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Technical Brief

Dynamic Weighted Bar for Upper Limb Rehabilitation

[+] Author and Article Information
Taylor C. Hornung

Department of Mechanical Engineering,
The Pennsylvania State University,
University Park, PA 16802
e-mail: tch5085@psu.edu

Stephen J. Piazza

Department of Kinesiology,
The Pennsylvania State University,
University Park, PA 16802
e-mail: piazza@psu.edu

Everett C. Hills

Department of Physical Medicine and Rehabilitation,
The Pennsylvania State University,
Hershey, PA 17033
e-mail: ech14@psu.edu

Jason Z. Moore

Department of Mechanical Engineering,
The Pennsylvania State University,
University Park, PA 16802
e-mail: jzm14@psu.edu

Manuscript received October 5, 2015; final manuscript received March 6, 2016; published online August 5, 2016. Assoc. Editor: Venketesh Dubey.

J. Med. Devices 10(4), 044503 (Aug 05, 2016) (4 pages) Paper No: MED-15-1271; doi: 10.1115/1.4033451 History: Received October 05, 2015; Revised March 06, 2016

This paper explores the design of a dynamically weighted therapy bar, which can provide real-time quantitative performance information and adjustments during rehabilitation exercise. In contrast, typical therapy equipment is passive, offering no feedback to the patient or clinician. The dynamic weighted bar (DWB) was designed and fabricated containing an inertial sensor which tracks the orientation of the bar and adjusts the position of an internal weight accordingly, in turn providing a targeted force imbalance between the patient's two arms. Step input experiments were performed on the device while it was held in various stationary positions. The DWB was able to successfully function and transmit motion information. It was able to produce a center of mass shift of 101.6 mm, and a complete travel time between 0.96 s and 1.41 s over the entire length. The use of the DWB device can offer many benefits during rehabilitation including access to more quantitative information for clinicians as well as the potential for more personalized therapy programs.

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References

Go, A. S. , Mozaffarian, D. , Roger, V. L. , Benjamin, E. J. , Berry, J. D. , Blaha, M. J. , Dai, S. F. , Ford, E. S. , Fox, C. S. , Franco, S. , Fullerton, H. J. , Gillespie, C. , Hailpern, S. M. , Heit, J. A. , Howard, V. J. , Huffman, M. D. , Judd, S. E. , Kissela, B. M. , Kittner, S. J. , Lackland, D. T. , Lichtman, J. H. , Lisabeth, L. D. , Mackey, R. H. , Magid, D. J. , Marcus, G. M. , Marelli, A. , Matchar, D. B. , McGuire, D. K. , Mohler, E. R. , Moy, C. S. , Mussolino, M. E. , Neumar, R. W. , Nichol, G. , Pandey, D. K. , Paynter, N. P. , Reeves, M. J. , Sorlie, P. D. , Stein, J. , Towfighi, A. , Turan, T. N. , Virani, S. S. , Wong, N. D. , Woo, D. , Turner, M. B. , Comm, A. H. A. S. , and Subcomm, S. S. , 2014, “ Heart Disease and Stroke Statistics-2014 Update a Report From the American Heart Association,” Circulation, 129(3), pp. E28–E292. [CrossRef] [PubMed]
Bonita, R. , and Beaglehole, R. , 1988, “ Recovery of Motor Function After Stroke,” Stroke, 19(12), pp. 1497–1500. [CrossRef] [PubMed]
Khan, L. , Zygman, M. , Rymer, W. , and Reinkensmeyer, D. , 2006, “ Robot-Assisted Reaching Exercise Promotes Arm Movement Recovery in Chronic Hemiparetic Stroke: A Randomised Controlled Pilot Study 6,” J. NeuroEng. Rehabil., 3(2), pp. 1–13. [PubMed]
Lum, P. S. , Taub, E. , Schwandt, D. , Postman, M. , Hardin, P. , and Uswatte, G. , 2004, “ Automated Constraint-Induced Therapy Extension (AutoCITE) for Movement Deficits After Stroke,” J. Rehabil. Res. Dev., 41(3), pp. 249–258. [CrossRef] [PubMed]
Sanchez, R. J. , Liu, J. , Rao, S. , Shah, P. , Smith, R. , Rahman, T. , Cramer, S. C. , Bobrow, J. E. , and Reinkensmeyer, D. J. , 2006, “ Automating Arm Movement Training Following Severe Stroke: Functional Exercises With Quantitative Feedback in a Gravity-Reduced Environment,” IEEE Trans. Neural Syst. Rehabil. Eng., 14(3), pp. 378–389. [CrossRef] [PubMed]
Burgar, C. G. , Lum, P. S. , Shor, P. C. , and Van der Loos, H. F. M. , 2000, “ Development of Robots for Rehabilitation Therapy: The Palo Alto VA/Stanford Experience,” J. Rehabil. Res. Dev., 37(6), pp. 663–673. [PubMed]
Mataric, M. J. , Eriksson, J. , Feil-Seifer, D. J. , and Winstein, C. J. , 2007, “ Socially Assistive Robotics for Post-Stroke Rehabilitation,” J. NeuroEng. Rehabil., 4(1), p. 5.
Prange, G. B. , Jannink, M. J. A. , Groothuis-Oudshoorn, C. G. M. , Hermens, H. J. , and IJzerman, M. J. , 2006, “ Systematic Review of the Effect of Robot-Aided Therapy on Recovery of the Hemiparetic Arm After Stroke,” J. Rehabil. Res. Dev., 43(2), pp. 171–183. [CrossRef] [PubMed]
Reinkensmeyer, D. J. , Hogan, N. , Krebs, H. I. , Lehman, S. L. , Lum, P. S. , and Newman, D. J. , 2000, “ Rehabilitators, Robots, and Guides: New Tools for Neurological Rehabilitation,” Biomechanics and Neural Control of Posture and Movement, Springer, New York, pp. 516–534.
Colombo, R. , Pisano, F. , Micera, S. , Mazzone, A. , Delconte, C. , Carrozza, M. C. , Dario, P. , and Minuco, G. , 2005, “ Robotic Techniques for Upper Limb Evaluation and Rehabilitation of Stroke Patients,” IEEE Trans. Neural Syst. Rehabil., 13(3), pp. 311–324. [CrossRef]
Volpe, B. T. , Krebs, H. I. , Hogan, N. , Edelstein, L. , Diels, C. , and Aisen, M. , 2000, “ A Novel Approach to Stroke Rehabilitation—Robot-Aided Sensorimotor Stimulation,” Neurology, 54(10), pp. 1938–1944. [CrossRef] [PubMed]
Charnnarong, J. , Hogan, N. , Krebs, H. I. , and Sharon, A. , 1995, “ Interactive Robotic Therapist,” U.S. Patent No. 5,466,213.
Reinkensmeyer, D. J. , Dewald, J. P. , and Rymer, W. Z. , 1999, “ Guidance-Based Quantification of Arm Impairment Following Brain Injury: A Pilot Study,” IEEE Trans. Rehabil. Eng., 7(1), pp. 1–11. [CrossRef] [PubMed]
Lum, P. S. , Burgar, C. G. , Shor, P. C. , Majmundar, M. , and Van der Loos, M. , 2002, “ Robot-Assisted Movement Training Compared With Conventional Therapy Techniques for the Rehabilitation of Upper-Limb Motor Function After Stroke,” Arch. Phys. Med. Rehabil., 83(7), pp. 952–959. [CrossRef] [PubMed]
Riener, R. , Nef, T. , and Colombo, G. , 2005, “ Robot-Aided Neurorehabilitation of the Upper Extremities,” Med. Biol. Eng. Comput., 43(1), pp. 2–10. [CrossRef] [PubMed]
Fitzgerald, G. K. , Axe, M. J. , and Snyder-Mackler, L. , 2000, “ The Efficacy of Perturbation Training in Nonoperative Anterior Cruciate Ligament Rehabilitation Programs for Physically Active Individuals,” Phys. Ther., 80(2), pp. 128–140. [PubMed]

Figures

Grahic Jump Location
Fig. 2

Diagram of controls endcap for DWB

Grahic Jump Location
Fig. 3

Mapping (left) and diagram (right) of bar angle to target weight position for CG knob = 0.6, weight high mode (top), and weight low mode (bottom)

Grahic Jump Location
Fig. 4

DWB clinician interface

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Fig. 5

DWB experiment fixture

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Fig. 6

Step input response of DWB for various bar pitch angles

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Fig. 7

Rise time of weight position based on pitch angle

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