The influence of central neuropathic pain in paraplegic patients on performance of a motor imagery based Brain Computer Interface.

OBJECTIVE: The aim of this study was to test how the presence of central neuropathic pain (CNP) influences the performance of a motor imagery based Brain Computer Interface (BCI). METHODS: In this electroencephalography (EEG) based study, we tested BCI classification accuracy and analysed event related desynchronisation (ERD) in 3 groups of volunteers during imagined movements of their arms and legs. The groups comprised of nine able-bodied people, ten paraplegic patients with CNP (lower abdomen and legs) and nine paraplegic patients without CNP. We tested two types of classifiers: a 3 channel bipolar montage and classifiers based on common spatial patterns (CSPs), with varying number of channels and CSPs. RESULTS: Paraplegic patients with CNP achieved higher classification accuracy and had stronger ERD than paraplegic patients with no pain for all classifier configurations. Highest 2-class classification accuracy was achieved for CSP classifier covering wider cortical area: 82±7% for patients with CNP, 82±4% for able-bodied and 78±5% for patients with no pain. CONCLUSION: Presence of CNP improves BCI classification accuracy due to stronger and more distinct ERD. SIGNIFICANCE: Results of the study show that CNP is an important confounding factor influencing the performance of motor imagery based BCI based on ERD.

Control of human spine in repetitive sagittal plane flexion and extension motion using a CPG based ANN approach.

The complexity associated with musculoskeletal modeling, simulation, and neural control of the human spine is a challenging problem in the field of biomechanics. This paper presents a novel method for simulation of a 3D trunk model under control of 48 muscle actuators. Central pattern generators (CPG) and artificial neural network (ANN) are used simultaneously to generate muscles activation patterns. The parameters of the ANN are updated based on a novel learning method used to address the kinetic redundancy due to presence of 48 muscles driving the trunk. We demonstrated the feasibility of the proposed method with numerical simulation of experiments involving rhythmic motion between upright standing and 55 degrees of flexion. The tracking performance of the model is accurate to within 2° while reciprocal muscle activation patterns were similar to the observed experimental coordination patterns in normal subjects. The suggested method can be used to map high-level control strategies to low-level control signals in complex biomechanical and biorobotic systems. This will also provide insight about underlying neural control mechanisms.

How does the central nervous system address the kinetic redundancy in the lumbar spine? Three-dimensional isometric exertions with 18 Hill-model-based muscle fascicles at the L4-L5 level.

The human motor system is organized for execution of various motor tasks in a different and flexible manner. The kinetic redundancy in the human musculoskeletal system is a significant property by which the central nervous system achieves many complementary goals. An equilibrium-based biomechanical model of isometric three-dimensional exertions of trunk muscles has been developed. Following the definition and role of the uncontrolled manifold, the kinetic redundancy concept is explored in mathematical terms. The null space of the kinetically redundant system when a certain joint moment and/or stiffness are needed is derived and discussed. The aforementioned concepts have been illustrated, using a three-dimensional three-degrees-of-freedom biomechanical model of the spine with 18 anatomically oriented Hill-type-model muscle fascicles. The considerations of stability and its consequence on the internal loading of the spine and coactivation consequences are discussed in both general and specific cases. The results can shed light on the interaction mechanisms in muscle activation patterns seen in various tasks and exertions and can provide a significant understanding for future research studies and clinical practices related to low-back disorders. Alteration of recruitment patterns in low-back-pain patients has been explained on the basis of this biomechanical analysis. The higher coactivation results in higher internal loading while providing higher joint stiffness that enhances spinal stability, which guards against spinal deformation in the presence of any perturbations.