Multimodal BCI-Mediated FES Suppression of Pathological Tremor E. Rocon, J.A. Gallego, L. Barrios, A.R. Victoria, J. Ib´ anez, D. Farina, F. Negro, J.L. Dideriksen, S. Conforto T. D’Alessio, G. Severini, J.M. Belda-Lois, L.Z. Popovic, G Grimaldi, M. Manto, J.L. Pons Abstract— Tremor constitutes the most common movement disorder; in fact 14.5% of population between 50 to 89 years old suffers from it. Moreover, 65% of patients with upper limb tremor report disability when performing their activities of daily living (ADL). Unfortunately, 25% of patients do not respond to drugs or neurosurgery. In this regard, TREMOR project proposes functional compensation of up- per limb tremors with a soft wearable robot that applies biomechanical loads through functional electrical stimulation (FES) of muscles. This wearable robot is driven by a Brain Neural Computer Interface (BNCI). This paper presents a multimodal BCI to assess generation, transmission and exe- cution of both volitional and tremorous movements based on electroencephalography (EEG), electromyography (EMG) and inertial sensors (IMUs). These signals are combined to obtain: 1) the intention to perform a voluntary movement from cortical activity (EEG), 2) tremor onset, and an estimation of tremor frequency from muscle activation (EMG), and 3) instantaneous tremor amplitude and frequency from kinematic measurements (IMUs). Integration of this information will provide control signals to drive the FES-based wearable robot. I. I NTRODUCTION Tremor is a rhythmic oscillation of a body part, [1]. It is a disorder that is not life-threatening, but it can be responsible for functional disability and social inconvenience. Moreover, tremor is the most common movement disorder and it is strongly increasing in incidence and prevalence with ageing. More than 65% of the population with upper limb tremor presents serious difficulties in performing activities of daily living (ADL), [2]. Tremor pathogenesis involves different The work presented in this paper has been carried out with the financial support from the Commission of the European Union, within Framework 7, specific IST programme ”Accessible and Inclusive ICT”, Target outcome 7.2 ”Advanced self-adaptive ICT-enabled assistive systems based on non- invasive Brain to Computer Interaction (BCI)”, under Grant Agreement number ICT-2007-224051, ”TREMOR: An ambulatory BCI-driven tremor suppression system based on functional electrical stimulation.” J.A. Gallego, L. Barrios, E. Rocon, A.R. Victoria, J. Ib´ anez, and J.L. Pons are with the Bioengineering Group, CSIC, Madrid, Spain gallego,erocon@iai.csic.es D. Farina, F. Negro and J.L. Dideriksen are with the Center for Sensory- Motor Interaction, Faculty of Engineering, Science and Medicine Depart- ment of Health Science and Technology, Aalborg University, Aalborg, Denmark df@hst.aau.dk S. Conforto. T DAlessio and G. Severini are with the Dipartimento di Elettronica Applicata, Universit degli Studi Roma TRE, Rome, Italy conforto@uniroma3.it J.M. Belda-Lois is with Instituto de Biomec´ anica de Valencia, Valencia, Spain juanma.belda@ibv.upv.es L.Z. Popovic is with Faculty of Electrical Engineering, University of Belgrade, Serbia lanapop@etf.rs G. Grimaldi and M. Manto are with the Neurologie Department, ULB Erasme, Brussels, Belgium mmanto@ulb.ac.be E. Rocon is with Technaid S.L., Madrid, Spain info@technaid.com mechanisms at both Central and Peripheral Nervous System (CNS and PNS), [3]. Tremor is typically managed by means of drugs, surgery (thalamotomy), and deep brain stimulation, but treatments are not effective in approximately 25% of patients. Re- cently, the use of mechanical loading (by means of orthotic exoskeletons) was evaluated with successful results, both technically and clinically, as a new and alternative method for tremor suppression, [4]. The main drawback of this mechanical management of tremor is: 1) the resulting bulky solutions, 2) the inefficiency in transmitting loads from the exoskeleton to the human musculo-skeletal system and 3) technological limitations in terms of actuator technologies. The main objective of TREMOR project (ICT-2007- 224051) is to validate, technically, functionally and clinically, the concept of mechanically suppressing tremor through selective Functional Electrical Stimulation (FES) based on a (Brain Computer Interface) BCI-driven detection of invol- untary (tremor) motor activity. Tremor identification, char- acterization and tracking are compulsory if the dissipative force in a mechanical tremor suppression approach is not to load the patient’s voluntary motion. Otherwise, the user would feel a mechanical resistance to the motion, [4]. For a successful adaptive tremor absorption mechanism, a means for intelligent detection of tremor versus voluntary motion is required. As the challenge coming from the complexity of func- tional movements has not been solved yet, the possibility to combine EEG signals and other source of data to minimize perturbations (e.g. essential tremor, dyskinesia) to the desired movements is a more manageable effort. In this context, this paper proposes a multimodal BCI to assess generation, transmission and execution of both volitional and tremorous movements based on electroencephalography (EEG), elec- tromyography (EMG) and inertial sensors (IMUs). The sig- nals are combined to obtain: 1) the intention to perform a voluntary movement from cortical activity (EEG), 2) tremor onset, and an estimation of tremor frequency from muscle activation (EMG), 3) instantaneous tremor amplitude and frequency from kinematic measurements (IMUs). The integration of the information will provide control signals to drive the FES-based wearable robot. II. METHODS A platform was developed for the integration of the different system components, namely IMU, EMG and EEG sensors. This integration comprises both software and hard- ware integration. The platform is compounded by off the 32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31 - September 4, 2010 978-1-4244-4124-2/10/$25.00 ©2010 IEEE 3337