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A computerised real-time measurement system to locate the position of the urine stream in designing urine collection devices for women

A computerised real-time measurement system to locate the position of the urine stream in designing urine collection devices for women
A computerised real-time measurement system to locate the position of the urine stream in designing urine collection devices for women
Clinicians often use intuitive models based on clinical experience or regression models based on population studies to plan treatment of gait-related disorders. Because such models are constructed using data collected from previous patients, the predicted clinical outcome for a particular patient may not be reliable. We propose a new approach that uses computational models based on engineering mechanics to predict post-treatment outcome from pre-treatment movement data. The approach utilizes a four-phase optimization process built around a dynamic, patient-specific gait model. The first three phases calibrate the model's joint, inertial, and control parameters, respectively, where the control parameters are weights in an optimization cost function that tracks the patient's pre-treatment gait motion and loads. The last phase predicts the patient's post-treatment gait pattern by performing a tracking optimization with the calibrated model modified to simulate the selected treatment.

We demonstrate the approach by simulating how two treatments for knee osteoarthritis (OA) – gait modification and high tibial osteotomy (HTO) surgery – alter the external knee adduction torque for a specific patient. By performing multiple tracking optimizations, we calibrated the model's parameter values to reproduce the patient's knee adduction torque curve for a toe out gait motion. When we performed a tracking optimization with the calibrated model using a modified footpath to simulate an increased stance width, the predicted reduction in both adduction torque peaks matched experimental results to within 4.8% error. When we performed a tracking optimization with the same model using modified leg geometry to simulate HTO surgery, the predicted reductions were consistent with published data. The approach requires further evaluation with a larger number of patients to determine its effectiveness for planning the treatment of gait-related disorders on a patient-specific basis.

patient-specific, optimisation, gait, knee adduction moment, high tibial osteotomy
1350-4533
531-537
Xu, Y.
30b17987-352d-4c0e-b58b-25c03dcd223d
Macaulay, M.C.
505970d3-1e67-4c1f-8291-3a950d336c6b
Jowitt, F.A.
61a001de-c956-4234-9507-4eec9fea833e
Clarke-O'Neill, S.R.
b8a7d954-501c-4133-ad38-b300afcfb2c2
Fader, M.J.
c318f942-2ddb-462a-9183-8b678faf7277
van den Heuvel, E.A.
bae3d3a7-90ff-4297-9702-9fa3c14c8709
Cottenden, A.M.
264b07aa-fe35-4045-ab3f-e61f2cb9ebe8
Xu, Y.
30b17987-352d-4c0e-b58b-25c03dcd223d
Macaulay, M.C.
505970d3-1e67-4c1f-8291-3a950d336c6b
Jowitt, F.A.
61a001de-c956-4234-9507-4eec9fea833e
Clarke-O'Neill, S.R.
b8a7d954-501c-4133-ad38-b300afcfb2c2
Fader, M.J.
c318f942-2ddb-462a-9183-8b678faf7277
van den Heuvel, E.A.
bae3d3a7-90ff-4297-9702-9fa3c14c8709
Cottenden, A.M.
264b07aa-fe35-4045-ab3f-e61f2cb9ebe8

Xu, Y., Macaulay, M.C., Jowitt, F.A., Clarke-O'Neill, S.R., Fader, M.J., van den Heuvel, E.A. and Cottenden, A.M. (2008) A computerised real-time measurement system to locate the position of the urine stream in designing urine collection devices for women. Medical Engineering & Physics, 30 (4), 531-537. (doi:10.1016/j.medengphy.2007.05.016).

Record type: Article

Abstract

Clinicians often use intuitive models based on clinical experience or regression models based on population studies to plan treatment of gait-related disorders. Because such models are constructed using data collected from previous patients, the predicted clinical outcome for a particular patient may not be reliable. We propose a new approach that uses computational models based on engineering mechanics to predict post-treatment outcome from pre-treatment movement data. The approach utilizes a four-phase optimization process built around a dynamic, patient-specific gait model. The first three phases calibrate the model's joint, inertial, and control parameters, respectively, where the control parameters are weights in an optimization cost function that tracks the patient's pre-treatment gait motion and loads. The last phase predicts the patient's post-treatment gait pattern by performing a tracking optimization with the calibrated model modified to simulate the selected treatment.

We demonstrate the approach by simulating how two treatments for knee osteoarthritis (OA) – gait modification and high tibial osteotomy (HTO) surgery – alter the external knee adduction torque for a specific patient. By performing multiple tracking optimizations, we calibrated the model's parameter values to reproduce the patient's knee adduction torque curve for a toe out gait motion. When we performed a tracking optimization with the calibrated model using a modified footpath to simulate an increased stance width, the predicted reduction in both adduction torque peaks matched experimental results to within 4.8% error. When we performed a tracking optimization with the same model using modified leg geometry to simulate HTO surgery, the predicted reductions were consistent with published data. The approach requires further evaluation with a larger number of patients to determine its effectiveness for planning the treatment of gait-related disorders on a patient-specific basis.

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More information

e-pub ahead of print date: 20 July 2007
Published date: May 2008
Keywords: patient-specific, optimisation, gait, knee adduction moment, high tibial osteotomy

Identifiers

Local EPrints ID: 58927
URI: https://eprints.soton.ac.uk/id/eprint/58927
ISSN: 1350-4533
PURE UUID: f28f9cd2-0292-446b-94f5-89220497246b

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Date deposited: 19 Aug 2008
Last modified: 13 Mar 2019 20:31

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Contributors

Author: Y. Xu
Author: M.C. Macaulay
Author: F.A. Jowitt
Author: S.R. Clarke-O'Neill
Author: M.J. Fader
Author: E.A. van den Heuvel
Author: A.M. Cottenden

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