Optimizing the Management of Disabling Spasticity Following Spinal Cord Damage: The Ability Network-An International Initiative.

Optimizing the treatment of disabling spasticity in persons with spinal cord damage is hampered by a lack of consensus regarding the use of acceptable definitions of spasticity and disabling spasticity, and the relative absence of decision tools such as clinical guidelines and concise algorithms to support decision-making within the broader clinical community. Many people with spinal cord damage are managed outside specialist centers, and variations in practice result in unequal access to best practice despite equal need. In order to address these issues, the Ability Network-an international panel of clinical experts-was initiated to develop management algorithms to guide and standardize the assessment, treatment, and evaluation of outcomes of persons with spinal cord damage and disabling spasticity. To achieve this, consensus was sought on common definitions through facilitated, in-person meetings. To guide patient selection, an in-depth review of the available tools was performed and expert consensus sought to develop an appropriate instrument. Literature reviews are guiding the selection and development of tools to evaluate treatment outcomes (body functions, activity, participation, quality of life) as perceived by people with spinal cord damage and disabling spasticity, and their caregivers and clinicians. Using this approach, the Ability Network aims to facilitate treatment decisions that take into account the following: the impact of disabling spasticity on health status, patient preferences, treatment goals, tolerance for adverse events, and in cases of totally dependent persons, caregiver burden.

Application of higher order statistics techniques to EMG signals to characterize the motor unit action potential.

The electromyographic (EMG) signal provides information about the performance of muscles and nerves. At any instant, the shape of the muscle signal, motor unit action potential (MUAP), is constant unless there is movement of the position of the electrode or biochemical changes in the muscle due to changes in contraction level. The rate of neuron pulses, whose exact times of occurrence are random in nature, is related to the time duration and force of a muscle contraction. The EMG signal can be modeled as the output signal of a filtered impulse process where the neuron firing pulses are assumed to be the input of a system whose transfer function is the motor unit action potential. Representing the neuron pulses as a point process with random times of occurrence, the higher order statistics based system reconstruction algorithm can be applied to the EMG signal to characterize the motor unit action potential. In this paper, we report results from applying a cepstrum of bispectrum based system reconstruction algorithm to real wired-EMG (wEMG) and surface-EMG (sEMG) signals to estimate the appearance of MUAPs in the Rectus Femoris and Vastus Lateralis muscles while the muscles are at rest and in six other contraction positions. It is observed that the appearance of MUAPs estimated from any EMG (wEMG or sEMG) signal clearly shows evidence of motor unit recruitment and crosstalk, if any, due to activity in neighboring muscles. It is also found that the shape of MUAPs remains the same on loading.