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Select Highlights of Significant Contributions to Science, Engineering, and Technology


Quadriceps and Hamstrings Muscle Control in Athletic Males and Females. (2008)

Female athletes are 4-6 times more likely to sustain major knee joint injuries as compared to their male counterparts. Experts have long believed that the female predisposition to these injuries is related to the way in which they control their thigh muscles. While there were several research works to support neuromuscular differences during sport-related activity, it was not clear whether the differences observed were more related to their inherent control differences or were compensatory strategies employed to prevent perturbations faced during sport events. This was primarily due to the lack of neuromuscular evaluation tools to separate fundamental vs. compensatory strategies. This information is critical because it has meaningful implications on training strategies employed to prevent sport-related serious knee injuries. Dr. Krishnan used an elegant approach to study the basic thigh muscle neural control/recruitment strategies employed by males and females using a novel target-matching experiment that ensured to separate the basic strategies from compensatory or reactive strategies. Dr. Krishnan’s work provides the best evidence to date that there are fundamental differences in voluntary muscle control in males and females that may impact injury risk. Moreover, the results suggest that females may need to be trained differently than males, which is generally not the case at this time.


Torque-based Triggering Improves Stimulus Timing Precision in Activation Tests. (2009)

Knee strength testing is routinely performed to determine efficacy and effectiveness of a treatment, to develop criteria for patient progression, and to document clinical course of the patient. The ability to produce maximum muscle force is severely compromised in patients with orthopedic and neurological disorders. A major factor that contributes to this weakness is related to the patient’s inability to drive his/her muscles maximally during strength testing, which is termed as voluntary activation deficits. A common approach to study activation deficits involves superimposition of a strong electrical stimulus during maximal muscle contractions. The superimposed stimulus will generate additional force if the patient suffers from voluntary activation deficits. On the contrary, the electrical stimulus will not elicit any additional force if the subject is generating maximal muscle force.

Electrical stimuli during activation tests are conventionally delivered by one of two methods: 1) manually by visually inspecting the force curve and triggering the stimulator at the point perceived to be peak force or 2) automatically at a set time-point following the onset of volitional muscle contraction. It is rare, however, for the stimulus to be delivered at a time when the subject is producing peak force with these approaches, which is critical for precise test results. Hence, significant measurement error is introduced to the estimation of voluntary activation. Dr. Krishnan invented a novel triggering algorithm that substantially (by about 75%) reduced the measurement error during activation testing. This is a major invention as it would substantially improve the quality of current standards of voluntary activation testing in patients with knee disorders. This technique is now widely used in several laboratories in the country and worldwide.


Modeling nonlinear errors in surface electromyography due to baseline noise: a new methodology (2011)

Surface electromyography (EMG) is a noninvasive technique for evaluating and recording the electrical activity produced by 
Full Textthe muscles during contractions. This technique is heavily used in both clinical and research settings to study the behavior of skeletal muscles during human movements. The surface EMG signal is often contaminated by some degree of baseline noise (i.e., electrical signals that are not directly due to muscle activity). It is customary for clinicians and scientists to subtract baseline noise from the measured EMG signal prior to further analyses. However, this method is inappropriate when the magnitude of noise is high. This work provides a new method to account for baseline noise using mathematical modeling. This new error correction method provides a superior approach to accounting for baseline noise when assessing EMG burst amplitudes. 


Corticospinal tract integrity correlates with knee extensor weakness in chronic stroke survivors. (2011)

Approximately 795,000 people have a stroke each year in the United States, imposing an enormous economic (>$50 billion annual healthcare cost) and social burden. Stroke is the leading cause for long-term adult disability in the United States and worldwide. Muscle weakness develops rapidly after stroke, adversely affecting motor performance, and contributing to reduced functional ability. It is not clear why some patients suffer from substantial muscle weakness even years after the initial incidence of stroke whereas others recover completely. This information will be very valuable to clinicians as it will help in the early detection of people who may *not* respond to conventional therapy and may require additional aggressive therapy after stroke. The novelty of this study lies on the fact that it is the first study to establish the relationship between neural pathway integrity, measured using both radiological and electrophysiological techniques, and post-stroke muscle weakness. This research work provides a valuable measurement tool that can help to reliably predict who may suffer from long-term muscle weakness after stroke, which will substantial improve the quality of patient care in the United States and elsewhere. 


Corticospinal responses of quadriceps are abnormally coupled with hip adductors in chronic stroke survivors (2012)

The ability to control and coordinate muscle actions in a fine manner is critical for smooth performance of everyday activities such as walking, climbing stairs, etc. Stroke survivors often lose their ability to move their joints independently in a controlled fashion, which results in abnormal movement patterns that are detrimental to balance and stability. As a result, stroke survivors are severely incapacitated in carrying out many of their daily activities independently. An understanding of the mechanisms that mediate loss of independent joint control is a key to establish successful treatment programs. This study used a novel noninvasive brain stimulation technique to help identify the changes happening at the brain level that may promote abnormal movement patterns after stroke. The results of this study provide new insights into the mechanisms underlying loss of independent joint control after stroke and have meaningful implications for post-stroke rehabilitation interventions.


Active Robotic Training Improves Locomotor Function in a Chronic Stroke Survivor (2012)

Gait (walking) impairment is one of the primary causes of disability after stroke with about 75% of stroke survivors living with some form of walking-related disability. Gait disruption not only creates a stigma for these patients, but also puts them at risk for fall related injuries and significantly impacts their quality of life. Unfortunately, even with best standard of care, current therapeutic interventions have minimal influence on the natural path of gait recovery after stroke. One reason for the non-optimal outcome after stroke is related to inadequate amount of therapy provided to these patients. It is currently not feasible for therapists to provide extended amount of gait therapy as this form of therapy places substantial physical burden on the therapists involved in the training processes. Moreover, the cost of such therapy will be exorbitant thereby placing substantial economic burden on the patients and their family. Robot-aided gait therapy is potentially a promising approach to restore motor function after stroke as the dosage of therapy can be increased several folds without major physical burden on the therapists or economic burden on the patients. However, for the robots to be successful it should possess the skills of a trained therapist. In this paper, Dr. Krishnan describes a novel gait training paradigm for individuals with stroke. This training paradigm combines two unique and novel features: (1) advanced control algorithms that allow the robot to be tuned specifically to behave like therapists and (2) a target-tracking task that facilitates active involvement of the patients in the training process. They also report the remarkable effectiveness of this paradigm on walking function of a chronic stroke survivor.


Extracting Synergies in Gait: Using EMG Variability to Evaluate Control Strategies. (2012)

The human body consists of substantially more number of muscles than the available degrees of freedom for movement. The 
problem of how the nervous system coordinates the numerous degrees of freedom of the body has been a long-standing issue in motor control (i.e., muscle control). One hypothesis is that the nervous system simplifies control by functionally linking multiple muscles to act as if they were a single-unit. Scientists have long studied this hypothesis by using complex mathematical analyses of the electromyograhic activity of various muscles when performing activities such as walking or reaching. A key criticism for this analysis is that the algorithms are not sophisticated enough to detect whether the control strategies revealed through this analysis reflect true motor control strategies or simply reflect coincidental firing of two or more muscles together because of the constraint induced by the task. In this paper, Ranganathan and Krishnan used a novel mathematical simulation technique to demonstrate that the existing techniques are not capable of distinguishing true motor control from coincidental firing due to task constraint. They also provide a novel approach to evaluate neural control strategies that demonstrated substantial superiority than the existing methods. 


Pilot Study on the Feasibility of Robot-Aided Leg Motor Training to Facilitate Active Participation. (2013)

Robot-aided gait therapy offers a promising approach towards improving gait function in individuals with neurological disorders such as stroke or spinal cord injury. However, as highlighted before (in paper 6) incorporation of appropriate control strategies is essential for actively engaging the patient in the therapeutic process. Although several control algorithms (such as assist-as-needed and error augmentation) have been proposed to improve active patient participation, we hypothesize that the therapeutic benefits of these control algorithms can be greatly enhanced if combined with a motor learning task to facilitate neural reorganization and motor recovery. In this paper, we described a novel active robotic training approach using the Lokomat and pilot-tested whether this approach can enhance active patient participation during training. The findings from this study provide a proof-of-concept demonstration for the first time that combining robotic gait training with a motor learning task enhances active participation.