Bart Jansen is a professor at the medical imaging and ehealth group of the department of Electronics and Informatics (ETRO) at the Vrije Universiteit Brussel. He is interested in developing image and signal processing methods and artificial intelligence methods for a variety of applications in the broad biomedical engineering domain, but mainly focussing on rehabilitation engineering.
Rehabilitation engineering is a term with many different definitions. Some consider it to be a rather broad domain focussing on assessing and responding to the needs of people with disabilities, others (like the EMBS) define it as creating methods and technologies to help patients regain cognitive and/or motor function.
I am driven by the observation that in physical and cognitive rehabilitation there are several important aspects that could improve the rehabilitation process for the patients in a crucial manner.
One of those is the poor quantification of treatment effect: a fine grained monitoring of patients (e.g. suffering from neurodegenerative or other conditions) does not exist. Hence, evolution of for instance motor skills are poorly quantified and the effects of treatment options on these are largely unquantified at an individual basis. This is not surprising, as such an analysis requires specialised tools and examinations as for instance functional assessment at a gait lab. Such assessment is not available nor feasible or desirable on a very frequent basis for a large group of people. Rather, more frequent or even continuous assessment, easily accessible or even ubiquitous, could provide a through quantification of the cognitive and motor functions of the subject. This would allow for a detailed quantification (and later on understanding) of the impact of various rehabilitation schemes. In this domain, we mainly focus on the development of tools and methods for physical assessment by means of low-cost mass market sensor devices, including the Wii balance board, the Microsoft Kinect and others. Besides improving the quality of care and the efficiency of the rehabilitation process, our tools also provide digital biomarkers for pharmaceutical studies focusing on various interventions on subjects with disabilities of movement disorders.
A second issue with current rehabilitation practices is the suboptimal compliance and adherence to optimal rehabilitation exercise doses. Rehabilitation is a slow process requiring a lot of repetitions and practising. Weekly, or even daily, one-on-one sessions with a rehabilitation specialist are hence often not sufficient, driving the prescription of for instance home-based exercises. However, a vast minority of subjects comply to these, as they are perceived as being difficult, painful, boring or even useless. Game-based rehabilitation concerns the use of computer games to present, assess and steer the rehabilitation exercises and might actually improve adherence and compliance. However, whereas real-life therapists excell in adapting therapeutic interventions to the needs of every individual subjects, computer games are fit-for-all and rigid. We investigate the development and use of a flexible and adaptive game based rehabilitation platform.
Neuro Evolution concerns the use of genetic algorithms to evolve neural networks. As this is an optimization approach which is not using gradient information, it is a slow and computationally intensive search process. However, the powerful search strategies provided by contemporary genetic algorithms allows for the joint optimization of network topology and network weights (e.g. NEAT). Our research focuses on integrating feature selection as a third component in this joint optimization process and has resulted in the development of FD-NEAT, a successor of NEAT performing feature selection, network topology optimization and weight optimization.
Although seriously hyped, the adoption of augmented reality beyond gadgets is rather poor. Both improvements in terms of hardware (glasses) as well as applications are needed. In this domain, we focus on developing niche applications for instance in medical and look into visualisation of medical image data and object recognition.
Prof. Dr. Bart Jansen
Vrije Universiteit Brussel (VUB)
Department of Electronics and Informatics (ETRO)
Pleinlaan 2 B-1050 - Brussel - Belgium
Room Pleinlaan 9, 1st floor, room 1.59
Tel: +32 (2) 629 10 34
E-mail: bjansen at etrovub dot be
|||Association Between Immunosenescence Phenotypes and Pre-frailty in Older Subjects: Does Cytomegalovirus Play a Role?. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 74(4):480-488, Oxford University Press, 2019.|
|||Validation of the Wii Balance Board to assess balance modifications induced by increased respiratory loads in healthy subjects. Gait and Posture, 68:449-452, Elsevier, 2019.|
|||Augmenting Microsoft's HoloLens with vuforia tracking for neuronavigation. Healthcare Technology Letters, 5(5):221-225, Institution of Engineering and Technology, 2018.|
|||Evaluation of data balancing techniques. Application to CAD of lung nodules using the LUNA16 framework. Revista de Ingeniería Electrónica, Automática y Comunicaciones, 39(3):57-67, 2018.|
|||The end of active video games and the consequences for rehabilitation. Physiotherapy Research International., 23(4), John Wiley and Sons Ltd, 2018.|
|||Effect of cognitive task on static balance in patients with pulmonary fibrosis: Conference Abstract: Belgian Brain Congress 2018 — Belgian Brain Council. Frontiers in Neuroscience, Frontiers Media S.A., 2018.|
|||Evaluation of appendicular lean mass using bio impedance in persons aged 80+: A new equation based on the BUTTERFLY-study. Clinical Nutrition, Churchill Livingstone, 2018., (Copyright \circledC 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.).|
|||The Use of Mobile Games to Assess Cognitive Function of Elderly with and without Cognitive Impairment.. Journal of Alzheimer's Disease, 64(4):1285-1293, IOS Press, 2018.|
|||3D Analysis of Upper Limbs Motion during Rehabilitation Exercises Using the KinectTM Sensor: Development, Laboratory Validation and Clinical Application. Sensors, 18(7), Multidisciplinary Digital Publishing Institute (MDPI), 2018.|
|||Fast and robust Fourier domain-based classification for on-chip lens-free flow cytometry. Optics Express, 26(11):14329-14339, The Optical Society, 2018.|
|||The use of mobile games to refine the diagnosis of dementia: Conference Abstract: Belgian Brain Congress 2018 — Belgian Brain Council. Frontiers in Neuroscience, Frontiers Media S.A., 2018.|