Effect of FES Interventions on Gait Dynamics in Stroke Population
Effect of FES Interventions on Gait Dynamics in Stroke Population
Our proposal quantitatively analyzes gait dynamics of hemiplegic individuals in response to
 the Function Electrical Stimulation (FES) intervention and identifies the responders to the
 intervention. This study will improve our knowledge of FES intervention and help clinicians
 strategize the FES interventions more effectively based on the responders' gait
 characteristics, thus supporting the NINDS' fundamental goal of translating basic and
 clinical discoveries into better ways to prevent and treat neurological disorders.
Hemiplegia with associated foot drop occurs in 50% of the stroke survivors and frequently
 impairs an individual's ability to walk. Functional Electrical Stimulation (FES) based
 neuroprosthetic devices have been developed to correct foot drop. The efficacy of these
 devices were initially examined by Liberson el al. who demonstrated that electrical
 stimulations could assist in restoring functional movements in paralyzed limbs. In addition
 to assistance with foot drop, these devices have showed significant improvements in
 biomechanical variables such as walking speed, distance, stride length and physiological cost
 for individuals with stroke. In order to comprehensively understand the effect of electrical
 stimulations on gait recovery, it is critical to analyze the dynamic aspects of gait and
 measure gait variability during the functional electrical stimulation intervention. In the
 proposed investigation, we will determine the 'gait symmetry' of FES assisted walking using
 bilateral cyclograms of the ankle and knee over a period of 6 months. This novel approach
 will account for the dynamics and complexity of balance by measuring the deviations of joints
 from a line of symmetry at every instance of gait cycle and will provide better measure of
 gait symmetry. Utilization of this outcome measure will allow us to understand the role of
 electrical stimulation at ankle and how this effect gets translated to the knee and hip
 joints during walking. The changes in the surface electromyograms (EMGs) of selective muscle
 groups will demonstrate how FES can contribute to muscle re-training after stroke. We will
 use advanced signal processing algorithms to remove FES artifact from the EMG signal in order
 to comprehensively analyze the carry-over effect of the FES intervention. Finally, we will
 employ Principal Component Analysis (PCA) - an advanced data mining technique to track and
 quantify the overall gait recovery process of individuals with stroke using pattern
 classification algorithms. The gait symmetry measure and the EMGs will be statistically
 classified to see their clear separation at baseline and 6 month intervals. This
 classification will allow us to identify the individuals who were most responsive to the
 intervention. This information is critical and will allow researchers and clinicians to
 re-strategize the rehabilitation process. Such scientific evaluation will provide the base
 for further development and implementation of FES devices or technologies, thus supporting
 the NINDS' fundamental goal of translating basic and clinical discoveries into better ways to
 treat neurological disorders.
Inclusion Criteria:

 -  Must have sustained a stroke at least 6 months prior to study enrollment

 -  Must have hemiplegia with foot drop

 -  Must have positive response to peroneal nerve stimulation resulting in adequate
 dorsiflexion of the ankle

 -  No current usage of Functional Electrical Stimulations for the treatment of foot drop

 -  No history of injury or pathology to the unaffected limb

 -  Must be able to walk independently or with close supervision, for 25 feet without
 WalkAide or any assistive device

 Exclusion Criteria:

 -  Orthopedic pathologies or history that will interfere with ambulation or limit the
 range of motion of the lower limbs

 -  Neuromuscular pathologies or history that will interfere with neuromuscular function,
 ambulation, or limit the range of motion of the lower limbs (e.g., myasthenia gravis,
 Eaton-Lambert syndrome, amyotrophic lateral sclerosis)

 -  Neurological pathologies (e.g., multiple sclerosis)

 -  Serious lung or heart conditions that could severely limit their ability to walk

 -  Current involvement in any other study that can affect the results of this study

 -  Inability or unwillingness to comply with study procedures, follow-up requirements and
 follow instructions