Seminar Details
2021-11-02 (14h) : Welcome Seminar
At Euler building (room a.002)
Organized by Mathematical Engineering
Section 1: Using photogrammetry for the objective study of ancient bowed instruments: a machine learning approach
Speaker :
Beghin, Philémon
Abstract :
The morphology of today’s violin differs greatly from that of the first instruments of the late 16th century. Indeed, in order to meet the standards suggested by famous orchestras and conservatories, many ancient violins have been recut. It is important for musicologists, violin makers and museum curators to analyse the alterations they have undergone. Specialists agree that the instruments have been reshaped, but have difficulty to prove it rigorously. Moreover, the historical testimonies about this process are imprecise. It is therefore necessary to find an objective way to quantify violin geometry. This project aims to develop a set of algorithmic tools in order to compute an adequate mathematical representation that is able to describe the 3D shape of an object (violin) acquired by photogrammetry. Based on that representation, machine learning techniques will be applied in order to perform clustering and classification with the aim of quantifying their geometric characteristics, their possible anomalies and, if applicable, their original morphology. From an engineering point of view, the development of 3D analyses of objects as complex as violins will allow the growth of methods and knowledge potentially applicable to many fields outside of organology.
Section 2: Biomechanics of tactile feedback during dexterous manipulation of objects
Speaker :
Doumont, Donatien
Abstract :
The biomechanics of the skin and underlying tissues play a fundamental role in the sense of touch. Indeed, when the finger comes in contact with an object, the deformations induced within these living tissues are translated by the mechanoreceptors (or tactile sensors) into neural signals, which are then interpreted by the brain to generate the appropriate motor response. This project is aimed at better understanding the feedback provided by the tactile afferents during interactions with objects. To that end, we will combine passive stimulation tasks mimicking the mechanical interactions during object manipulation and active manipulation tasks while monitoring the activity of tactile afferents (only in the passive case) and several key biomechanical parameters such as external forces, surface skin deformation, and skin moisture. This combination of techniques will enable us to gain insight into the essential aspects of tactile feedback that enable stable and dexterous control of fingertip forces during manipulation. Such insight will have direct implications for the development of sensorized bionic hands.
Section 3: Simulation of the stride-to-stride variability of patients with Parkinson’s disease
Speaker :
Vandamme, Clémence
Abstract :
Gait is a complex mechanism involving several neural structures such as the motor cortex, the cerebellum and basal ganglia. It also requires the integration of sensorial feedback from visual, vestibular and peripheral receptors. The complex coordination of these structures is not yet fully understood. In particular, recent studies revealed that gait fluctuations exhibit Long Range Autocorrelation (LRA) such that fluctuations at any given moment are statistically related to those that occur over many different time scales. Up to now, the physiological origin of LRA remains unclear. Moreover, this specific correlation structure is altered in elderly and in people suffering from neurodegenerative diseases, such as Parkinson’s disease. Consequently, it is thought that an optimal level of LRA is a marker of stable gait and high adaptive capabilities. Clinically, LRA indicators could complement the diagnostic of Parkinson's disease and constitutes a precautious marker of risk of fall. This project aims to provide a comprehensive model that includes a continuous-time control of the biomechanics plant for both a healthy population and Parkinson’s patients, as it is an important challenge for fundamental understanding as well as for clinical applications.
Section 4: Influence of vestibular, visual and somesthesic inputs on dexterous manipulation
Speaker :
Vandergooten, Simon
Abstract :
Since birth we evolve in a steady gravitational environment in which our brain has learned to manipulate objects. For example, we are able to unconsciously optimize the force with which we squeeze objects when handling them. In order to better characterize the influence of gravity on upper limb movement kinematics as well as on the dynamics of prehension (i.e. the act of grasping), several parabolic flight campaigns as well as ground-based experiments were performed. These experiments ultimately led to GRIP, an experiment carried out in the International Space Station that focuses on long-term motor adaptation to microgravity, in particular during dexterous object manipulation. On the ground, our current setup comprising a rotating chair, four motion-tracking cameras and the grip-lift manipulandum allows us to perform control experiments that are necessary for the interpretation of and analysis of GRIP data. With this project, we aim to study how visual, vestibular and somatosensory feedbacks interact and affect the planning of movement trajectory, the perception of the verticality and the anticipative force mechanisms underlying finger-arm coordination.