Training modalities in robot-mediated upper limb rehabilitation in stroke : A framework for classification based on a systematic review

© 2014 Basteris et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The work described in this manuscript was partially funded by the European project ‘SCRIPT’ Grant agreement no: 288698 (http://scriptproject.eu). SN has been hosted at University of Hertfordshire in a short-term scientific mission funded by the COST Action TD1006 European Network on Robotics for NeuroRehabilitationRobot-mediated post-stroke therapy for the upper-extremity dates back to the 1990s. Since then, a number of robotic devices have become commercially available. There is clear evidence that robotic interventions improve upper limb motor scores and strength, but these improvements are often not transferred to performance of activities of daily living. We wish to better understand why. Our systematic review of 74 papers focuses on the targeted stage of recovery, the part of the limb trained, the different modalities used, and the effectiveness of each. The review shows that most of the studies so far focus on training of the proximal arm for chronic stroke patients. About the training modalities, studies typically refer to active, active-assisted and passive interaction. Robot-therapy in active assisted mode was associated with consistent improvements in arm function. More specifically, the use of HRI features stressing active contribution by the patient, such as EMG-modulated forces or a pushing force in combination with spring-damper guidance, may be beneficial.Our work also highlights that current literature frequently lacks information regarding the mechanism about the physical human-robot interaction (HRI). It is often unclear how the different modalities are implemented by different research groups (using different robots and platforms). In order to have a better and more reliable evidence of usefulness for these technologies, it is recommended that the HRI is better described and documented so that work of various teams can be considered in the same group and categories, allowing to infer for more suitable approaches. We propose a framework for categorisation of HRI modalities and features that will allow comparing their therapeutic benefits.Peer reviewedFinal Published versio

Feasibility of a second iteration wrist and hand supported training system for self-administered training at home in chronic stroke

Telerehabilitation allows continued rehabilitation at home after discharge. The use of rehabilitation technology supporting wrist and hand movements within a motivational gaming environment could enable patients to train independently and ultimately serve as a way to increase the dosage of practice. This has been previously examined in the European SCRIPT project using a first prototype, showing potential feasibility, although several usability issues needed further attention. The current study examined feasibility and clinical changes of a second iteration training system, involving an updated wrist and hand supporting orthosis and larger variety of games with respect to the first iteration. Nine chronic stroke patients with impaired arm and hand function were recruited to use the training system at home for six weeks. Evaluation of feasibility and arm and hand function were assessed before and after training. Median weekly training duration was 113 minutes. Participants accepted the six weeks of training (median Intrinsic Motivation Inventory = 4.4 points and median System Usability Scale = 73%). After training, significant improvements were found for the Fugl Meyer assessment, Action Research Arm Test and self-perceived amount of arm and hand use in daily life. These findings indicate that technology-supported arm and hand training can be a promising tool for self-administered practice at home after stroke.Final Accepted Versio

Quantifying and correcting for speed and stride frequency effects on running mechanics in fatiguing outdoor running

Measuring impact-related quantities in running is of interest to improve the running technique. Many quantities are typically measured in a controlled laboratory setting, even though most runners run in uncontrolled outdoor environments. While monitoring running mechanics in an uncontrolled environment, a decrease in speed or stride frequency can mask fatigue-related changes in running mechanics. Hence, this study aimed to quantify and correct the subject-specific effects of running speed and stride frequency on changes in impact-related running mechanics during a fatiguing outdoor run. Seven runners ran a competitive marathon while peak tibial acceleration and knee angles were measured with inertial measurement units. Running speed was measured through sports watches. Median values over segments of 25 strides throughout the marathon were computed and used to create subject-specific multiple linear regression models. These models predicted peak tibial acceleration, knee angles at initial contact, and maximum stance phase knee flexion based on running speed and stride frequency. Data were corrected for individual speed and stride frequency effects during the marathon. The speed and stride frequency corrected and uncorrected data were divided into ten stages to investigate the effect of marathon stage on mechanical quantities. This study showed that running speed and stride frequency explained, on average, 20%–30% of the variance in peak tibial acceleration, knee angles at initial contact, and maximum stance phase knee angles while running in an uncontrolled setting. Regression coefficients for speed and stride frequency varied strongly between subjects. Speed and stride frequency corrected peak tibial acceleration, and maximum stance phase knee flexion increased throughout the marathon. At the same time, uncorrected maximum stance phase knee angles showed no significant differences between marathon stages due to a decrease in running speed. Hence, subject-specific effects of changes in speed and stride frequency influence the interpretation of running mechanics and are relevant when monitoring, or comparing the gait pattern between runs in uncontrolled environments

Assessment and visualisation of daily-life arm movements after stroke

For an optimal guidance of the rehabilitation therapy of stroke patients in an in-home setting, objective, and patient specific assessment of upper extremity task performance is needed. Towards this goal, metrics of hand position relative to the pelvis were estimated and visualized. Metrics, including work area and maximum reaching distance, appeared to strongly correlate with the upper extremity part of the Fugl-Meyer Assessment scale (r>0.84, p<0.001). Proposed metrics and visualisation can be used to objectively assess the arm movement performance over a longer period of time in a daily-life setting, if combined with info about performed task derived from a activity monitor

Pressure Insoles for Gait and Balance Estimation

Stroke leads to impairment in motor ability, gait, and balance, due to brain tissue damage [1]. Clinical therapy following stroke aims at improving mobility and functional capacity. However, there is lack of objective information about subject’s performance once they are transferred home [2]. A wearable, unobtrusive system is needed to describe and compare clinical capacity and performance in a home setting. ForceShoes™ (Xsens Technologies B.V., The Netherlands) had been developed to provide holistic information about subject’s gait and balance measures, such as Extrapolated Centre of Mass (XCoM) and Dynamic Stability Margin (DSM) [3], [4]. Using these measures, a clear distinction between the capacity and performance of the subject is seen. However, this system is obtrusive and requires a long time to set up. This project addresses the need for a wearable and minimal sensing system with an unobtrusive set up. Pressure insoles are lightweight and inconspicuous, and when coupled with an Inertial Measurement Unit (IMU), several gait and balance measures can be estimated. In this study, a 1-D pressure insole system (medilogic ® insoles, T&T medilogic Medizintechnik GmbH, Germany), coupled with IMUs, is investigated for objective quantification of gait and dynamic balance measures. Although, to obtain such measures, 3D forces and moments are required. Linear regression models were used to model 3D forces/moments from the 1D plantar pressures measured from pressure insoles. The predicted forces and moments were used for estimation of XCoM and DSM. These parameters were compared with the estimations done by the forces and moments from the Force Shoes™. The regression model is tested for different walking speeds. High correlation and low differences between the estimations from predicted and measured values show that pressure insoles can indeed be used as an wearable alternative. The results will also be used in designing a wearable in-shoe system that can be used in daily life monitoring for stroke subjects. The study is a part of project 7 of NeuroCIMT, funded by the Dutch National foundation STW. REFERENCES [1] S. F. Tyson, M. Hanley, J. Chillala, A. Selley, and R. C. Tallis, “Balance disability after stroke.,” Phys. Ther., vol. 86, no. 1, pp. 30–38, 2006. [2] B. Klaassen, B.-J. F. van Beijnum, M. Weusthof, D. Hof, F. B. van Meulen, Ed Droog, H. Luinge, L. Slot, A. Tognetti, F. Lorussi, R. Paradiso, J. Held, A. Luft, J. Reenalda, C. Nikamp, J. H. Buurke, H. J. Hermens, and P. H. Veltink, “A Full Body Sensing System for Monitoring Stroke Patients in a Home Environment,” Commun. Comput. Inf. Sci., vol. 511, pp. 378–393, 2016. [3] F. B. van Meulen, D. Weenk, E. H. F. van Asseldonk, H. M. Schepers, P. H. Veltink, and J. H. Buurke, “Analysis of Balance during Functional Walking in Stroke Survivors,” PLoS One, vol. 11, no. 11, p. e0166789, Nov. 2016. [4] F. B. van Meulen, D. Weenk, J. H. Buurke, B.-J. F. van Beijnum, and P. H. Veltink, “Ambulatory assessment of walking balance after stroke using instrumented shoes,” J. Neuroeng. Rehabil., vol. 13, no. 1, p. 48, 2016. [5] A. L. Hof, M. G. J. Gazendam, and W. E. Sinke, “The condition for dynamic stability,” J. Biomech., vol. 38, no. 1, pp. 1–8, 2005