Upper-limb kinematic reconstruction during stroke robot-aided therapy
- 586 Downloads
The paper proposes a novel method for an accurate and unobtrusive reconstruction of the upper-limb kinematics of stroke patients during robot-aided rehabilitation tasks with end-effector machines. The method is based on a robust analytic procedure for inverse kinematics that simply uses, in addition to hand pose data provided by the robot, upper arm acceleration measurements for computing a constraint on elbow position; it is exploited for task space augmentation. The proposed method can enable in-depth comprehension of planning strategy of stroke patients in the joint space and, consequently, allow developing therapies tailored for their residual motor capabilities. The experimental validation has a twofold purpose: (1) a comparative analysis with an optoelectronic motion capturing system is used to assess the method capability to reconstruct joint motion; (2) the application of the method to healthy and stroke subjects during circle-drawing tasks with InMotion2 robot is used to evaluate its efficacy in discriminating stroke from healthy behavior. The experimental results have shown that arm angles are reconstructed with a RMSE of 8.3 × 10−3 rad. Moreover, the comparison between healthy and stroke subjects has revealed different features in the joint space in terms of mean values and standard deviations, which also allow assessing inter- and intra-subject variability. The findings of this study contribute to the investigation of motor performance in the joint space and Cartesian space of stroke patients undergoing robot-aided therapy, thus allowing: (1) evaluating the outcomes of the therapeutic approach, (2) re-planning the robotic treatment based on patient needs, and (3) understanding pathology-related motor strategies.
KeywordsUpper-limb kinematics Rehabilitation robotics Stroke rehabilitation
This work was partly supported by the European project H2020/AIDE (CUP J42I15000030006) and the Italian project Industria2015/DAHMS (CUP B85E10003020008).
- 6.Colombo R, Sterpi I, Mazzone A, Pisano F, Delconte C (2011) Modeling upper limb clinical scales by robot-measured performance parameters. In: IEEE international conference on rehabilitation robotics (ICORR) (pp 1–5)Google Scholar
- 7.Denavit J, Hartenberg SH (1955) A kinematic notation for lower-pair mechanisms based on matrices. ASME J Appl Mech 22:215–221Google Scholar
- 11.Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S (1975) The post stroke hemiplegic patient. A method for evaluation of physical performance. Scand J Rehabil Med 7:1331Google Scholar
- 13.Guglielmelli E, Johnson MJ, Shibata T (2009) Guest editorial special issue on rehabilitation robotics. IEEE TRO 25:477–480Google Scholar
- 17.Li Z, Kim H, Milutinovi D, Rosen J (2013) Synthesizing redundancy resolution criteria of the human arm posture in reaching movements. In: Milutinovi D, Rosen J (eds) Redundancy in robot manipulators and multi-robot systems. Springer, Berlin, pp 201–240Google Scholar
- 19.Medendorp WP, Crawford JD, Henriques DYP, Van Gisbergen JAM, Gielen CCAM (2000) Kinematic strategies for upper arm-forearm coordination in three dimensions. J Neurophys 84:2302–2316Google Scholar
- 23.OBrien MD (1986) Aids to the examination of the peripheral nervous system (3rd edn). London. Bailliere TindallGoogle Scholar
- 24.Papaleo E, Zollo L, Sterzi S, Guglielmelli E (2012) An inverse kinematics algorithm for upper-limb joint reconstruction during robot-aided motor therapy. In: BIOROB-IEEE/RAS-EMBS international conference on biomedical robotics and biomechatronics (pp 1983–1988)Google Scholar
- 29.Sciavicco L, Villani L (2009) Robotics: modelling, planning and control. Springer, BerlinGoogle Scholar