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Using acceleration sensors to identify rigidity release threshold during Deep Brain Stimulation surgery
Ashesh Shah, Jerome Coste, Jean-Jacques Lemaire, Erik Schkommodau, Raphael Guzman, Ethan Taub, Simone Hemm-Ode
To cite this version:
Ashesh Shah, Jerome Coste, Jean-Jacques Lemaire, Erik Schkommodau, Raphael Guzman, et al.. Using acceleration sensors to identify rigidity release threshold during Deep Brain Stimulation surgery. 7th international IEEE EMBS Conference on Neural Engineering, Apr 2015, Montpellier, France. poster 520, 2015, IEEE/EMBS Conference on Neural Engineering (NER), 2015. �hal-01866559�
USING ACCELERATION SENSORS TO IDENTIFY RIGIDITY RELEASE THRESHOLD
DURING DEEP BRAIN STIMULATION SURGERY
A. Shah
1, Member, IEEE, J. Coste
2, JJ. Lemaire
2, E. Schkommodau
1, Member, IEEE , R. Guzman
3, E. Taub
3and S. Hemm-Ode
1, Member, IEEE
1Institute for Medical and Analytical Technologies, University of Applied Sciences and Arts Northwestern Switzerland, School of Life Sciences, Muttenz, Switzerland
2CHU de Clermont-Ferrand, EA 7282, IGCNC, Université d'Auvergne, France, CHU de Clermont-Ferrand, France
3Departments of Neurosurgery and Biomedicine, University Hospital Basel, Basel, Switzerland
Contact: Dr. Simone Hemm-Ode T +41 61 4674-796 F +41 61 4674-701 simone.hemm@fhnw.ch Ashesh Shah T +41 61 4674-413 ashesh.shah@fhnw.ch Dr. Jerome Coste T +33 4 73 751 002 jcoste@chu-clermontferrand.fr
Background
Deep brain stimulation (DBS) is now a widely accepted surgical treatment for Parkinson’s disease (PD). Electrodes are implanted in the patient’s brain after intraoperative test stimulation. Changes in parkinsonian rigidity during test stimulation are detected by an evaluator, usually a neurologist, by identifying changes in the resistance of the patient’s arm to a passive movement. When a stimulation-induced reduction in rigidity is observed, the stimulation amplitude is noted; this is the clinical rigidity release threshold. The aim of the present study was to test the hypothesis that, at the moment of reduction in rigidity, the speed with which the evaluator moves the patient's arms increases, and that this change and its amplitude can be detected with an acceleration sensor.
Methods
Institute for Medical and Analytical Technologies, Head: Prof. Dr.-Ing. Erik Schkommodau, Gründenstrasse 40, 4132 Muttenz, Switzerland. http://www.fhnw.ch/lifesciences/ima
Step 1: Data recording setup. A 3 axis accelerometer evaluation board (STEVAL-MKI022V1, ST) housed in a non-conductive printed plastic case (FullCure 830 Vero White, Objet Geometries Ltd) is mounted on the evaluators wrist using a Velcro strap. This sensor is connected to a laptop with in-house developed recording software. This software is also connected to the deep brain stimulation system which provides current during the test stimulations.
Acceleration recording system Deep brain stimulation system
Synchronization Signal Acceleration
data
Electrical Stimulation
Data Recording setup
Output
0 0,2 0,4 0,6 0,8 1 -1 -0,5 0 0,5 1 1,5 2 2,5 3 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 Stimula tion Amplitude (mA) Acc eler ation (g ) Time (ms)Acceleration Data Stimulation Amplitude
Step 2: Synchronization of two data sets. Accelerometer data is recorded during all test stimulations in synchronization with the electrophysiology system.
Acceleration data synchronized with test stimulation current
0 0,2 0,4 0,6 0,8 1 Sti mula ti on Ampl it ude (mA) Stimulation Amplitude -100 -50 0 50 100 150 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 P er cen t chang e ( %) Time (ms)
Rigidity Release Threshold Identification
Standard Deviation Signal Energy Peak Frequency Amplitude
Step 4: The data set with the highest change compared to baseline is identified and the stimulation amplitude corresponding to this data set is defined as the “Quantitatively identified rigidity release threshold” Max
Data Processing
Baseline 1 2 3 n …… Window Baseline 1 2 3 Std. Dev 0.289998 0.326865 0.273751 0.312869 Sig. Energy 0.08483 0.10719 0.075328 0.09781 Entropy 3.812613 3.732637 3.668649 4.124105 Freq. 0.761719 0.761719 1.142578 0.761719 PFA 121.0322 123.6341 102.3569 134.2219 n 0.346294 0.119767 3.796258 1.142578 114.1474 ……Step 3: Statistical features are extracted from the recorded acceleration data in a
windowed manner. Features extracted from data during test stimulation are normalized to those extracted from baseline data when there was no test stimulation.
Wilcoxon signed rank test was used to identify which features changed with change in rigidity
Feature Extraction
Clinical Application
• Clinical study carried out in University Hospital Clermont-Ferrand, France. • Data was recorded from 9 PD patients who underwent DBS surgery
• A total of 190 test stimulations were performed and data analysed following steps 1 to 4.
Results
• Three statistical features were identified to well describe rigidity release (Standard Deviation, Signal Energy and Spectral Amplitude of the Peak Frequency)
• Out of the 190 test stimulations, rigidity release thresholds were found using the clinical method for 144 evaluations, while using quantitative method, 160 thresholds were found. For 138 test stimulations, thresholds were found using both the methods.
• The rigidity release thresholds found using accelerometer evaluation are significantly lower than those found clinically (Fig 5).
Discussion
• The additional acceleration measurements during the surgery did not increase operation time or the patient’s discomfort.
• Sufficient baseline data is necessary for proper identification of acceleration thresholds.
• There is an inherent subjective component in the acceleration analysis because the evaluation is done by the neurologist.
• Further analysis in relation to anatomy could result in better target structures and could raise additional knowledge of the mechanisms of action of DBS
1,2 0,8 0 0,5 1 1,5 2 2,5 3 Clinical (n=138) Quantitative (n=138) Stimula tion Amplitude (mA)
Fig 5: Box plot showing
comparison between clinical threshold and quantitative threshold
Conclusion
• The acceleration of the neurologist’s movement is inversely proportional to change in patient‘s rigidity.
• Acceleration measurements confirm the subjective evaluation, but they seem to be more sensitive (Fig 5).
• Quantitative rigidity evaluation is feasible during DBS surgery.
Threshold Identification
Results of Clinical
Application
Acknowledgements
This research has been supported by the Swiss National Science Foundation (SNSF) and the Germaine de Stael program.
