Capteurs



Nearly a third of school-aged children fail to develop the efficient handwriting performance required to cope at school (Smits-Engelsman et al, 2001; Danna et al, 2016). Among this population, 5 to 10% of children are dysgraphic. Currently, the diagnosis of dysgraphia is based on the BHK test which is relatively subjective. Most of the time, the dysgraphia diagnosis is done lately and lead to serious consequences on children scholar achievements. It is thus crucial to diagnose and handle these deficits as early as possible. The most investigated aspects of handwriting is the motor level (Danna et al, 2013; Smits-Engelsman & Galen, 1997; Hamstra-Bletz & Blöte, 1993), but brain or oculomotor activities associated to handwriting have been poorly investigated in children. Recently, a first algorithm for automatic detection of dysgraphia has been developed (Asselborn et al, 2018), but technological improvements are required for its use in the dysgraphia diagnosis. In a previous study, an important database has been collected in typical and dysgraphic children and handwriting parameters specific to dysgraphic children have been identified and used to develop a first algorithm. Performances achieved in terms of dysgraphia diagnosis are around 85%. The current PhD position aims at analyzing the handwriting in typical and dysgraphic children by using 3 simultaneous measurements: handwriting kinematic parameters, brain activity recorded by EEG and oculomotor activity recorded by eye tracking. From these data, contribution of EEG and oculomotor features in supervised machine learning models will be assessed. The final goal is to develop a new tool, automatic and reliable, for dysgraphia diagnosis.

Design, development and evaluation of sensors based on electrical methods for detecting and quantifying airborne ultrafine particles

Département des Technologies des NanoMatériaux (LITEN)

Laboratoire de Nanocaractérisation et Nanosécurité



Research field: Air quality monitoring is a real societal challenge that leads to strong expectations from the public. Currently, there is no reliable low-cost particulate matter sensors that covers a wide range of particle size. Many optical sensors are reported but respond to particles larger than 300 nm by providing their mass concentration (PM10 and PM2.5). Only few ergonomic and accurate personal monitors allow the assessment of individual exposure to manufactured nanomaterials and ultrafine particles. This is indicative of a high potential for exploitation. Description of the research topic: We propose to develop particle microsensors offering granulometric sizing over the 5-300 nm range and the chemical composition of the collected material. The purpose of this PhD thesis is to develop, assess, theoretically and experimentally, the performances of an integrated device for the detection and the quantification of particles based on ion diffusion charging. The device is aiming to sort the particles according to their electrical mobility and to collect them selectively on a substrate according to size-resolved concentric rings. Quantitative analysis of particle charging and losses will be carried out. The electrical detection using electrometers will allow quantification in real time thanks to an appropriate signal processing algorithm. Several metrics of interest will be explored such as number-based concentration, LDSA (lung-deposited surface area) concentration and mass concentration. We propose the development of a simplified system allowing the monitoring of several channels (5-20 nm, 20-100 nm, 100-300 nm) in order to propose a solution able to determine and locate sources of ultrafine particles in real time (application to urban pollution).

Improving CO2 fixation by microalgae through a combined genetic, metabolic and process engineering approach





Improving CO2 fixation by microalgae is a challenge for the developing microalgae industry. There is great interest in this improvement, as it will significantly increase the biomass productivity of microalgae reducing the cost of cultivation and more specifically as a vector in in flue gas bioremediation. Promising candidates with increased rates of photosynthesis were obtained in a previous study. They will be screened in this PhD thesis for their increased ability to fix CO2. The best mutant(s) will be thoroughly characterized. First, a genetic approach through complementation studies will be performed. Then, the metabolites produced during photosynthesis will be determined and measured to produce a map to understand the basis of the CO2 fixation increase. And finally, these mutants will be grown in fully instrumented photobioreactors to adopt a process approach. This line of attack using diverse and complementary techniques (genetics, metabolics and process) will allow the understanding and improvement of CO2 fixation by microalgae.

Cross-layer security reinforcement of vehicular wireless communication protocols

Département Systèmes

Laboratoire Communication des Objets Intelligents



Vehicular wireless connectivity (also referred to as V2X for Vehicle to Everything) is seen today as a core enabler of future cooperative intelligent transport systems (C-ITS) (ex. highly autonomous driving, vulnerable users safety, fleet/trajectories coordination, vehicular mapping and vehicular Internet of Things?). ITS-G5, which relies on the IEEE 802.11p radio standard operating at 5.9 GHz, or C-V2X/LTE-V, which is an adaptation of 4G cellular solutions into the vehicular context (standard under definition), are two examples of relevant technologies frequently promoted in this context. However, related « open » V2X transmission modes are most often based on information broadcast (i.e., to reach the highest numbers of neighboring vehicles around) and as such, they are highly vulnerable (ex. with public control frequency channels). Accordingly, many kinds of attacks must be considered, including critical services denial (ex. through jamming, messages injection/interception, impersonations?). So far, most of the security schemes put forward in this context rely on conventional cryptographic techniques and tools (i.e., using non-specific keys, pseudonyms or signatures). On the one hand, the main security features (i.e., primitives, seeds and algorithms?), which are determined in a static way, can be over-sized in some particular vehicular use cases. On the other hand, the resulting cryptographic overhead (in terms of computational complexity and access to the core network) contribute to strongly increase the latency of protected systems, what may be not compliant with safety applications. In the frame of these PhD studies, we thus propose to define and evaluate new security mechanisms that could take benefits from different layers of the V2X protocol stack, as well as from the specificities of the vehicular application context itself (ex. « stealth » radio resource allocation, pseudo-random access and/or messages periodicity reducing the predictability of over-the-air data traffic, neighbors' trust assessment by cross-checking the consistency of exchanged application data...), while completing and reinforcing existing security schemes. A first step of these investigations with consist in conducting an in-depth risk analysis with respect to the specifications of current V2X standards. Then, some of the counter-measures proposed to mitigate most critical attacks will be validated by means of both simulations and field experimental data.

Sub-ppb detection using graphene nanomechanical resonators with optomechanical transduction

Département Composants Silicium (LETI)

Laboratoire Composants Micro-Capteurs



Combining ultimate surface-to-volume ratio, ultra-low mass and elevated Young's modulus, graphene rises as an optimal candidate for the next generation of ultra-low NEMS resonator dedicated to nano-gravimetric sensing. During this Ph.D., a prototype of a resonating graphene NEMS shall be fabricated and applied to mass sensing (being for gas or biological sensing). Current transduction techniques used for silicon NEMS are hardly adaptable to graphene resonators. Hence, the developement of these ultimate physics objects is currently hindered by lack of efficient transduction techniques. We aim, during this Ph.D. , at combining advantages offered by graphene resonator with an optomechanical transduction of its movement, so to demonstrate a sensor with the ability of sensing masses in the Dalton range or gaseous compounds concentration below the ppb limit. These resolutions are currently out-of-reach with current silicon NEMS technology

MEMS mirror for LIDAR in autonomous vehicules

Département Composants Silicium (LETI)

Labo Composants Micro-actuateurs



Optical MEMS (MOEMS) are more and more asked, in particular for the autonomous car, which has to have mapping possibilities in order to detect obstacles (like a LIDAR - "LIGHT Detection And Ranging"). It consists in scanning the environment with a laser beam and in measuring the distance between the LIDAR and the point where is reflected the laser. A micro-mirror can fill advantageously this function, assuring compactness of the system and low production cost. The goal of this thesis consists in developing a 1D and 2D micro-mirror able to scan the space following two perpendicular directions, in particular for the LIDAR application. For that purpose, first it will be necessary to study the state of the art on micro-mirrors, to understand the specifications linked to the focused application. From these specifications, the candidate will have to investigate the actuation principle (preferentially piezoelectric). After these preliminary studies, and in parallel of the experimental study of 1D micro-mirrors already developed in CEA-LETI, the candidate will have to work on the analytical modelling, and/or the Finite Element Method (FEM) simulation using COMSOL, of new 1D and 2D micro-mirror architectures. The technological realization of demonstrators will be assured by the technological platform of the CEA-LETI. The candidate will participate in the follow-up of the manufacturing and then will performed the electromechanical and optical characterizations of the devices, in order to compare them with specifications. Finally, the student will propose all the optimization and new architectures in order to improve the performances of the devices.

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