• Aucun résultat trouvé

Quantitative rigidity evaluation during deep brain stimulation surgery - a preliminary study

N/A
N/A
Protected

Academic year: 2021

Partager "Quantitative rigidity evaluation during deep brain stimulation surgery - a preliminary study"

Copied!
3
0
0

Texte intégral

(1)

HAL Id: hal-01871549

https://hal.uca.fr/hal-01871549

Submitted on 26 Nov 2018

HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Quantitative rigidity evaluation during deep brain

stimulation surgery - a preliminary study

Simone Hemm-Ode, Dagmar Gmünder, Ashesh Shah, Ulla Miguel,

Jean-Jacques Lemaire, Jerome Coste

To cite this version:

Simone Hemm-Ode, Dagmar Gmünder, Ashesh Shah, Ulla Miguel, Jean-Jacques Lemaire, et al.. Quantitative rigidity evaluation during deep brain stimulation surgery - a preliminary study. 46th annual conference of the German Society for Biomedical Engineering, German Society for Biomedical Engineering, Sep 2012, Iéna, Germany. pp.698, �10.1515/bmt-2012-4324�. �hal-01871549�

(2)

Simone Hemm-Ode et al. Biomed tech (2012) Iena, Germany

1

Quantitative rigidity evaluation during deep brain

stimulation surgery - a preliminary study

Simone Hemm-Ode, Institute for Medical and Analytical Technologies, University of

Applied Sciences Northwestern Switzerland, Muttenz, Switzerland, [email protected]

Dagmar Gmünder, Institute for Medical and Analytical Technologies, University of

Applied Sciences Northwestern Switzerland, Muttenz, Switzerland, [email protected]

Ashesh Shah, Institute for Medical and Analytical Technologies, University of Applied

Sciences Northwestern Switzerland, Muttenz, Switzerland, [email protected]

Miguel Ulla, Neuro-Psycho-pharmacologie des Systèmes dopaminergiques sous-corticaux,

Université d'Auvergne; Service de Neurologie, CHU de Ferrand, Clermont-Ferrand, France,

[email protected]

Jean- Jacques Lemaire, Image-Guided Clinical Neuroscience and Connectomics - ISIT,

Université d'Auvergne; Service de Neurochirurgie, CHU de Ferrand, Clermont-Ferrand, France,

[email protected]

Jérôme Coste, Image-Guided Clinical Neuroscience and Connectomics - ISIT, Université

d'Auvergne; Service de Neurochirurgie, CHU de Clermont-Ferrand, Clermont-Ferrand, France,

(3)

Simone Hemm-Ode et al. Biomed tech (2012) Iena, Germany

2

Introduction

Deep brain stimulation (DBS) is a common neurosurgical procedure for relieving movement related disorders such as Parkinson’s disease. DBS extends uncertainties associated with suboptimal target selection. Our aim was to evaluate the feasibility to objectively assess clinical effects obtained during intraoperative test stimulation based on acceleration measurements of the neurologist’s wrist.

Methods

One patient referred for bilateral DBS-implantationfor the treatment of Parkinson’s disease was included in the study. A 3-axis accelerometer was fixed on the neurologist's wrist during intraoperative test stimulation. While the intensity of electric current used for stimulation was increased, the neurologist continuously moved the patient's wrist to determine the moment of and the amplitude at rigidity release ("stimulation threshold"). For each test stimulation position, differrent mathematical features were determined and statistically compared a) for the time period before reaching the stimulation threshold that had been identified by the neurologist and b) after reaching the threshold. We then visually identified the stimulation thresholds that would have been chosen based on the acceleration signal alone and compared them to the ones subjectively identified by the neurologist.

Results

A statistical significant change in rigidity (p<0.01) could be identified for signal entropy, energy and standard deviation. The signal energy seemed to be the most sensible parameter showing a higher percentage change comparedto the initial clinical state. The stimulation threshold identified based on the acceleration signal was in most cases lower than the subjectively determined one.

Conclusion

The present study has demonstrated the feasibility to perform rigidity assessments from the acceleration signal of the wrist. The stimulation threshold was confirmed by the acceleration measurements, and it seems that the measurements were more sensitive than the neurologist’s evaluation. Results have to be confirmed by a larger clinical study.

Références

Documents relatifs

The extracted features are then normalized to the baseline value and the normalized feature set is used to find effec- tive stimulation amplitude (acceleration threshold). Based

Two exploration electrodes (Alpha Omega) were inserted and electrophysiological mapping (MER) was performed at the preplanned positions in both trajectories simultaneously. After

Figure 5: A) Column chart showing average Best Clinical Amplitude (BCA) and Best Quantitative Amplitude (BQA) distributed over different anatomical structures. B) 100% stacked

- For every test stimulation, change in acceleration features was calculated for the data corresponding to the visually identified effective stimulation amplitude. - Stimulation

The method was applied in 15 DBS procedures in 2 centers (University Hospital Bern, Switzerland &amp; University Hospital Clermont-Ferrand, France); the data were

In addition to comparing the improvement in tremor identified by the different methods, the IQ values were also used to identify effective stimulation current amplitudes.. For

A method for side effect analysis based on electric field simulations for intraoperative test stimulation in deep brain stimulation surgery..

Figure 2: Graph showing acceleration data (blue) along with stimulation amplitude (red) with time. In order to have a statistically significant comparison, we used Wilcoxon