Identifying offline muscle strength profiles sufficient for short-duration FES-LCE exercise: A PAC learning model approach

Journal of Clinical Monitoring and Computing

Volumn 20, Issue 3, 2006, Pages 209-220

  Trumbower, Randy D ^a   Rajasekaran, Sanguthevar ^b   Faghri, Pouran D ^b,c  

^a NORTHWESTERN UNIVERSITY   (United States)

^b Material and Biomolecular Engineering   (United States)

^c UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

FES LCE; PAC learning; SCI; Statistical models

Indexed keywords

FUNCTIONAL ELECTRICAL STIMULATION (FES); LEG CYCLE ERGOMETRY (LCE); LINEAR DISCRIMINANT ANALYSIS (LDA); MUSCLE STRENGTH; PROBABLY APPROXIMATELY CORRECT (PAC);

BIOMECHANICS; EXERCISE EQUIPMENT; MATHEMATICAL MODELS; NEURAL NETWORKS; STATISTICAL METHODS;

MUSCLE;

ACCURACY; ADULT; AGE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BICYCLE ERGOMETER; BODY HEIGHT; BODY WEIGHT; CLASSIFICATION; CLINICAL ARTICLE; CONTROLLED STUDY; DISCRIMINANT ANALYSIS; DYNAMIC EXERCISE; ELECTROSTIMULATION; FATIGUE; HUMAN; INTERMETHOD COMPARISON; LEARNING; LEG MUSCLE; LOGISTIC REGRESSION ANALYSIS; MALE; MUSCLE EXERCISE; MUSCLE FUNCTION; MUSCLE STRENGTH; MUSCLE TRAINING; MUSCULOSKELETAL SYSTEM PARAMETERS; NORMAL HUMAN; ONLINE ANALYSIS; POSITION; PREDICTION; PRIORITY JOURNAL; PROCESS DEVELOPMENT; SPINAL CORD INJURY; STATIC EXERCISE; STATISTICAL ANALYSIS; THEORETICAL STUDY; TORQUE; VALIDATION PROCESS;

ADULT; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DIAGNOSIS, COMPUTER-ASSISTED; ELECTRIC STIMULATION THERAPY; EXERCISE TEST; EXERCISE THERAPY; EXERTION; HUMANS; MALE; MODELS, BIOLOGICAL; MUSCLE CONTRACTION; MUSCLE, SKELETAL; PHYSICAL EXERTION; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; THERAPY, COMPUTER-ASSISTED;

EID: 33745948322     PISSN: 13871307     EISSN: 15732614     Source Type: Journal    
DOI: 10.1007/s10877-006-9023-2     Document Type: Article

References (48)

1. Faghri PD, Glaser RM, Figoni SF. Functional electrical stimulation leg cycle ergometer exercise: Training effects on cardiorespiratory responses of spinal cord injured subjects at rest and during submaximal exercise. Arch Phys Med Rehabil 1992; 73: 1085-1093.
2. Glaser RM. Functional neuromuscular stimulation. Exercise conditioning of spinal cord injured patients. Int J Sports Med 1994; 15: 142-148.
3. Petrofsky J. Bicycle ergometer for paralyzed muscles. Journal of Clinical Engineering 1984; 9: 13-19.
4. Petrofsky J, Stacy. The effect of training on endurance and the cardiovascular responses of individuals with paraplegia during dynamic exercise induced by functional electrical stimulation. European Journal of Applied Physiology 1992; 64: 487-492.
5. Faghri P, Glaser R. Feasibility of using two FES exercise modes for spinal cord injured patients. Clinical Kinesiology 1989; 44.
6. Hooker SP, Figoni SF, Glaser RM, Rodgers MM, Ezenwa BN, Faghri PD. Physiologic responses to prolonged electrically stimulated leg-cycle exercise in the spinal cord injured. Arch Phys Med Rehabil 1990; 71: 863-869.
7. Leeds EM, Klose KJ, Ganz W, Serafini A, Green BA. Bone mineral density after bicycle ergometry training. Arch Phys Med Rehabil 1990; 71: 207-209.
8. Ragnarrson K, Pollack S, O'Daniel W, Edgar R, Petrofsky J, Nash M. Clinical evaluation of computerized functional electrical stimulation after spinal cord injury: A multicenter pilot study. Arch Phys Med Rehabililitation 1988; 69: 672-677.
9. Figoni SF. Perspectives on cardiovascular fitness and SCI. J Am Paraplegia Soc 1990; 13: 63-71.
10. Gurney AB, Robergs RA, Aisenbrey J, Cordova JC, McClanahan L. Detraining from total body exercise ergometry in individuals with spinal cord injury. Spinal Cord 1998; 36: 782-789.
11. Franco JC, Perell KL, Gregor RJ, Scremin AM. Knee kinetics during functional electrical stimulation induced cycling in subjects with spinal cord injury: A preliminary study. J Rehabil Res Dev 1999; 36: 207-216.
12. Gerrits HL, de Haan A, Sargeant AJ, Dallmeijer A, Hopman MT. Altered contractile properties of the quadriceps muscle in people with spinal cord injury following functional electrical stimulated cycle training. Spinal Cord 2000; 38: 214-223.
13. Vestergaard P, Krogh K, Rejnmark L, Mosekilde L. Fracture rates and risk factors for fractures in patients with spinal cord injury. Spinal Cord 1998; 36: 790-796.
14. Schutte L, Rodgers M, Zajac F, Glaser R. Improving the efficacy of electrical-stimulation induced leg cycle ergometry, in Mechanical Engineering, Stanford University, Palo Alto CA 1993.
15. Trumbower RD, Faghri PD. Crank torque profile of leg muscles at different stimulation intensities and pedal crank positions on a recumbent leg cycle ergometer. Presented at ACRM Conference 2005.
16. Figoni SF, Rodgers MM, Glaser RM, Hooker SP, Faghri PD, Ezenwa BN, Mathews T, Suryaprasad AG, Gupta SC. Physiologic responses of paraplegics and quadriplegics to passive and active leg cycle ergometry. J Am Paraplegia Soc 1990; 13:33-39.
17. Figoni S, Rodgers M, Glaser R, Hooker S, Faghri P, Ezenwa B, Mathews T, Suryaprasad A, Gupta S. Physiologic responses of paraplegics and quadriplegics to passive and active leg cycle ergometry. J Am Paraplegia Soc 1990; 13: 33-39.
18. Gfohler M, Lugner P. Cycling by means of functional electrical stimulation. IEEE Trans Rehabil Eng 2000; 8: 233-243.
19. Myers R. Classical and modern regression with applicaitons, 2nd edition, Duxbury Press, Belmont 1990.
20. Haykin S. Neural networks, 2nd Edition 1999.
21. Fisher R. The use of multiple measurements in taxonomic problems. Ann Eugen 1936; 10: 422-429.
22. Fukunaga K. Introduction to Statistical Pattern Recognition. Academic Press, San Diego 1990.
23. Valiant L. A theory of the learnable. Communications of the ACM 1984; 17: 1134-1142.
24. Angluin D, Smith C. Inductive inference: Theory and methods. Computing Surveys 1983; 15: 237-269.
25. Center NSCIS. The 2004 annual statistical report for the model spinal cord injury care systems. University of Alabama at Birmingham, Birmingham 2004.
26. Winter D. Biomechanics and Motor Control of Human Movement, 2nd edition, John Wiley & Sons, Inc, New York, 1990.
27. Trumbower R, Faghri P. FES-induced pedal force generation of individual leg muscles during a single crank rotation in persons with SCI, Spinal Cord, Submitted.
28. Faghri PD, Trumbower RD. Short-duration FES-induced leg cycling dynamics at different stimulation intensities and flywheel resistances, presented at IFESS 2005, Montreal, Canada 2005.
29. Thorstensson A, Karlsson J. Fatiguability and fiber composition of human skeletal muscle. Acta Physio Scand 1976; 98: 318-322.
30. Vandewalle H, Peres G, Monod H. Standard anaerobic exercise tests. Sports Med 1987; 4: 268-289.
31. Burnham R, Martin T, Stein R, Bell G, MacLean I, Steadward R. Skeletal muscle fibre type transformation following spinal cord injury. Spinal Cord 1997; 35: 86-91.
32. McCartney N, Obminski G, Heigenhauser GJ. Torque-velocity relationship in isokinetic cycling exercise. J Appl Physiol 1985; 58: 1459-1462.
33. Siff M. Biomechanical foundations of strength and power training, in V. Zatsiorsky (ed.), Biomechanics in sport, Blackwell Scientific Ltd., London 2000, pp. 103-139.
34. Triantaphyllou E, Soyster A, Kumara S. Generating logical expressions from positive and negative examples via a branch-and-bound approach. Computers Ops Res 1994; 21: 185-197.
35. Sanchez S, Triantaphyllou E, Chen J, Liao T. An incremental learning algorithm for constructing Boolean functions from positive and negative examples. Computers & Operations Research 2002; 29: 1677-1700.
36. Deshpande A, Triantaphyllou E. A greedy randomized adaptive search procedure (GRASP) for inferring logical clauses from exmples in polynomial time and some extensions. Mathematical and Computer Modelling 1998; 27: 75-99.
37. Dreiseitl S, Ohno-Machado L. Logistic regression and artificial neural network classification models: A methodology review. J Biomed Inform 2002; 35: 352-359.
38. Subasi A, Ercelebi E. Classification of EEG signals using neural network and logistic regression. Comput. Methods Programs Biomed 2005; 78: 87-99.
39. Rumelhart D, McClelland J. Parallel Distributed Processing: Eexplorations in the Microstructure of Cognition. Vol. 1, MIT Press, Cambridge 1986.
40. Kearns M, Vazirani U. An Introduction to Computational Learning Theory. MIT Press 1994.
41. Crago PE, Peckham PH, Thrope GB. Modulation of muscle force by recruitment during intramuscular stimulation. IEEE Trans Biomed. Eng 1980; 27: 679-684.
42. Johnson R, Wichern D. Applied Multivariate Statistical Analysis, 4th edition. Prentice-Hall, Saddle River 1998.
43. Windows SF. SPSS 12.0 for Windows, Release 12.0.0 ed. SPSS, Inc Chicago 2003.
44. Cristianini N, Shawe-Taylor J. An introduction to Support Vector Machines and other Kernel-Based Learning Methods. University Press, Cambridge 2000.
45. Dasarathy B. Nearest Neighbor Pattern Classification Techniques. IEEE Computer Society Press, Silver Spring 1991.
46. Breiman L, Friedman J, Olshen R, Stone C. Classification and Regression Trees. Chapman & Hall, New York 1984.
47. Trumbower RD, Faghri PD. Relationship between isometric pedal force generation and stimulation intensity of individual leg muscles involved in FES-induced leg cycling. Presented at IFESS 2005, Montreal, Canada 2005.
48. Hosmer D, Lemeshow S. Applied logistic regression, 2nd ed. Wiley, New York, 2000.