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Lab website
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Manual dexterity enables a wide variety of hand functions and movements, which are controlled by a complex sensorimotor system (brain, spinal cord, peripheral nerves). The DEXTRAIN® tool evaluates manual dexterity through a standardised visuomotor task. The tool consists of 5 sensors which are connected to pistons (one for each finger), and which measure and record the forces applied. It allows the quantification of several variables such as the ability to move the fingers independently, the control of the force of each finger, the maximum force of the hand, temporal aspects such as sequences or rhythmic movements. Manual dexterity is often affected in neurological, psychiatric and musculoskeletal pathologies (e.g. stroke). This device can be coupled with the REAplan® robot which explores / rehabilitates the proximal part of the upper limb, and with other measures.
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From an ethical and legal viewpoint, it is crucial to address the tension raised by the use of prosthetics or so-called enhancement technologies: how to conciliate the individual transformation and emancipation through technologies with the collective principles of equality and merit at the core of certain social practices (e.g., Pistorius case illustrated here) ? (Christophe Lazaro)
Photo credit (Oscar Pistorius) : This work is licensed under a Creative Commons Attribution-ShareAlike 2.0 Generic License
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The emergence of complex prosthetic technologies changes our representations of the body and nurture people’s belief in the possibility to enhance human capacities beyond species normal functioning. Prosthetics and assistive technologies are then no longer conceived merely as devices for repairing or replacing the functions of a “disabled” body, but as vectors for redesigning the "normal" human body according to particular needs and desires, by modifying it or creating new capacities for action and perception and, more generally, by increasing its performance.
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Lab website
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A fundamental challenge in neuroscience consists in understanding how the brain processes sensory stimuli. A sensory stimulus applied to an individual is first transduced through dedicated receptors before being encoded with action potentials and finally conveyed toward the cortex. Artificial intelligence, including machine learning and signal processing, can be used to study the links between the activity of complex neuronal networks and the human perception of external events from different modalities (such as vision, audition, touch, ...). In particular, periodic pain-related (e.g. cool and warm) stimuli can elicit periodic responses in neuronal populations responding to the stimuli, which can be studied despite the large amount of noise in recorded brain signals.
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HABIT-ILE : Hand-arm Bimanual Intensive Therapy Including Lower Extremities
• This intervention, developed in our lab, is based on the principles of motor skill learning.
• It considers the difficulties of each child as well as their age and interests.
• By having a “child-friendly” approach, we are able to improve their motor development but also daily life activities that normally are challenging or difficult to be performed by the child.
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The test bench is driving the joint axis of the prosthesis in order to simulate gait cycles experimentally. Under controlled conditions, the device enables to characterize and to test the different versions of the prosthesis ELSA.
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ELSA is a compliant bionic ankle that can restore mobility to trans-tibial amputees.
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Vision based systems for terrain detection play important roles in mobile robotics, and recently such systems emerged for locomotion assistance of disabled people. This video shows a pilot test result of such system which has been developed by Louvain Bionics team. The system can estimate the upcoming terrains type for three steps in advance. We assigned specific color for each terrain type : ground (green points); down ramp (purple points); up ramp (red points); up stairs (blue points); downstairs (yellow points).
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In the PaDAWAn project, we are developing an assistive method to support walking in patients with Parkinson's disease. For this purpose, we use an active pelvis orthosis to assist the patients' hip flexion-extension movement. The objective would be to improve the values of some specific gait parameters, and ideally to restore them to the level of healthy walkers' values, thanks to this orthosis. If we manage to show interesting effects, this robot could be used as part of a rehabilitation therapy for patients with Parkinson's disease, or as a daily assistance for those patients.
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Contact laurence.dricot@uclouvain.be for more information
about statistical and mathematical processing, learning, administrative aspects ...
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Lab website
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Louvain Bionics was initiated by the “Fondation Louvain” and the legacy of Mr Pierre De Merre. It was recognised as an interdisciplinary research centre in 2016. It aims to bring together the expertise of researchers from UCLouvain, whose research is about 1) designing and validating medical devices, 2) improving our understanding of the interaction between the human body and this type of device, or 3) questioning these new techniques from an ethical and legal point of view.
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The REA2plan robot (AXINESIS / LOUVAIN BIONICS) can mobilize both arms of the subject individually and record their positions (kinematics). This robotic personal trainer has the ability to measure and interpret the force exchange with the subject (dynamics), which allows smooth and continuous interactions. Our serious game motor skill learning with a speed accuracy trade off (the CIRCUIT) has been implemented in the REAplan. The subjects use the robotic handle to move a cursor as fast and accurately as possible along a complex circuit displayed on the LCD monitor, completing as many laps as possible (speed) in 1 minute while keeping the cursor within the track (accuracy). The measure of the speed accuracy trade off is computed to quantify motor skill learning. High-score & reward are used to motivate the subjects.
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Data obtained from a typical grip and lift trial with the Active Touch Device. The red curve shows the grip force and the blue curve the loading force exerted by the finger in order to lift the device. In the second part of the video, the red parts of the fingertip are getting deformed and the green parts remain undeformed.
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Lab website
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The upper part of this video illustrates the movement made by a subject during an experiment (here during a task involving the right arm). Both arms are shown as well as the different targets on the screen above the subject's hands. The lower plot represents the signals of shoulder muscles activated during movement.
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Louvain Bionics
UCLouvain's hub for medical device+human research and innovation
Camille Chatelle - Research Manager
+32 10 47 22 11
camille.chatelle@uclouvain.be
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From left to right, up to down: Renaud Ronsse, Martin Edwards, Thierry Lejeune, Yannick Bleyenheuft, Christine Detrembleur, Valérie Goffaux, Olivier Collignon, Yves Vandermeeren, Christophe Lazaro, Gilles Vannuscorps, Benoît Macq, Mylène Botbol-Baum, Sylvie Nozaradan, Philippe Lefèvre, Benoît Herman, Laurence Dricot, Bruno Dehez, Frederic Crevecoeur, Valéry Legrain, André Mouraux, John Lee, Michel Verleysen, Aleksandar Jankovski, Philippe de Timary, Gaëtan Stoquart, Mark Hunyadi, Bernard Hanseeuw & Marie Van Reybroeck.
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Louvain Bionics
UCLouvain's hub for medical device+human research and innovation
Camille Chatelle - Research Manager
+32 10 47 22 11
camille.chatelle@uclouvain.be
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(a) stimulation surface of a contact thermal stimulator and time courses of cool and warm stimuli ; (b) example of periodic stimulus (red) and collected intensity ratings (blue); (c) and (d) extraction of statistically-relevant information from periodic stimuli (Mulders, D., et al. PLoS ONE 2020).
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Artificial intelligence to automate the treatment planning process in radiation oncology : towards active learning and clinical decision support system.
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