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Inverse dynamics modelling of upper-limb tremor, with cross-correlation analysis

Ketteringham, Laurence P.; Jones, Rosie J.S.; Neild, Simon A.; Davies-Smith, Angela M.; Western, David G.; Hyde, Richard A.


Laurence P. Ketteringham

Rosie J.S. Jones

Simon A. Neild

Angela M. Davies-Smith

David Western
Wallscourt Fellow in Health Technology

Richard A. Hyde


A method to characterise upper-limb tremor using inverse dynamics modelling in combination with cross-correlation analyses is presented. A 15 degree-of-freedom inverse dynamics model is used to estimate the joint torques required to produce the measured limb motion, given a set of estimated inertial properties for the body segments. The magnitudes of the estimated torques are useful when assessing patients or evaluating possible intervention methods. The cross-correlation of the estimated joint torques is proposed to gain insight into how tremor in one limb segment interacts with tremor in another. The method is demonstrated using data from a single patient presenting intention tremor because of multiple sclerosis. It is shown that the inertial properties of the body segments can be estimated with sufficient accuracy using only the patient's height and weight as a priori knowledge, which ensures the method's practicality and transferability to clinical use. By providing a more detailed, objective characterisation of patient-specific tremor properties, the method is expected to improve the selection, design and assessment of treatment options on an individual basis.

Journal Article Type Article
Publication Date Jun 1, 2014
Journal Healthcare Technology Letters
Print ISSN 2053-3713
Electronic ISSN 2053-3713
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 1
Issue 2
Pages 59-63
APA6 Citation Ketteringham, L. P., Jones, R. J., Neild, S. A., Davies-Smith, A. M., Western, D. G., & Hyde, R. A. (2014). Inverse dynamics modelling of upper-limb tremor, with cross-correlation analysis. Health Technology Letters, 1(2), 59-63.
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