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Chronic whiplash associated disorders and neck movement measurements: an instantaneous helical axis approach.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.ORCID iD: 0000-0003-3363-7414
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
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2003 (English)In: IEEE transactions on information technology in biomedicine, ISSN 1089-7771, E-ISSN 1558-0032, Vol. 7, no 4, 274-282 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents an assessment tool for objective neck movement analysis of subjects suffering from chronic whiplash-associated disorders (WAD). Three-dimensional (3-D) motion data is collected by a commercially available motion analysis system. Head rotation, defined in this paper as the rotation angle around the instantaneous helical axis (IHA), is used for extracting a number of variables (e.g., angular velocity and range, symmetry of motion). Statistically significant differences were found between controls and subjects with chronic WAD in a number of variables.

Place, publisher, year, edition, pages
2003. Vol. 7, no 4, 274-282 p.
URN: urn:nbn:se:umu:diva-22045PubMedID: 15000354OAI: diva2:212468
Available from: 2009-04-22 Created: 2009-04-22 Last updated: 2015-11-30
In thesis
1. Biomechanical assessment of head and neck movements in neck pain using 3D movement analysis
Open this publication in new window or tab >>Biomechanical assessment of head and neck movements in neck pain using 3D movement analysis
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Umeå: Strålningsvetenskaper, 2008. 85 p.
Umeå University medical dissertations, ISSN 0346-6612 ; 1160
movement analysis, kinematics, helical axis, neck pain, whiplash, cervical spine, pattern classification, motor control, head-eye co-ordination, head movement
National Category
Medical and Health Sciences
Research subject
Biomedical Radiation Science
urn:nbn:se:umu:diva-1600 (URN)978-91-7264-518-9 (ISBN)
Public defence
2008-04-18, Hörsal B, Umeå Universitetssjukhus, NUS, UMEÅ, 09:00 (English)
Available from: 2008-03-31 Created: 2008-03-31 Last updated: 2011-11-21Bibliographically approved
2. Biomechanical methods and error analysis related to chronic musculoskeletal pain
Open this publication in new window or tab >>Biomechanical methods and error analysis related to chronic musculoskeletal pain
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background Spinal pain is one of humanity’s most frequent complaints with high costs for the individual and society, and is commonly related to spinal disorders. There are many origins behind these disorders e.g., trauma, disc hernia or of other organic origins. However, for many of the disorders, the origin is not known. Thus, more knowledge is needed about how pain affects the neck and neural function in pain affected regions. The purpose of this dissertation was to improve the medical examination of patients suffering from chronic whiplash-associated disorders or other pain related neck-disorders.

Methods A new assessment tool for objective movement analysis was developed. In addition, basic aspects of proprioceptive information transmission, which can be of relevance for muscular tension and pain, are investigated by studying the coding of populations of different types of sensory afferents by using a new spike sorting method. Both experiments in animal models and humans were studied to accomplish the goals of this dissertation. Four cats where were studied in acute animal experiments. Mixed ensembles of afferents were recorded from L7-S1 dorsal root filaments when mechanical stimulating the innervated muscle. A real-time spike sorting method was developed to sort units in a multi-unit recording. The quantification of population coding was performed using a method based on principal component analysis. In the human studies, 3D neck movement data were collected from 59 subjects with whiplash-associated disorders (WAD) and 56 control subjects. Neck movement patterns were identified by processing movement data into parameters describing the rotation of the head for each subject. Classification of neck movement patterns was performed using a neural network using processed collected data as input. Finally, the effect of marker position error on the estimated rotation of the head was evaluated by computer simulations.

Results Animal experiments showed that mixed ensembles of different types of afferents discriminated better between different muscle stimuli than ensembles of single types of these afferents. All kinds of ensembles showed an increase in discriminative ability with increased ensemble size. It is hypothesized that the main reason for the greater discriminative ability might be the variation in sensitivity tuning among the individual afferents of the mixed ensemble will be larger than that for ensembles of only one type of afferent. In the human studies, the neural networks had a predictivity of 0.89, a sensitivity of 0.90 and a specificity of 0.88 when discriminating between control and WAD subjects. Also, a systematic error along the radial axis of the rigid body added to a single marker had no affect on the estimated rotation of the head.

Conclusion The developed spike sorting method, using neural networks, was suitable for sorting a multiunit recording into single units when performing neurophysiological experiments. Also, it was shown that neck movement analysis combined with a neural network could build the basis of a decision support system for classifying suspected WAD or other pain related neck-disorders.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2009. 110 p.
Umeå University medical dissertations, ISSN 0346-6612 ; 1240
cervical spine, ensemble theory, error analysis, helical axis, kinematics, movement analysis, neural coding, pattern recognition, spike sorting, whiplash
National Category
Biomedical Laboratory Science/Technology
urn:nbn:se:umu:diva-18470 (URN)978-91-7264-717-6 (ISBN)
Institutionen för strålningsvetenskaper, 90185, Umeå
Public defence
2009-02-27, Sal 260, Röntgens föreläsningssal, by 3A, Norrlands universitetssjukhus, Umeå, 13:00 (Swedish)
Available from: 2009-02-10 Created: 2009-02-10 Last updated: 2015-11-30Bibliographically approved

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Öhberg, FredrikGrip, HelenaWiklund, Urban
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