Volpe, B.T., M. Ferraro, D. Lynch, P. Christos, J. Krol, C. Trudell, H.I. Krebs and N. Hogan (2004) Robotics and Other Devices in the Treatment of Patients Recovering from Stroke. Current Atherosclerosis Reports, 6:314–319

Fasoli, S. E., Krebs, H. I., Stein, J., Frontera, W. R., Hughes, R. & Hogan, N. (2004) Robotic Therapy for Chronic Motor Impairments after Stroke: Follow-Up Results. Archives of Physical Medicine & Rehabilitation 85:1106-1111

Rohrer, B., Fasoli. F., Krebs, H.I., Volpe, B.T., Frontera, W.R., Stein, J., Hogan, N. (2004) Submovements Grow Larger, Fewer, and More Blended During Stroke Recovery. Motor Control, 2004, 8, 472-483

Krebs, H.I.; Celestino, J.; Williams, D.; Ferraro, M.; Volpe, B.T.; Hogan, N. (2004) A Wrist Extension to MIT-MANUS In Z. Zenn Bien and Dimitar Stefanov (Eds.) Advances in Human-Friendly Robotic Technologies for Movement Assistance / Movement Restoration for People with DisabilitiesSpringer-Verlag series Lecture Notes in Control and Information Sciences, Vol 306.

Fasoli, S.E., Krebs, H.I., Ferraro, M., Hogan, N., Volpe, B.T. (2004) Does shorter rehabilitation limit potential recovery post-stroke? Neurorehabilitation and Neural Repair, 18:2:88-94.

Buerger, S.P., Palazzolo, J.J., Krebs, H.I. & Hogan, N. (2004) “Rehabilitation Robotics: Adapting Robot Behavior to Suit Patient Needs and Abilities.” Proc. American Control Conference, pp.3239-3244.

Hogan, N. & Krebs. H.I. (2004) Interactive Robots for Neuro-Rehabilitation. In T. Platz (ed.) Motor System Plasticity, Recovery, and Rehabilitation Restorative Neurology and Neuroscience 20:1-10 RNN277, IOS Press

Wheeler, J.W., Krebs, H.I., Hogan, N., “An Ankle Robot for a Modular Gait Rehabilitation System,” IROS 2004, Japan, Sept. 2004.

Stein, J., Krebs, H.I., Frontera, W.R., Fasoli, S.E., Hughes, R., Hogan, N., Comparison of Two Techniques of Robot-Aided Upper Limb Exercise Training After Stroke. American Journal Physical Medicine Rehabilitation, 83:9:720-728 (2004).

Hogan, N. (2004) Muscle-like mechanical impedance aids interactive robotics. Proceedings 2nd Conference on Artificial Muscles–Biomimetic Systems Engineering, May 2004, Osaka, Japan.

Hogan, N. and Buerger, Stephen P. (2004) Impedance and Interaction Control. Chapter 19 in: Robotics and Automation Handbook, T.R.Kurfess, (ed.) CRC Press.

Bowers, T., Anquetil, P., Hunter, I. & Hogan, N. (2004) Analysis and Modeling of Electromechanical Coupling in an Electroactive Polymer-Based Actuator. Materials Research Society Symposium Proceedings, 785:127-132

Leah R. MacClellan, Douglas D. Bradham, Jill Whitall, Jill Ohlhoff, Christine Meister, Hermano I. Krebs, Neville Hogan, Bruce Volpe, and Christopher T. Bever. (2004) Robotic Upper Extremity Neuro-Rehabilitation in Chronic Stroke Patients. AAPM&R (abstract)

Krebs, H.I., Ferraro, M., Buerger, S.P., Newbery, M.J., Makiyama, A., Sandmann, M., Lynch, D., Volpe, B.T., Hogan, N. (2004) Rehabilitation Robotics: Pilot Trial of a Spatial Extension for MIT-Manus. Journal of NeuroEngineering and Rehabilitation, 1:5 Biomedcentral

References

Charles SK, Krebs HI, Volpe BT, Lynch D, Hogan N, “Wrist Rehabilitation Following Stroke: Initial Clinical Results” International Conference on Rehabilitation Robotics, June 2005 (in press)

Hoffman, D. S. and P. L. Strick (1986). “Step-tracking movements of the wrist in humans. I. Kinematic Analysis.” J Neurosci 6: 3309-3318.

Hoffman, D. S. and P. L. Strick (1990). “Step-Tracking Movements of the Wrist in Humans. II. EMG Analysis.” The Journal of Neuroscience 10(1): 142-152.

Hoffman, D. S. and P. L. Strick (1993). “Step-tracking movements of the wrist in humans. III. Influence of changes in load on patterns of muscle activity.” J Neurosci 13: 5212-5227.

Hoffman, D. S. and P. L. Strick (1999). “Step-tracking movements of the wrist. IV. Muscle activity associated with movements in different directions.” J Neurophysiol 81: 319-333.

Figure 1

Figure 2

Figure 3

As reported in [6], thirty patients with hemiplegia caused by a stroke that occurred at least 8 months prior to their initial evaluation participated in the PBPT protocol. Figure 3 demonstrates the evolution of the control parameters during early and late therapy sessions for a patient. This patient tended to move slower (tm ↑), but aim better (ksw ↓) as the early session progressed. Notice, the patient was producing quicker, better-aimed movements by the late therapy session. Although more patients need to complete the PBPT protocol to make a stronger statement, the reduction of clinical impairment measures from these patients appears to be many times greater (a factor of four to a factor of ten [6]) than the reductions from the initial protocol. Under the working hypothesis that motor recovery resembles motor learning, the initial success of the PBPT protocol provides further evidence that robotic therapy works by enhancing neural plasticity.

Bibliography

[1] S. E. Fasoli , H. I. Krebs, J. Stein, W. R. Frontera, R. Hughes, and N. Hogan, “Robotic therapy for chronic motor impairments after stroke: follow-up results,” Arch Phys Med Rehabil, vol. 85, no. 7, pp. 1106-1111, 2004.

[2] C. S. Li, C. Padoa-Schioppa, and E. Bizzi, “Neuronal correlates of motor performance and motor learning in the primary motor cortex of monkeys adapting to an external force field,” Neuron, vol. 30, no. 2, pp. 593-607, 2001.

[3] R. J. Nudo, B. M. Wise, F. Sifuentes, and G. W. Milliken, “Neural substrates for the effects of rehabilitative training on motor recovery after ischemic infarct,” Science, vol. 272, no. 5269, pp. 1791-1794, 1996.

[4] R. A. Schmidt and T. D. Lee, Motor Control and Learning: A Behavioral Emphasis, Champaign, IL: Human Kinetics, 1999.

[5] H. I. Krebs, J. J. Palazzolo, L. Dipietro, M. Ferraro, J. Krol, K. Rannekleiv, B. T. Volpe, and N. Hogan, “Rehabilitation robotics: performance-based progressive robot-assisted therapy,” Auton Robot, vol. 15, no. 1, pp. 7-20, 2003.

[6] M. Ferraro, J. J. Palazzolo, J. Krol, H. I. Krebs, N. Hogan, and B. T. Volpe, “Robot-aided sensorimotor arm training improves outcome in patients with chronic stroke,” Neurology, vol. 61, no. 11, pp. 1604-1607, 2003.

The MIT Wrist Robot, designed by Dustin Williams, [1] has demonstrated the effectiveness of robotic therapy in aiding the rehabilitation of stroke victims. In an effort to better understand the neurological processes involved in this therapy and evaluate its effectiveness a patented MRI compatible version of the wrist robot is under development so that therapy and brain imaging may be carried out simultaneously. [2]

The conceptualization, design and initial testing were conducted by Sarah Mendelowitz [3]. The MRI compatibility requirement necessitated a careful selection of materials and components. The actuation is accomplished with two standard electric motors, located outside the MRI room, which drive an MRI compatible hydraulic system, consisting of two pairs of custom designed and fabricated vane motors. These, in turn, actuate a handle grasped by the patient via a friction drive or geared differential. Initial testing has been conducted and the design is currently being modified and optimized.

Bibliography

[1] D. Williams, A Robot for Wrist Rehabilitation. MSME Thesis, Massachusetts Institute of Technology, June 2001

[2] Hogan et al. System and Method for Medical Imaging Utilizing a Robotic Device, and Robotic Device for use in Medical Imaging. United States Patent 5,794,621. August 18, 1998.

[3] S. Mendelowitz, Design of an MRI Compatible Robot for Wrist Rehabilitation. MSME Thesis, Massachusetts Institute of Technology, May 2005.

Electro-rheological fluids

ER fluids quickly vary their rheological properties in response to an imposed electric field. There are two types of ER fluids, heterogeneous and homogeneous, shown below along with a sketch of the corresponding shear stress response of each type of fluid to an increasing shear rate and electrical field.

A prototype was developed using a layered architecture with ER fluid between sheets of aluminized mylar to study, among other things, the effect of unconstrained boundary conditions and of the inter-electrode spacer material. Research showed that homogeneous ER fluid exhibits a magnitude higher energy absorption for the same power input as heterogeneous fluid. The research also showed that ER fluid was most effective when implemented without a spacer in the tested geometry. This result could be a reflection of the increased ER effect with decreasing electrode spacing or the interference of the ER effect by an intermittent dielectric layer. Ongoing research aims to address these possibilities and to explore new geometries that have the potential for higher force transmission and more efficient operation. A mathematical model was also developed that could reproduce the experimental performance of this system and support continuing device design.

Applications

The energy absorbing nature of field responsive fluids has proven useful in commercial products ranging from shock absorbers to protective garments. Each of these products relies on a combination of the energy absorption mechanism of a specific field responsive fluid and a matched “transmission geometry” to translate the change in material properties at the molecular scale into a usable macro-scale change in device properties. This project aims to understand the underlying mechanisms that affect human-scale performance and to choose the combination of fluid and transmission geometry that maximize this performance.

Electro-rheological fluids

Applications of ER fluids have historically relied on transmitting torque by shearing fluid between two or more counter-rotating disks/shells or on pushing activated ER fluid through an orifice. Mechanical clutches and dampers are classic examples of applications for ER fluids. Current ISN research puts ER fluid into flexible layers that could act like a variable stiffness fabric, absorbing vibration or impact, and supporting load.

A key consideration in this research is the particular geometry that will work best with ER fluids to provide protection for soldiers. A rigid geometry with constrained boundary conditions is impractical in a field-deployable device. ISN researchers have investigated the effect of unconstrained boundary conditions in creating the ER effect using flexible electrodes, and the effect of different inter-electrode spacers. These spacers were used to prevent contact of the electrodes that would lead to a short circuit.

A recent development in project 4.3 is the concept of using electrodes without a separate spacer but with a set of raised features on one of the electrodes designed to prevent electrode contact. These features may be patterned to enhance the ER effect by both decreasing the minimum allowable distance between the electrodes and by adding additional shear surface area. This approach in intended to be compatible with both rigid and flexible substrates. Experiments to study the effects of nanoscale electrode spacing and surface geometry are in progress.

Shear-thickening fluids

An application of shear-thickening fluid that is currently under consideration is blast lung protection. It has been shown that blast injuries result from small-amplitude, high-rate loading and acceleration of the chest cavity. A possible protective mechanism could be created using STF filled foam layered with an air-filled foam. The impedance mismatch between these foam layers and the energy absorption/dissipation properties of ST fluids may help reduce blast lung injuries by lengthening the duration of the blast pressure wave.

Velocity profiles of voluntary unconstrained human arm movements under some conditions, e.g., during accurate movements, are irregular. Specifically, the velocity profiles of the hand paths (Vt) exhibit fluctuations from the typical bell-shaped profile. What is the nature of such fluctuations? Do these fluctuations reveal anything about the nature of the controller of human arm movements?

We recorded the hand path trajectories of 4 unimpaired subjects with a low-impedance planar robot (InMotion2 Inc, Cambridge MA). Subjects performed 300 point-to-point movements at 3 different self-paced speeds (fast, comfortable, slow with peak Vt: 0.40±0.09, 0.16±0.08, 0.07±0.03 m/s, respectively) along the horizontal plane.

We found that the irregularity of Vt profiles increased as movement speed decreased. We described the Vt profiles as combinations of overlapping support-bounded lognormal discrete elementary units of movements (submovements). Figure 1 shows typical speed profiles at fast (top) comfortable (middle) and slow (bottom) speed and the correspondingsubmovement decomposition. The number of submovements increased as movement speed decreased (1.62±0.56, 2.35±0.75, 3.96±1.15 for the different speeds respectively, p<0.001). Their parameters were modulated to reconstruct theVt profiles and were similar across subjects.

We suggest the possibility that the occurrence of irregularity in Vt profiles is a by-product of the way human arm movements are generated, i.e., through submovements. Further evidence of this hypothesis is suggested by the apparent inconsistency of this experimental data with the theoretical predictions of alternative hypotheses proposed, during the past few years, to explain human arm movement irregularity.

Specifically, this data appears to be inconsistent with hypotheses that arm movements become irregular when signals generated by a time-continuous controller are degraded either by noise (Gaussian constant or signal-dependent) present in the neuromuscular system or by the mechanics of the musculoskeletal system

References

Combinations of elementary units underlying human arm movements at different speeds, L Dipietro, HI Krebs, B Volpe, N Hogan, Society for Neuroscience, Annual Meeting, 2004

Origins of irregularity in human arm movements, L Dipietro, N Hogan, HI Krebs, B Volpe, Progress in Motor Control V, 2005

Finally, by achieving and comparing these results, we can render a part of answer to the question – “what is the theoretical or mathematical definition of improvement of locomotion?” or “what is necessary to rehabilitate neurologically impaired subjects?”

Levy-Tzedek, S., Arle, J.E., Apetauerova, D., Shils, J.L., Gould, C., Krebs, H.I. (2006) Clinical score improves while motor performance deteriorates in a parkinsonian patient with deep-brain stimulation. 2006 ACRM-ASNR Joint Conference (accepted).

Apetauerova, D., Levy-Tzedek, S., Gould, C., Arle, J.E., Shils, J.L., Penney, D., Krebs, H.I. (2006) Impaired visual perception in a patient with idiopathic Parkinson’s disease with otherwise intact cognitive function. 2006 ACRM-ASNR Joint Conference (accepted).

This project has the following specific aims:

1) Test whether specific wrist robotic training improves motor performance among inpatients and persons with chronic impairment after stroke.

2) Test whether the order in which robot therapy is delivered influences outcomes among persons with chronic impairment after stroke (planar before wrist vs. wrist before planar).

3) Test whether there is any generalization of recovery gains across different joints among persons with chronic impairment after stroke.

4) Test whether there is any interference between training across different joints among persons with chronic impairment after stroke.

5) Develop a competent Internal Model using ANN not just capable of learning a novel task, but also capable of retaining this learning while learning another new task.