Skip to main content

Research Repository

Advanced Search

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.

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


Laurence P. Ketteringham

Rosie J.S. Jones

Simon A. Neild

Angela M. Davies-Smith

Profile Image

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.


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.

Journal Article Type Article
Acceptance Date Apr 16, 2014
Online Publication Date May 27, 2014
Publication Date Jun 1, 2014
Deposit Date Jun 5, 2019
Publicly Available Date Jun 5, 2019
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
Public URL
Publisher URL


You might also like

Downloadable Citations