- Christine Azevedo Coste DEMAR Inria Project Team
Christine Azevedo Coste is Dr.-Ing. research scientist at INRIA/LIRMM, Montpellier, France within the DEMAR Inria project-team. Christine got her PhD and “Habilitation à Diriger les recherches” in 2002 and 2014, respectively. Christine and Jessica Rose, Professor in the department of Orthopaedic Surgery at Stanford University and director of the Motion & Gait Analysis Lab at Lucile Packard Children’s Hospital at Stanford, got awarded a collaborative research grant from the France-Stanford Center for Interdisciplinary Studies in 2015 to collaborate on the topic of « Inertial Sensors Based Analysis of Gait on Children with Spastic Cerebral Palsy ».
- Christine, what is your field of research?
I work in the field of bioengineering and more precisely neuroprosthetics in the context of functional assistance of individuals with sensory-motor deficiencies (spinal cord injuries, post-stroke hemiplegia, Parkinson disease…). My contributions mainly concern human motion analysis and neuroprostheses control for clinical applications.
- With which US team(s) do you work? For how long have you been working together? On what project are you currently working on together?
An Inria associate team, @WALK, was created in 2009 between the Inria DEMAR team and one of the robotics labs of Stanford university, the (AI Lab) led by Oussama Khatib. The scientific goals concerned artificial human walking going from biomechanical analysis of robotics optimal motion to muscle modeling and movement synthesis using simulation and active interfaces (SAI). I was not personally involved in this work. Jessica Rose was collaborating with the US team and we met in 2012 but never worked together until now. DEMAR is also working with Kenichi Yoshida at the Biomedical Engineering Department of Indiana University-Purdue University Indianapolis since 2006. The collaboration is mainly within the context of 2 successive European projects and concerns neurophysiology of invasive electrical stimulation of nerves.
- You obtained a Collaborative Research Grant from the France-Stanford Center for Interdisciplinary studies to work with the Department of Orthopaedic Surgery of Stanford University: what does it bring you?
Since 2012, Jessica Rose and myself have initiated discussions on possible collaboration. Prof. Rose has been working for many years with patients with walking disorders and more precisely on children with cerebral palsy (CP). Her research has reinforced an appreciation for the potential transformative impact of neuromuscular electrical stimulation (NMES) to improve motor deficits in cerebral palsy. I am very interested in investigating the potential application of my research on movement analysis and functional assistance with this population as I expect important outputs that may improve rehabilitation and quality of life of these children.
- What do you expect from this collaboration and what would be the next step?
Analysis of walking abnormalities is an important clinical assessment used for treatment of gait disorders in children with cerebral palsy (CP). Camera-based motion capture, the current gold standard, enables practitioners to perform gait analyses with high accuracy. However, the technology can only be used in the laboratory where motion capture is constrained to a limited space. Mobile systems are now possible using wearable sensors such as Inertial Measurement Units (IMU). These sensor-based systems have potential to provide a more efficient, mobile alternative for movement analysis and can offer real-time feedback to patients for more effective rehabilitation. Our aim is to quantitatively assess walking problems associated with CP, using wearable technology. Despite their small size, ease-of-use, robust design and low-cost, numerous recognized technical issues make the use of IMUs relatively complex. The DEMAR team has been working on these issues for some years[1] and Benoît Sijobert (PhD student) who will participate in this project has also a good experience on gait parameter extraction from a minimal number of sensors. Through a series of experiments we will combine our efforts and complementary skills to propose an IMU sensor system and software to extract meaningful gait parameters for rehabilitation of children with CP. Hopefully, the next step will be to formalize a larger project including neuroprosthetic solutions embedding the motion estimation tools developed within this preliminary collaboration.
- The call is currently open: what advice would you give to prospective applicants?
Go ahead! Do not limit possible ideas of collaboration!
