Browsing by Author "Balasubramanian, Sivakumar"
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Item Improving the match between ability and challenge: Toward a framework for automatic level adaptation in game-based assessment and training(2013) Perry, Joel C.; Balasubramanian, Sivakumar; Rodriguez-De-Pablo, Cristina; Keller, Thierry; Tecnalia Research & InnovationIt is believed that the quality of arm mobility in planar reach movements can be adequately characterized by measures of planar position and vertical force. For the purpose of impairment assessment, it is further proposed that a complete picture of mobility performance can be represented through the assessment of metrics representative of each of four capacities: 1) Range of motion, 2) Range of force, 3) Control of motion, and 4) Control of force. In this paper, a set of games for mobility assessment is presented and initial plots of motion profiles and several computed metrics are shown for one patient in the performance of range of motion and control of motion assessments. Assessment plots are shown for four of seven training sessions and metrics are computed at each of the seven sessions to show the progression over the course of the 2-week clinical pilot study with the ArmAssist.Item Is EMG a Viable Alternative to BCI for Detecting Movement Intention in Severe Stroke?(2018-12) Balasubramanian, Sivakumar; Garcia-Cossio, Eliana; Birbaumer, Niels; Burdet, Etienne; Ramos-Murguialday, Ander; Medical TechnologiesObjective: In light of the shortcomings of current restorative brain-computer interfaces (BCI), this study investigated the possibility of using EMG to detect hand/wrist extension movement intention to trigger robot-assisted training in individuals without residual movements. Methods: We compared movement intention detection using an EMG detector with a sensorimotor rhythm based EEG-BCI using only ipsilesional activity. This was carried out on data of 30 severely affected chronic stroke patients from a randomized control trial using an EEG-BCI for robot-assisted training. Results: The results indicate the feasibility of using EMG to detect movement intention in this severely handicapped population; probability of detecting EMG when patients attempted to move was higher (p < 0.001) than at rest. Interestingly, 22 out of 30 (or 73%) patients had sufficiently strong EMG in their finger/wrist extensors. Furthermore, in patients with detectable EMG, there was poor agreement between the EEG and EMG intent detectors, which indicates that these modalities may detect different processes. Conclusion : A substantial segment of severely affected stroke patients may benefit from EMG-based assisted therapy. When compared to EEG, a surface EMG interface requires less preparation time, which is easier to don/doff, and is more compact in size. Significance: This study shows that a large proportion of severely affected stroke patients have residual EMG, which yields a direct and practical way to trigger robot-assisted training.Item Serious games for assessment and training in post-stroke robotic upper-limb telerehabilitation(INSTICC Press, 2014) Rodríguez-De-Pablo, Cristina; Perry, Joel C.; Balasubramanian, Sivakumar; Belloso, Aitor; Saviç, Andrej; Tomiç, Tijana Dimkiç; Keller, Thierry; Londral, Ana Rita; Encarnacao, Pedro; Tecnalia Research & InnovationResearch shows that better results in post-stroke rehabilitation are obtained when patients receive more intensive therapy. However, the increasing affected population and the limited healthcare resources prevent the provision of intense rehabilitation care. Thus, there is a need for a more autonomous and scalable care provision methods that can be transferred out of the clinic and into home environments. Serious games in combination with robotic rehabilitation can provide an affordable, engaging, and effective way to intensify treatment, both at the clinic and at home. Furthermore, they can offer quantitative assessment of motor performance, allowing individualized treatments and to keep the patient and their therapists informed about therapy progress. Towards this end, a set of games for assessment and training of upper-limb motor impairment after stroke with the ArmAssist is presented. A special effort has been made to design the assessment games in order to be able, not only to measure the effectiveness of the training, but also to compare the assessment results with the standard assessment scales used in the clinic. Feedback from usability testing of previous versions of the system has also been crucial for the final design. Preliminary results of an ongoing clinical testing are presented.Item Validating ArmAssist Assessment as outcome measure in upper-limb post-stroke telerehabilitation(Institute of Electrical and Electronics Engineers Inc., 2015-11-04) Rodriguez-De-Pablo, Cristina; Balasubramanian, Sivakumar; Savic, Andrej; Tomic, Tijana D.; Konstantinovic, Ljubica; Keller, Thierry; Tecnalia Research & InnovationThe ArmAssist is a low-cost robotic system for post-stroke upper-limb telerehabilitation based on serious games. The system incorporates a set of games for the assessment of arm function, the ArmAssist Assessment (AAA), which allows a remote monitoring of the progress of the patient and an automatic adaptation of the therapy. In this study, different components of the AAA are compared against three widely-used clinical tests, the Fugl-Meyer Assessment (FMA) [1], the Action Research Arm Test (ARAT) [2] and the Wolf Motor Function Test (WMFT) [3] in order to select the most clinically meaningful ones for the final score provided to patients and therapist, and evaluate their capability to predict or even improve some aspects of these standard scales. All four tests were performed in 38 separate sessions in 19 post-stroke individuals in their sub-acute phase, as part of a broader study. Statistically significant correlation could be shown with the three clinical tests. These preliminary results are promising for the validation of AAA as a fast, automatic and clinically meaningful tool for remote progress assessment and therapy adaptation; however, more data and further analysis is needed to confirm this.