Electrode array-based electrical stimulation using ILC with restricted input subspace

Control Engineering Practice

Volumn 23, Issue 1, 2014, Pages 32-43

  Freeman, Chris T ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Electrical stimulation; Electrode array; Experimental benchmarking; Iterative learning control; Multi variable input; Multi variable output systems

Indexed keywords

ASSISTIVE TECHNOLOGY; ELECTRICAL STIMULATIONS; ELECTRODE ARRAYS; ITERATIVE LEARNING CONTROL; MODEL IDENTIFICATION; MULTI-VARIABLE INPUT; MUSCULOSKELETAL DYNAMICS; STRUCTURAL KNOWLEDGE;

CONTROL THEORY; ELECTRICAL ENGINEERING;

TWO TERM CONTROL SYSTEMS;

EID: 84891113774     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2013.11.006     Document Type: Article

References (42)

1. Amann N., Owens D.H., Rogers E. Iterative learning control for discrete-time systems with exponential rate of convergence. IEE Proceedings - Control Theory Applications 1996, 143(23):217-224.
2. Ben-Tal A., Zibulevsky M. Penalty/barrier multiplier methods for convex programming problems. SIAM Journal of Optimization 1997, 7:347-366.
3. Boyd S., Vandenberghe L. Convex optimization 2005, Cambridge University Press.
4. Burridge J.H., Ladouceur M. Clinical and therapeutic applications of neuromuscular stimulation. A review of current use and speculation into future developments. Neuromodulation 2001, 4(4):147-154.
5. Crema A., Micera S. A novel electrode array for FES-based grasping restoration. Journal Neuroengineering and Rehabilitation 2013, 10:66.
6. d'Avella A., Saltiel P., Bizzi E. Combinations of muscle synergies in the construction of a natural motor behavior. Neuroscience 2003, 6(3):300-308.
7. Department of Health (2010). Progress in improving stroke care. National Audit Office.
8. Freeman C.T. Constrained point-to-point iterative learning control with experimental verification. Control Engineering Practice 2012, 20(5):489-498.
9. Freeman C.T., Hughes A.M., Burridge J.H., Chappell P.H., Lewin P.L., Rogers E. Iterative learning control of FES applied to the upper extremity for rehabilitation. Control Engineering Practice 2009, 17(3):368-381.
10. Freeman C.T., Rogers E., Hughes A.-M., Burridge J.H., Meadmore K.L. Electrical stimulation and robotic-assisted upper limb stroke rehabilitation. IEEE Control Systems Magazine 2012, 32(1):18-43.
11. Freeman C.T., Tan Y. Iterative learning control with mixed constraints for point-to-point tracking. IEEE Transactions on Control System Technology 2013, 21(3):604-616.
12. Guillameta D., Vitria J., Schiele B. Introducing a weighted non-negative matrix factorization for image classification. Pattern Recognition Letters 2003, 24(14):2447-2454.
13. Hatonen J.J., Harte T.J., Owens D.H. Discrete-time inverse model-based iterative learning control. Stability, monotonicity and robustness. International Journal of Systems Science 2005, 78(8):557-586.
14. Heller B.W., Clarke A.J., Good T.R., Healey T.J., Nair S., Pratt E.J. Automated setup of functional electrical stimulation for drop foot using a novel 64 channel prototype stimulator and electrode array. Results from a gait-lab based study. Medical Engineering and Physics 2013, 35(1):74-81.
15. Hendricks, H. T., van Limbeek, J., Geurts, A. C., & Zwarts, M. J. (2002). Motor recovery after stroke: A systematic review of the literature. Archives of Physical Medicine and Rehabilitation 83(11), 1629-1637.
16. Hughes A.M., Freeman C.T., Burridge J.H., Chappell P.H., Lewin P., Rogers E. Feasibility of iterative learning control mediated by functional electrical stimulation for reaching after stroke. Journal of Neurorehabilitation and Neural Repair 2009, 23(6):559-568.
17. Keller, T., Lawrence, M., Kuhn, A., & Morari, M. (2006). New multi-channel transcutaneous electrical stimulation technology for rehabilitation. In Proceedings of the 28th IEEE EMBS annual international conference (pp. 194-197). New York.
18. Kroon J.R.D., IJzerman M.J.J., Chae J., Lankhorst G.J., Zilvold G. Relation between stimulation characteristics and clinical outcome in studies using electrical stimulation to improve motor control of the upper extremity in stroke. Journal of Rehabilitation Medicine 2005, 37(2):65-74.
19. Kroon J.R.D., van der Lee J.H., Izerman M.J., Lankhorst G.J. Therapeutic electrical stimulation to improve motor control and functional abilities of the upper extremity after stroke. A systematic review. Clinical Rehabilitation 2002, 16:350-360.
20. Le F., Markovsky I., Freeman C.T., Rogers E. Identification of electrically stimulated muscle models of stroke patients. Control Engineering Practice 2010, 18(4):396-407.
21. Le F., Markovsky I., Freeman C.T., Rogers E. Recursive identification of Hammerstein systems with application to electrically stimulated muscle. Control Engineering Practice 2012, 20(4):386-396.
22. Lin T., Owens D.H., Hätönen J.J. Newton method based iterative learning control for discrete non-linear systems. International Journal of Control 2006, 79(10):1263-1276.
23. Lynch C.L., Popovic M.R. Functional electrical stimulation. Closed-loop control of induced muscle contractions. IEEE Transactions on Control System Technology 2008, (April):40-50.
24. Lyons G.M., Lane G.E., Clarke-Maloney M., O'Brien J.V., Grace P.A. An investigation of the effect of electrode size and electrode location on comfort during stimulation of the gastrocnemius muscle. Medical Engineering and Physics 2004, 26(10):873-878.
25. Malesevic N., Popovic L., Bijelic G., Kvascev G. Muscle twitch responses for shaping the multi-pad electrode for functional electrical stimulation. Journal of Automatic Control 2010, 20:53-57.
26. Meadmore K.L., Hughes A.M., Freeman C.T., Cai Z., Tong D., Burridge J.H., et al. Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke. Journal of Neuro Engineering and Rehabilitation 2012, 9(June (32)).
27. Micera S., Keller T., Lawerence M., Morari M., Popovic D.B. Wearable neural prosthesis. Restoration od sensory-motor function by transcutaneous electrical stimulation. IEEE Engineering in Medicine and Biology Magazine 2010, 64-69. (May/June).
28. O'Dwyer S.B., O'Keeffe D.T., Coote S., Lyons G.M. An electrode configuration technique using an electrode matrix arrangement for FES-based upper arm rehabilitation systems. Medical Engineering & Physics 2006, 28(2):166-176.
29. Ortega J.M., Rheinboldt W.C. Iterative solution of nonlinear equations in several variables 1970, Academic Press, London.
30. Owens D.H. Multivariable norm optimal and parameter optimal iterative learning control. A unified formulation. International Journal of Control 2012, 85(8):1010-1025.
31. Owens D.H., Freeman C.T., Dinh T.V. Norm-optimal iterative learning control with intermediate point weighting. Theory, algorithms, and experimental evaluation. IEEE Transactions on Control System Technology 2012, 21(3):999-1007.
32. Owens D.H., Hätönen J.J., Daley S. Robust monotone gradient-based discrete-time iterative learning control. International Journal of Robust and Nonlinear Control 2009, 19:634-661.
33. Popovic D.B., Popovic M.B. Automatic determination of the optimal shape of a surface electrode. Selective stimulation. Journal of Neuroscience Methods 2009, 178:174-181.
34. Popovic-Bijeli A., Bijeli G., Jorgovanovi N., Bojanic D., Popovic M.B., Popovic D.B. Multi-field surface electrode for selective electrical stimulation. Artificial Organs 2005, 29(6):448-452.
35. Rushton D.N. Functional electrical stimulation and rehabilitation - an hypothesis. Medical Engineering and Physics 2003, 25(1):75-78.
36. Schill, O., Rupp, R., Pylatiuk, C., Schulz, S., & Reischl, M., 2009. Automatic adaptation of a self-adhesive multi-electrode array for active wrist joint stabilization in tetraplegic SCI individuals. In 2009 IEEE Toronto international conference on science and technology for humanity (TIC-STH) (pp. 708-713).
37. Shin D.K., Gurdal Z., Griffin O.H.G. A penalty approach for nonlinear optimization with discrete design variables. Engineering Optimization 1990, 16:29-42.
38. Snoek G.J., IJzerman M.J., in 'tGroen F.A., Stoffers T.S., Zilvold G. Use of the NESS handmaster to restore handfunction in tetraplegia. Clinical experiences in ten patients. Spinal Cord 2000, 38:244-249.
39. Theodorou, E., Todorov, E., & Valero-Cuevas, F. J. (2011). Neuromuscular stochastic optimal control of a tendon driven index finger model. In: Proceedings of the american control conference (pp. 348-355). San Francisco, CA.
40. Tsang, W., Singh, K., & Fiume, E. (2005). Helping hand: An anatomically accurate inverse dynamics solution for unconstrained hand motion. In: Proceedings of the 2005 ACM SIGGRAPH/eurographics symposium on computer animation (pp. 319-328).
41. Turk R., Burridge J.H., Davis R., Cosendai G., Sparrow O., Roberts H.C., et al. Therapeutic effectiveness of electric stimulation of the upper-limb poststroke using implanted microstimulators. Archives of Physical Medicine and Rehabilitation 2008, (October):89.
42. Westerveld A.J., Schouten A.C., Veltink P.H., van der Kooij H. Selectivity and resolution of surface electrical stimulation for grasp and release. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2012, 20(1):94-101.