Biomechanical assessment of head and neck movements in neck pain using 3D movement analysis

Three-dimensional movement analysis was used to evaluate head and neck movement in patients with neck pain and matched controls. The aims were to further develop biomechanical models of head and neck kinematics, to investigate differences between subjects with non-specific neck pain and whiplash associated disorders (WAD), and to evaluate the potential of objective movement analysis as a decision support during diagnosis and follow-up of patients with neck pain. Fast, repetitive head movements (flexion, extension, rotation to the side) were studied in a group of 59 subjects with WAD and 56 controls. A back propagation artificial neural network classified vectors of collected movement variables from each individual according to group membership with a predictivity of 89%. The helical axis for head movement were analyzed in two groups of neck pain patients (21 with non-specific neck pain and 22 with WAD) and 24 matched controls. A moving time window with a cut-off angle of 4° was used to calculate finite helical axes. The centre of rotation of the finite axes (CR) was derived as the 3D intersection point of the finite axes. A downward migration of the axis during flexion/extension and a change of axis direction towards the end of the movements were observed. CR was at its most superior position during side rotations and at its most inferior during ball catching. This could relate to that side rotation was mainly done in the upper spine, while all cervical vertebrae were recruited to stabilize the head in the more complex catching task. Changes in movement strategy were observed in the neck pain groups: Neck pain subjects had lower mean velocities and ranges of movements as compared with controls during ball catching, which could relate to a stiffer body position in neck pain patients in order to stabilize the neck. In addition, the WAD group had a displaced axis position during head repositioning after flexion, while CR was displaced during fast side rotations in the non-specific neck pain group. Pain intensity correlated with axis and CR position, and may be one reason for the movement strategy changes. Increased amount of irregularities in the trajectory of the axis was found in the WAD group during head repositioning, fast repetitive head movements and catching. This together with an increased constant repositioning error during repositioning after flexion indicated motor control disturbances. A higher group standard deviation in neck pain groups indicated heterogeneity among subjects in this disturbance. Wireless motion sensors and electro-oculography was used simultaneously, as an initial step towards a portable system and towards a method to quantify head-eye co-ordination deficits in individuals with WAD. Twenty asymptomatic control subjects and six WAD subjects with eye disturbances (e.g. dizziness and double vision) were studied. The trial-to-trial repeatability was moderate to high for all evaluated variables (single intraclass correlation coefficients >0.4 in 28 of 32 variables). The WAD subjects demonstrated decreased head velocity, decreased range of head movement during gaze fixation and lowered head stability during head-eye co-ordination as possible deficits. In conclusion, kinematical analyses have a potential to be used as a support for physicians and physiotherapists for diagnosis and follow-up of neck pain patients. Specifically, the helical axis method gives information about how the movement is performed. However, a flexible motion capture system (for example based on wireless motion sensors) is needed. Combined analysis of several variables is preferable, as patients with different neck pain disorders seem to be a heterogeneous group