diff --git a/plugins/processing/signal-processing/doc/Doc_BoxAlgorithm_EntropyMeasure.dox-part b/plugins/processing/signal-processing/doc/Doc_BoxAlgorithm_EntropyMeasure.dox-part
new file mode 100644
index 0000000000000000000000000000000000000000..50e866e6557490a1c823b49bc93cc7f4e51f60ab
--- /dev/null
+++ b/plugins/processing/signal-processing/doc/Doc_BoxAlgorithm_EntropyMeasure.dox-part
@@ -0,0 +1,58 @@
+/**
+ * \page BoxAlgorithm_EntropyMeasure Entropy Measure
+__________________________________________________________________
+Detailed description
+__________________________________________________________________
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Description|
+ 
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Description|
+__________________________________________________________________
+
+Inputs description
+__________________________________________________________________
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Inputs|
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Inputs|
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Input1|
+ The input EEG signal. 
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Input1|
+__________________________________________________________________
+
+Outputs description
+__________________________________________________________________
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Output1|
+ The entropy corresponding to the input signal. The form of the output varies according to the scale and the multivariate parameters.
+ In the case of univariate uniscale (scale = 1) entropy, there will be one output, with as many channels as there were input channels, each output channel being the entropy of the corresponding input channel.
+ For multivariate uniscale entropy, there will be one output with one channel corresponding to the multivariate entropy of all the input channels.
+ For multiscale entropy, there will be as many outputs as indicated by the scale (output with index i corresponding to the entropy of scale i), and the number of channels for each output will be the same as just explained for scale 1. 
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Output1|
+__________________________________________________________________
+
+Settings description
+__________________________________________________________________
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting1|
+ The output entropy is the entropy of the last "Time window" seconds of signal. 
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting1|
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting2|
+ The output entropy is updated every "Time interval" seconds.
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting2|
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting3|
+ The pattern length for sample entropy.
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting3|
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting4|
+ The similarity threshold of patterns for sample entropy.
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting4|
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting5|
+ Scale > 1 means multiscale entropy of scale "Scale".
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting5|
+
+ * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting6|
+ If "Multivariate" is true, then the box will compute multivariate entropy, otherwise it will compute univariate entropy.
+ * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting6|
diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/AbsctractEntropyCalculator.cpp b/plugins/processing/signal-processing/src/algorithms/entropy/AbsctractEntropyCalculator.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..5636f72e65ba13304ca5b27d1d67bc62011f1351
--- /dev/null
+++ b/plugins/processing/signal-processing/src/algorithms/entropy/AbsctractEntropyCalculator.cpp
@@ -0,0 +1,54 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file AbsctractEntropyCalculator.cpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "AbstractEntropyCalculator.hpp"
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+EntropyCalculator::EntropyCalculator(int scale) : m_scale(scale) {
+    m_signal.resize(m_scale);
+    m_univariateEntropy.resize(m_scale);
+    m_multivariateEntropy.resize(m_scale);
+}
+
+void EntropyCalculator::initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels) {
+    m_slidingWindowSize = slidingWindowSize;
+    m_intervalTimeSize = intervalTimeSize;
+    m_nbChannels = nbChannels;
+    
+
+    for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) {
+        for(size_t channelIdx = 0; channelIdx < m_nbChannels; channelIdx++) {
+            m_signal[scaleIdx].emplace_back(slidingWindowSize / (scaleIdx + 1));
+        }
+    }
+}
+
+}
+}
+}
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/AbstractEntropyCalculator.hpp b/plugins/processing/signal-processing/src/algorithms/entropy/AbstractEntropyCalculator.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..77682206303a0ac47452b45cc3b7432f75767417
--- /dev/null
+++ b/plugins/processing/signal-processing/src/algorithms/entropy/AbstractEntropyCalculator.hpp
@@ -0,0 +1,64 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file AbsctractEntropyCalculator.hpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "../../defines.hpp"
+#include <vector>
+#include "SlidingWindowHelper.hpp"
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+/// <summary> The abstract class EntropyCalculator describes the interface for entropy calculator classes. </summary>
+class EntropyCalculator {
+public:
+	EntropyCalculator(int scale);
+
+	virtual void initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels);
+
+	virtual void calculateUnivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) = 0;
+	virtual void calculateMultivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) = 0;
+
+protected:
+	int m_scale; // m_scale > 1 for multiscale entropy
+	size_t m_slidingWindowSize;
+	size_t m_intervalTimeSize;
+	size_t m_nbChannels;
+
+	std::vector<std::vector<SlidingWindowChannel>> m_signal;
+
+	std::vector<std::vector<double>> m_univariateEntropy;
+	std::vector<double> m_multivariateEntropy;
+	
+	int m_totSamplesCount = 0;
+	int m_totSampCntAtLastUpdate = 0;
+
+};
+
+
+}
+}
+}
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.cpp b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..f80e3e9af99fb9abcfa7af947de4bea3c3a5f22b
--- /dev/null
+++ b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.cpp
@@ -0,0 +1,318 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file SampleEntropyCalculator.cpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "SampleEntropyCalculator.hpp"
+
+#include <boost/math/special_functions/binomial.hpp>
+
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+SampleEntropyCalculator::SampleEntropyCalculator(int m, double r, int scale): EntropyCalculator(scale), m_m(m), m_r(r) {
+    m_countM.resize(m_scale);
+    m_countM1.resize(m_scale);
+    m_univariateEntropy.resize(m_scale);
+    m_leftOffIndexes.resize(m_scale);
+}
+
+void SampleEntropyCalculator::initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels) {
+    EntropyCalculator::initialize(slidingWindowSize, intervalTimeSize, nbChannels);
+
+    double maxSimilarVectors = boost::math::binomial_coefficient<double>(slidingWindowSize,2);
+    m_maxTheoriticalEntropy = log(maxSimilarVectors);
+
+
+
+    for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) {
+
+        m_countM[scaleIdx].assign(m_nbChannels, SlidingWindowCounter(slidingWindowSize));
+        m_countM1[scaleIdx].assign(m_nbChannels, SlidingWindowCounter(slidingWindowSize));
+        m_univariateEntropy[scaleIdx].assign(m_nbChannels, m_maxTheoriticalEntropy);
+        m_leftOffIndexes[scaleIdx].assign(m_nbChannels, 0);
+    }
+
+}
+
+int SampleEntropyCalculator::similarVectors(size_t chanIdx, int startIdx1, int startIdx2, int scale) {
+
+
+    const std::deque<double>& timeSeries = m_signal[0][chanIdx].getData();
+    if (startIdx1 > startIdx2 - scale) {
+        return 0;
+    }
+
+    if (startIdx2 > (int)timeSeries.size() - (m_m+1)*scale) {
+        return 0;
+    }
+
+    for(int k = 0; k < m_m + 1; k++) {
+        
+        double coarseGrainedVal1 = 0;
+        double coarseGrainedVal2 = 0;
+
+        for(int s = 0; s < scale; s++) {
+            coarseGrainedVal1 += timeSeries[startIdx1+(k*scale)+s];
+            coarseGrainedVal2 += timeSeries[startIdx2+(k*scale)+s];
+        }
+
+        coarseGrainedVal1 /= (double)scale;
+        coarseGrainedVal2 /= (double)scale;
+
+        if(fabs(coarseGrainedVal1 - coarseGrainedVal2) > m_r) {
+            if(k < m_m) { return 0; }
+            return 1;
+        }
+    }
+    return 2;
+}
+
+
+int SampleEntropyCalculator::similarVectorsMultivariate(size_t chanIdx1, size_t chanIdx2, int startIdx1, int startIdx2, int scale) {
+
+
+    const std::deque<double>& timeSeries1 = m_signal[0][chanIdx1].getData();
+    const std::deque<double>& timeSeries2 = m_signal[0][chanIdx2].getData();
+
+    if(chanIdx1 == chanIdx2 && startIdx1 >= startIdx2) {
+        return 0;
+    }
+
+    if (startIdx1 > (int)timeSeries1.size() - (m_m+1)*scale || startIdx2 > (int)timeSeries2.size() - (m_m+1)*scale) {
+        return 0;
+    }
+
+    for(int k = 0; k < m_m + 1; k++) {
+        
+        double coarseGrainedVal1 = 0;
+        double coarseGrainedVal2 = 0;
+
+        for(int s = 0; s < scale; s++) {
+            coarseGrainedVal1 += timeSeries1[startIdx1+(k*scale)+s];
+            coarseGrainedVal2 += timeSeries2[startIdx2+(k*scale)+s];
+        }
+
+        coarseGrainedVal1 /= (double)scale;
+        coarseGrainedVal2 /= (double)scale;
+
+        if(fabs(coarseGrainedVal1 - coarseGrainedVal2) > m_r) {
+            if(k < m_m) return 0;
+            return 1;
+        }
+    }
+    return 2;
+}
+
+void SampleEntropyCalculator::updateUnivariate(size_t scaleIdx, size_t chanIdx) {
+    // Update counts of similar vectors of queue N°chanIdx
+    int chanSize = m_signal[0][chanIdx].size();
+    if(chanSize >= (m_m + 2) * (scaleIdx + 1)) { //otherwise the channel is too short for any calculation to be done
+        bool flag = false;
+        for(int newlyAddedVectIdx = m_leftOffIndexes[scaleIdx][chanIdx]; newlyAddedVectIdx <= (int)chanSize - (m_m+1) * ((int)scaleIdx+1) ; newlyAddedVectIdx += scaleIdx+1) {
+
+            for(int vectIdx = newlyAddedVectIdx - (scaleIdx+1) ; vectIdx >= 0 ; vectIdx-=scaleIdx+1) {
+                flag = true;
+
+                int similarityLevel = similarVectors(chanIdx, vectIdx, newlyAddedVectIdx, scaleIdx+1);
+                
+                if(similarityLevel == SIMILAR_LENGTH_M_PLUS_1) {
+                    m_countM[scaleIdx][chanIdx].incrementAt(vectIdx);
+                    m_countM1[scaleIdx][chanIdx].incrementAt(vectIdx);
+                }
+
+                if(similarityLevel == SIMILAR_LENGTH_M) {
+                    m_countM[scaleIdx][chanIdx].incrementAt(vectIdx);
+                }
+            }
+        }
+        if(flag) {
+            m_leftOffIndexes[scaleIdx][chanIdx] = chanSize - (m_m) * (scaleIdx+1);
+        }
+    }
+
+    int totM = m_countM[scaleIdx][chanIdx].getTotal();
+    int totM1 = m_countM1[scaleIdx][chanIdx].getTotal();
+
+    int a;
+
+    if(totM == 0 || totM1 == 0) { // "infinite" entropy
+        // In theory, in that case, the entropy should be infinite. But to avoid setting it to an arbitrary high number,
+        // it is set to m_maxTheoriticalEntropy, which is higher than any value the entropy can reach when it's not infinite
+        m_univariateEntropy[scaleIdx][chanIdx] = m_maxTheoriticalEntropy;
+    } else {
+        m_univariateEntropy[scaleIdx][chanIdx] = -log((double)totM1/(double)totM);
+    }
+}
+
+void SampleEntropyCalculator::updateMultivariate(size_t scaleIdx, size_t nbChannels) {
+
+    int chanSize = m_signal[0][0].size();
+    if(chanSize >= (m_m + 2) * (scaleIdx + 1)) { //otherwise the channel is too short for any calculation to be done
+        bool flag = false;
+        for (size_t newlyAddedVectChanIdx = 0 ; newlyAddedVectChanIdx < nbChannels; ++newlyAddedVectChanIdx) {
+            for(int newlyAddedVectIdx = m_leftOffIndexes[scaleIdx][newlyAddedVectChanIdx]; newlyAddedVectIdx <= (int)chanSize - (m_m+1) * ((int)scaleIdx+1) ; newlyAddedVectIdx += scaleIdx+1) {
+
+
+                for(size_t vectChanIdx = 0 ; vectChanIdx <= newlyAddedVectChanIdx; vectChanIdx++) {
+                    for(int vectIdx = newlyAddedVectIdx ; vectIdx >= 0 ; vectIdx-=scaleIdx+1) {
+
+                        if((vectChanIdx < newlyAddedVectChanIdx && vectIdx <= newlyAddedVectIdx) || vectIdx <= newlyAddedVectIdx - scaleIdx) {
+
+                            flag = true;
+
+                            int similarityLevel = similarVectorsMultivariate(vectChanIdx, newlyAddedVectChanIdx, vectIdx, newlyAddedVectIdx, scaleIdx+1);
+                            
+                            if(similarityLevel == SIMILAR_LENGTH_M_PLUS_1) {
+                                m_countM[scaleIdx][vectChanIdx].incrementAt(vectIdx);
+                                m_countM1[scaleIdx][vectChanIdx].incrementAt(vectIdx);
+                            }
+
+                            if(similarityLevel == SIMILAR_LENGTH_M) {
+                                m_countM[scaleIdx][vectChanIdx].incrementAt(vectIdx);
+                            }
+
+                        }
+
+                    }
+                }
+            }
+
+            if(flag) {
+                m_leftOffIndexes[scaleIdx][newlyAddedVectChanIdx] = chanSize - (m_m) * (scaleIdx+1);
+            }
+        }
+    }
+
+    int totM = 0;
+    int totM1 = 0;
+
+    for(size_t chanIdx = 0; chanIdx < nbChannels; chanIdx++) {
+        totM  += m_countM[scaleIdx][chanIdx].getTotal();
+        totM1 += m_countM1[scaleIdx][chanIdx].getTotal();
+    }
+
+    if(totM == 0 || totM1 == 0) { // "infinite" entropy
+        // In theory, in that case, the entropy should be infinite. But to avoid setting it to an arbitrary high number,
+        // it is set to m_maxTheoriticalEntropy, which is higher than any value the entropy can reach when it's not infinite
+        m_multivariateEntropy[scaleIdx] = m_maxTheoriticalEntropy;
+    } else {
+        m_multivariateEntropy[scaleIdx] = -log((double)totM1/(double)totM);
+
+    }
+
+
+}
+
+void SampleEntropyCalculator::calculateUnivariate(double* &inputBuffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) {
+    bool mustUpdateEntropy = false;
+
+    for(size_t sampleIdx = 0 ; sampleIdx < nbSamplesPerChannel; ++sampleIdx) { 
+            
+        if(m_totSamplesCount + sampleIdx >= m_totSampCntAtLastUpdate + m_intervalTimeSize) {
+            m_totSampCntAtLastUpdate = m_totSamplesCount + sampleIdx;
+            mustUpdateEntropy = true;
+        }
+        for (size_t chanIdx = 0 ; chanIdx < nbChannels; ++ chanIdx) {
+
+            // Update m_signal so it contains the latest m_timeWindow seconds of signal 
+            m_signal[0][chanIdx].add(inputBuffer[chanIdx*nbSamplesPerChannel + sampleIdx]);
+
+            for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) {
+
+                m_countM[scaleIdx][chanIdx].add(0);
+                m_countM1[scaleIdx][chanIdx].add(0);
+                
+                // Remove samples older than m_timeWindow from the queue N°chanIdx
+                if (m_signal[0][chanIdx].size() > m_slidingWindowSize) {
+                    if(m_leftOffIndexes[scaleIdx][chanIdx] != 0) {
+                        m_leftOffIndexes[scaleIdx][chanIdx]--;
+                    }
+                }
+                
+                if (mustUpdateEntropy) {
+                    updateUnivariate(scaleIdx, chanIdx);
+                }
+                
+                outputMatrices[scaleIdx]->getBuffer()[chanIdx*nbSamplesPerChannel + sampleIdx] = m_univariateEntropy[scaleIdx][chanIdx];
+
+            }
+            
+        }
+        mustUpdateEntropy = false;
+        
+    }
+    m_totSamplesCount += nbSamplesPerChannel;
+}
+
+void SampleEntropyCalculator::calculateMultivariate(double* &inputBuffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) {
+    bool mustUpdateEntropy = false;
+
+    for(size_t sampleIdx = 0 ; sampleIdx < nbSamplesPerChannel; ++sampleIdx) { 
+        
+        if(m_totSamplesCount + sampleIdx >= m_totSampCntAtLastUpdate + m_intervalTimeSize) {
+            m_totSampCntAtLastUpdate = m_totSamplesCount + sampleIdx;
+            mustUpdateEntropy = true;
+        }
+        for (size_t chanIdx = 0 ; chanIdx < nbChannels; ++ chanIdx) {
+
+            // Update m_signal so it contains the latest m_timeWindow seconds of signal 
+            m_signal[0][chanIdx].add(inputBuffer[chanIdx*nbSamplesPerChannel + sampleIdx]);
+
+            for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) {
+
+                m_countM[scaleIdx][chanIdx].add(0);
+                m_countM1[scaleIdx][chanIdx].add(0);
+                
+                // Remove samples older than m_timeWindow from the queue N°chanIdx
+                if (m_signal[0][chanIdx].size() > m_slidingWindowSize) {
+                    if(m_leftOffIndexes[scaleIdx][chanIdx] != 0) {
+                        m_leftOffIndexes[scaleIdx][chanIdx]--;
+                    }
+                }
+                
+            }
+        }
+
+        for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) {
+            if (mustUpdateEntropy) {
+                updateMultivariate(scaleIdx, nbChannels);
+            }
+            
+            outputMatrices[scaleIdx]->getBuffer()[sampleIdx] = m_multivariateEntropy[scaleIdx];
+        }
+
+            
+        mustUpdateEntropy = false;
+        
+    }
+    m_totSamplesCount += nbSamplesPerChannel;
+}
+
+
+}
+}
+}
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.hpp b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..dffeffe56f74c8cc71cd8b387446e451fa5ff4e4
--- /dev/null
+++ b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.hpp
@@ -0,0 +1,81 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file SampleEntropyCalculator.hpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "AbstractEntropyCalculator.hpp"
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+/// <summary> The class SampleEntropyCalculator describes one implementation of the Entropy Calculator abstract class that computes sample entropy. </summary>
+class SampleEntropyCalculator : public EntropyCalculator {
+public:
+	SampleEntropyCalculator(int m, double r, int scale = 1);
+
+	void initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels) override;
+
+	/**
+	* @brief Updates m_univariateEntropy so it contains, for each channel, the values of the corresponding sample entropy 
+	*/
+	void calculateUnivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) override;
+	/**
+	* @brief Updates m_multivariateEntropy so it contains the values of the multivariate sample entropy 
+	*/
+	void calculateMultivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) override;
+	
+
+
+private:
+	int m_m;
+	double m_r;
+
+	std::vector<std::vector<SlidingWindowCounter>> m_countM;
+	std::vector<std::vector<SlidingWindowCounter>> m_countM1;
+
+	std::vector<std::vector<size_t>> m_leftOffIndexes;
+	double m_maxTheoriticalEntropy;
+
+	enum SimilarityLevel {NOT_SIMILAR, SIMILAR_LENGTH_M, SIMILAR_LENGTH_M_PLUS_1};
+	/**
+	* @brief Checks if vectors of channel chanIdx that start at startIdx1 and startIdx2 and have length m_m have a distance lower that m_r, for scale scale
+	*/
+	int similarVectors(size_t chanIdx, int startIdx1, int startIdx2, int scale);
+	int similarVectorsMultivariate(size_t chanIdx1, size_t chanIdx2, int startIdx1, int startIdx2, int scale);
+	
+	/**
+	* @brief Updates the values of the univariate entropy so they can be added to the output buffer
+	*/
+	void updateUnivariate(size_t scaleIdx, size_t chanIdx);
+	/**
+	* @brief Updates the values of the multivariate entropy so they can be added to the output buffer
+	*/
+	void updateMultivariate(size_t scaleIdx, size_t nbChannels);
+
+};
+
+}
+}
+}
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.cpp b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..4c7ab6e47059aa02221441c2ba37730d2d3aea58
--- /dev/null
+++ b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.cpp
@@ -0,0 +1,71 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file SlidingWindowHelper.cpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "SlidingWindowHelper.hpp"
+
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+// ----------------- SlidingWindowChannel class -----------------
+SlidingWindowChannel::SlidingWindowChannel(size_t maxLength): SlidingWindowQueue<double>(maxLength) {}
+
+void SlidingWindowChannel::add(double value) {
+    if (m_data.size() > m_maxLength) {
+        m_data.pop_front(); // Remove the oldest element if at max length
+    }
+    m_data.push_back(value); // Add the new value
+}
+
+// -----------------SlidingWindowCounter class -----------------
+SlidingWindowCounter::SlidingWindowCounter(size_t maxLength): SlidingWindowQueue<int>(maxLength), m_total(0) {}
+
+void SlidingWindowCounter::add(int value) {
+    if (m_data.size() > m_maxLength) {
+        m_total -= m_data.front(); 
+        m_data.pop_front(); 
+    }
+    m_data.push_back(value); 
+    m_total += value; 
+}
+
+void SlidingWindowCounter::incrementAt(size_t index) {
+    if(index >= m_data.size()) {
+        throw std::invalid_argument("Index out of bounds");
+    } else {
+        m_data[index]++;
+        m_total++;
+    }
+}
+
+int SlidingWindowCounter::getTotal() const {
+    return m_total;
+}
+
+}
+}
+}
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.hpp b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..d28fbe621c3735e0cc23b4f5e9fd1a9a26c24944
--- /dev/null
+++ b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.hpp
@@ -0,0 +1,75 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file SlidingWindowHelper.hpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "../../defines.hpp"
+#include <toolkit/ovtk_all.h>
+
+#include <queue>
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+
+// SlidingWindowQueue abstract class
+template <typename T>
+class SlidingWindowQueue {
+public:
+    SlidingWindowQueue(size_t maxLength) : m_maxLength(maxLength) {}
+
+    size_t size() const { return m_data.size(); }
+    const std::deque<T>& getData() const { return m_data; }
+
+	virtual void add(T value) = 0;
+
+protected:
+	size_t m_maxLength;
+	std::deque<T> m_data;
+};
+
+// SlidingWindowChannel class
+class SlidingWindowChannel : public SlidingWindowQueue<double> {
+public:
+	explicit SlidingWindowChannel(size_t maxLength);
+
+	void add(double value) override;
+};
+
+// SlidingWindowCounter class
+class SlidingWindowCounter : public SlidingWindowQueue<int> {
+public:
+ 	explicit SlidingWindowCounter(size_t maxLength);
+	
+	void add(int value) override;
+	void incrementAt(size_t index);
+	int getTotal() const;
+private:
+	int m_total;
+};
+
+}
+}
+}
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.cpp b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..06d2a6dddd46c23a87457a0552da46ce255045b7
--- /dev/null
+++ b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.cpp
@@ -0,0 +1,147 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file CBoxAlgorithmEntropyMeasure.cpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+
+#include <iomanip>
+#include "CBoxAlgorithmEntropyMeasure.hpp"
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+bool CBoxAlgorithmEntropyMeasure::initialize() {
+	m_timeWindow = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 0);
+	m_timeInterval = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 1);
+	m_m = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 2);
+	m_r = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 3);
+    m_scale = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 4);
+    m_isMultivariate = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 5);
+
+    m_inputDecoder.initialize(*this, 0);
+    m_outputMatrices.resize(m_scale);
+    m_outputEncoders.resize(m_scale);
+
+    for(int scale = 0; scale < m_scale; scale++) {
+        m_outputMatrices[scale] = new CMatrix();
+
+	    m_outputEncoders[scale].initialize(*this, scale);
+        m_outputEncoders[scale].getInputMatrix().setReferenceTarget(m_outputMatrices[scale]);
+        m_outputEncoders[scale].getInputSamplingRate().setReferenceTarget(m_inputDecoder.getOutputSamplingRate());
+    }
+
+    m_entropyCalculator = new SampleEntropyCalculator(m_m, m_r, m_scale);
+
+    std::cout << std::fixed;
+    std::cout << std::setprecision(16);
+
+
+    return true;
+}
+
+bool CBoxAlgorithmEntropyMeasure::uninitialize()
+{
+	m_inputDecoder.uninitialize();
+    for(int scale = 0; scale < m_scale; scale++) {
+	    m_outputEncoders[scale].uninitialize();
+    }
+	return true;
+}
+
+bool CBoxAlgorithmEntropyMeasure::processInput(const size_t index)
+{
+	getBoxAlgorithmContext()->markAlgorithmAsReadyToProcess();
+	return true;
+}
+
+
+
+bool CBoxAlgorithmEntropyMeasure::process()
+{
+	IDynamicBoxContext& dynamicBoxContext = this->getDynamicBoxContext();
+
+	for (size_t i = 0; i < dynamicBoxContext.getInputChunkCount(0); ++i) {
+
+		m_inputDecoder.decode(i);
+
+        const uint64_t tStart = dynamicBoxContext.getInputChunkStartTime(0, i);
+		const uint64_t tEnd   = dynamicBoxContext.getInputChunkEndTime(0, i);
+
+        CMatrix* iMatrix = m_inputDecoder.getOutputMatrix();
+
+        const size_t nbChannels = iMatrix->getDimensionSize(0);
+		const size_t nbSamplesPerChannel = iMatrix->getDimensionSize(1);
+
+
+		if (m_inputDecoder.isHeaderReceived()) {
+            
+			m_samplingRate = m_inputDecoder.getOutputSamplingRate();
+            size_t maxChanSize = floor(m_samplingRate * m_timeWindow);
+            size_t timeIntervalSize = floor(m_samplingRate * m_timeInterval);
+
+            // initialize entropy calculator
+            m_entropyCalculator->initialize(maxChanSize, timeIntervalSize, nbChannels);
+			
+            // Pass the header to the next boxes, by encoding a header:
+            for(int scale = 0; scale < m_scale; scale++) {
+                if(!m_isMultivariate) {
+                    m_outputMatrices[scale]->resize(nbChannels,nbSamplesPerChannel);
+                } else {
+                    m_outputMatrices[scale]->resize(1, nbSamplesPerChannel);
+                }
+			    m_outputEncoders[scale].encodeHeader();
+            }
+		}
+
+		if (m_inputDecoder.isBufferReceived()) {        
+
+            double* inputBuffer = iMatrix->getBuffer();
+                
+            if(!m_isMultivariate) {
+                m_entropyCalculator->calculateUnivariate(inputBuffer, nbSamplesPerChannel, nbChannels, m_outputMatrices);
+            } else {
+                m_entropyCalculator-> calculateMultivariate(inputBuffer, nbSamplesPerChannel, nbChannels, m_outputMatrices);
+            }
+
+            for(int scale = 0; scale < m_scale; scale++) {
+                m_outputEncoders[scale].encodeBuffer();
+            }
+
+        }
+
+		if (m_inputDecoder.isEndReceived()) {
+            for(int scale = 0; scale < m_scale; scale++)
+                m_outputEncoders[scale].encodeEnd();
+		}
+
+        for(int scale = 0; scale < m_scale; scale++) {
+		    dynamicBoxContext.markOutputAsReadyToSend(scale, tStart, tEnd);   
+        }
+    }
+
+    return true;
+}
+
+}  // namespace SignalProcessing
+}  // namespace Plugins
+}  // namespace OpenViBE
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.hpp b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..2f9b55694ee4a289a84aba5d1ba880333fa1afaa
--- /dev/null
+++ b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.hpp
@@ -0,0 +1,169 @@
+///-------------------------------------------------------------------------------------------------
+/// 
+/// \file CBoxAlgorithmEntropyMeasure.hpp
+/// \brief Classes of the Box Entropy Measures.
+/// \author Axel Bouneau (Inria).
+/// \version 1.0.
+/// \date Mon Jan 29 10:00:00 2024.
+/// \Copyright (C) 2024 Inria
+/// 
+/// This program is free software: you can redistribute it and/or modify
+/// it under the terms of the GNU Affero General Public License as published by
+/// the Free Software Foundation, either version 3 of the License, or
+/// (at your option) any later version.
+/// 
+/// This program is distributed in the hope that it will be useful,
+/// but WITHOUT ANY WARRANTY; without even the implied warranty of
+/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+/// GNU Affero General Public License for more details.
+/// 
+/// You should have received a copy of the GNU Affero General Public License
+/// along with this program.  If not, see <http://www.gnu.org/licenses/>.
+/// 
+///-------------------------------------------------------------------------------------------------
+
+#pragma once
+
+#include "../defines.hpp"
+#include <toolkit/ovtk_all.h>
+
+#include "../algorithms/entropy/SampleEntropyCalculator.hpp"
+
+
+// The unique identifiers for the box and its descriptor.
+// Identifier are randomly chosen by the skeleton-generator.
+#define OV_AttributeId_Box_FlagIsUnstable					OpenViBE::CIdentifier(0x666FFFFF, 0x666FFFFF)
+
+namespace OpenViBE {
+namespace Plugins {
+namespace SignalProcessing {
+
+
+/// <summary> The class CBoxAlgorithmEntropyMeasure describes the box Entropy Measure. </summary>
+class CBoxAlgorithmEntropyMeasure final : virtual public Toolkit::TBoxAlgorithm<IBoxAlgorithm>
+{
+public:
+	void release() override { delete this; }
+
+	bool initialize() override;
+	bool uninitialize() override;
+
+	bool processInput(const size_t index) override;
+
+	bool process() override;
+
+
+	// As we do with any class in openvibe, we use the macro below to associate this box to an unique identifier. 
+	// The inheritance information is also made available, as we provide the superclass Toolkit::TBoxAlgorithm < IBoxAlgorithm >
+	_IsDerivedFromClass_Final_(Toolkit::TBoxAlgorithm<IBoxAlgorithm>, OVP_ClassId_BoxAlgorithm_EntropyMeasure)
+
+protected:
+	// Input decoder:
+	Toolkit::TSignalDecoder<CBoxAlgorithmEntropyMeasure> m_inputDecoder;
+	// Output decoder:
+	std::vector<Toolkit::TSignalEncoder<CBoxAlgorithmEntropyMeasure>> m_outputEncoders;
+	std::vector<CMatrix*> m_outputMatrices;
+
+private:
+	double m_samplingRate = 0.0;
+	
+	
+	// box parameters
+	double m_timeWindow = 0.0;
+	double m_timeInterval = 0.0;
+
+	// m is the length of the pattern vectors
+	int m_m = 0;
+
+	// r is the range below which two vectors are considered similar
+	double m_r = 0;
+
+	// m_scale is the scale wanted for entropy calculation. 1 for normal entropy ; >1 for multiscale entropy
+	int m_scale = 1;
+
+	bool m_isMultivariate = false;
+
+	EntropyCalculator* m_entropyCalculator;
+};
+
+/// <summary> The class CBoxAlgorithmEntropyMeasureListener allows to change the amount of outputs of the entropy measure box, depending on the scale parameter chosen by the user. </summary>
+class CBoxAlgorithmEntropyMeasureListener final : public Toolkit::TBoxListener<IBoxListener>
+{
+public:
+	bool onSettingValueChanged(Kernel::IBox& box, const size_t index) override
+	{
+		if (index == 4) {
+			CString scaleStr;
+			box.getSettingValue(index, scaleStr);
+
+			int wantedScale = atoi(scaleStr);
+			int currentScale = box.getOutputCount();
+
+			if(wantedScale < 1) wantedScale = 1;
+			if(wantedScale > 20) wantedScale = 20;
+
+			if (wantedScale > currentScale) {
+				for (int i = currentScale; i < wantedScale; ++i) {
+					char name[50];
+					std::sprintf(name, "Entropy scale %d", i+1);
+
+					box.addOutput(name, OV_TypeId_Signal);
+				}
+			// If wantedScale is less than currentScale, remove outputs
+			} else if (wantedScale < currentScale) {
+				for (int i = currentScale; i > wantedScale && i > 1; --i) {
+					box.removeOutput(box.getOutputCount() - 1);
+				}
+			}
+		}
+
+		return true;
+	}
+private:
+	_IsDerivedFromClass_Final_(Toolkit::TBoxListener<IBoxListener>, CIdentifier::undefined())
+};
+
+/// <summary> Descriptor of the box Entropy Measure. </summary>
+class CBoxAlgorithmEntropyMeasureDesc final : virtual public IBoxAlgorithmDesc
+{
+public:
+	void release() override { }
+
+	CString getName() const override { return CString("Entropy Measure"); }
+	CString getAuthorName() const override { return CString("Axel Bouneau"); }
+	CString getAuthorCompanyName() const override { return CString("Inria"); }
+	CString getShortDescription() const override { return CString("Computes the Entropy of an EEG signal."); }
+	CString getDetailedDescription() const override { return CString("Computes the sample entropy of the input signal. Can be set to compute multivariate and/or multiscale sample entropy."); }
+	CString getCategory() const override { return CString("Measures"); }
+	CString getVersion() const override { return CString("1.0"); }
+	CString getStockItemName() const override { return CString("gtk-remove"); }
+
+	CIdentifier getCreatedClass() const override { return OVP_ClassId_BoxAlgorithm_EntropyMeasure; }
+	IPluginObject* create() override { return new CBoxAlgorithmEntropyMeasure; }
+	IBoxListener* createBoxListener() const override { return new CBoxAlgorithmEntropyMeasureListener; }
+
+
+	bool getBoxPrototype(Kernel::IBoxProto& prototype) const override
+	{
+		prototype.addInput("Signal", OV_TypeId_Signal);
+
+		prototype.addOutput("Entropy", OV_TypeId_Signal);
+
+		prototype.addSetting("Time window (s)", OV_TypeId_Float, "10.0");
+		prototype.addSetting("Time interval (s)", OV_TypeId_Float, "0.0");
+		prototype.addSetting("m (pattern length)", OV_TypeId_Integer, "2");
+		prototype.addSetting("r (tolerance)", OV_TypeId_Float, "0.2");
+
+		prototype.addSetting("Scale", OV_TypeId_Integer, "1");
+		prototype.addSetting("Multivariate", OV_TypeId_Boolean, "false");
+		
+
+		return true;
+	}
+	_IsDerivedFromClass_Final_(IBoxAlgorithmDesc, OVP_ClassId_BoxAlgorithm_EntropyMeasureDesc)
+};
+
+
+}  // namespace SignalProcessing
+}  // namespace Plugins
+}  // namespace OpenViBE
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/src/defines.hpp b/plugins/processing/signal-processing/src/defines.hpp
index e893a4bc88af8570b9950362ccb52c5253015ea9..96f70ac186e0bbe7a1f5a852acf886a46b701963 100644
--- a/plugins/processing/signal-processing/src/defines.hpp
+++ b/plugins/processing/signal-processing/src/defines.hpp
@@ -56,6 +56,8 @@
 #define OVP_ClassId_BoxAlgorithm_ConnectivitySpectrumExtractDesc	OpenViBE::CIdentifier(0xb6e4b7c1, 0x7331662d)
 #define OVP_ClassId_BoxAlgorithm_PulseRateCalculator				OpenViBE::CIdentifier(0x034466a7, 0x8059bcf3)
 #define OVP_ClassId_BoxAlgorithm_PulseRateCalculatorDesc			OpenViBE::CIdentifier(0x04d32034, 0x096c0b42)
+#define OVP_ClassId_BoxAlgorithm_EntropyMeasure						OpenViBE::CIdentifier(0x46911275, 0xEC146FA3)
+#define OVP_ClassId_BoxAlgorithm_EntropyMeasureDesc					OpenViBE::CIdentifier(0xC7482EBA, 0x31772D60)
 
 #define Box_EpochVariance											OpenViBE::CIdentifier(0x335384EA, 0x88C917D0)
 #define Box_EpochVarianceDesc										OpenViBE::CIdentifier(0xA15EAEC5, 0xAB0CE730)
diff --git a/plugins/processing/signal-processing/src/main.cpp b/plugins/processing/signal-processing/src/main.cpp
index 2b27d3d3de1439a3e31761e7f933f28108baf13a..28a96bcf1bd1b77d574e7eaf458574c23a7762aa 100644
--- a/plugins/processing/signal-processing/src/main.cpp
+++ b/plugins/processing/signal-processing/src/main.cpp
@@ -24,7 +24,7 @@
 #include "box-algorithms/connectivity/CBoxAlgorithmConnectivitySpectrumExtract.hpp"
 
 #include "box-algorithms/CBoxAlgorithmPulseRateCalculator.hpp"
-
+#include "box-algorithms/CBoxAlgorithmEntropyMeasure.hpp"
 
 namespace OpenViBE {
 namespace Plugins {
@@ -52,7 +52,8 @@ OVP_Declare_Begin()
 	OVP_Declare_New(CBoxAlgorithmHilbertDesc)
 	OVP_Declare_New(CBoxIFFTDesc)
 
-	OVP_Declare_New(CBoxAlgorithmPulseRateCalculatorDesc);
+	OVP_Declare_New(CBoxAlgorithmPulseRateCalculatorDesc)
+	OVP_Declare_New(CBoxAlgorithmEntropyMeasureDesc)
 
 
 #if defined(TARGET_HAS_ThirdPartyFFTW3)
diff --git a/plugins/processing/signal-processing/test/DartTestfile.txt b/plugins/processing/signal-processing/test/DartTestfile.txt
index 5d100a81069107a077bdb85fe74914eb1569efc9..d479e2f9948223cacd7c66d6d43e2942f28d8d0d 100644
--- a/plugins/processing/signal-processing/test/DartTestfile.txt
+++ b/plugins/processing/signal-processing/test/DartTestfile.txt
@@ -17,4 +17,5 @@ validation_test_with_csv(scenarios-tests Discrete-Wavelet-Transform)
 validation_test_with_csv(scenarios-tests Discrete-Wavelet-Transform-Inverse)
 validation_test_with_csv(scenarios-tests ConnectivityWelch)
 validation_test_with_csv(scenarios-tests ConnectivityMVAR)
-validation_test_with_csv(scenarios-tests Pulse-Rate-Calculator)
\ No newline at end of file
+validation_test_with_csv(scenarios-tests Pulse-Rate-Calculator)
+validation_test_with_csv(scenarios-tests Entropy-Measure)
\ No newline at end of file
diff --git a/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-input.csv b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-input.csv
new file mode 100644
index 0000000000000000000000000000000000000000..b75a774cf0c0ab39d796c09f8fe3e961fc7c1e28
--- /dev/null
+++ b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-input.csv
@@ -0,0 +1,5001 @@
+Time:500Hz,Epoch,FP1,Event Id,Event Date,Event Duration
+0,0,0.53766714,,,
+0.002,0,1.833885,,,
+0.004,0,-2.2588469,,,
+0.006,0,0.86217332,,,
+0.008,0,0.31876524,,,
+0.01,0,-1.3076883,,,
+0.012,0,-0.43359202,,,
+0.014,0,0.34262447,,,
+0.016,0,3.5783969,,,
+0.018,0,2.769437,,,
+0.02,0,-1.3498869,,,
+0.022,0,3.0349235,,,
+0.024,0,0.72540422,,,
+0.026,0,-0.063054873,,,
+0.028,0,0.7147429,,,
+0.03,0,-0.20496606,,,
+0.032,0,-0.12414435,,,
+0.034,0,1.4896976,,,
+0.036,0,1.4090345,,,
+0.038,0,1.4171924,,,
+0.04,0,0.67149713,,,
+0.042,0,-1.2074869,,,
+0.044,0,0.71723865,,,
+0.046,0,1.6302353,,,
+0.048,0,0.48889377,,,
+0.05,1,1.034693,,,
+0.052,1,0.72688513,,,
+0.054,1,-0.30344092,,,
+0.056,1,0.29387147,,,
+0.058,1,-0.7872828,,,
+0.06,1,0.88839563,,,
+0.062,1,-1.1470701,,,
+0.064,1,-1.0688705,,,
+0.066,1,-0.80949869,,,
+0.068,1,-2.9442842,,,
+0.07,1,1.4383803,,,
+0.072,1,0.32519054,,,
+0.074,1,-0.75492832,,,
+0.076,1,1.3702985,,,
+0.078,1,-1.7115164,,,
+0.08,1,-0.10224245,,,
+0.082,1,-0.24144704,,,
+0.084,1,0.31920674,,,
+0.086,1,0.3128586,,,
+0.088,1,-0.86487992,,,
+0.09,1,-0.030051296,,,
+0.092,1,-0.16487902,,,
+0.094,1,0.62770729,,,
+0.096,1,1.0932657,,,
+0.098,1,1.1092733,,,
+0.1,2,-0.86365282,,,
+0.102,2,0.077359091,,,
+0.104,2,-1.214117,,,
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diff --git a/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-ref.csv b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-ref.csv
new file mode 100644
index 0000000000000000000000000000000000000000..2b3202b96b73f10f5d192a14707452ba3c99a310
--- /dev/null
+++ b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-ref.csv
@@ -0,0 +1,5001 @@
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diff --git a/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-test.xml b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-test.xml
new file mode 100644
index 0000000000000000000000000000000000000000..13ad2471d97a4107e9c36070df5b65f6d567f838
--- /dev/null
+++ b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-test.xml
@@ -0,0 +1,490 @@
+<OpenViBE-Scenario>
+	<FormatVersion>2</FormatVersion>
+	<Creator>OpenViBE Designer</Creator>
+	<CreatorVersion>3.6.0</CreatorVersion>
+	<Settings>
+		<Setting>
+			<Identifier>(0xd2d61f0d, 0xe70f6d31)</Identifier>
+			<TypeIdentifier>(0x79a9edeb, 0x245d83fc)</TypeIdentifier>
+			<Name>I-O File Names</Name>
+			<DefaultValue>Entropy-Measure</DefaultValue>
+			<Value>Entropy-Measure</Value>
+		</Setting>
+	</Settings>
+	<Inputs></Inputs>
+	<Outputs></Outputs>
+	<Boxes>
+		<Box>
+			<Identifier>(0x00000cd2, 0x0000577b)</Identifier>
+			<Name>Entropy Measure</Name>
+			<AlgorithmClassIdentifier>(0x46911275, 0xec146fa3)</AlgorithmClassIdentifier>
+			<Inputs>
+				<Input>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Signal</Name>
+				</Input>
+			</Inputs>
+			<Outputs>
+				<Output>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Entropy</Name>
+				</Output>
+				<Output>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Entropy scale 2</Name>
+				</Output>
+				<Output>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Entropy scale 3</Name>
+				</Output>
+				<Output>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Entropy scale 4</Name>
+				</Output>
+			</Outputs>
+			<Settings>
+				<Setting>
+					<TypeIdentifier>(0x512a166f, 0x5c3ef83f)</TypeIdentifier>
+					<Name>Time window (s)</Name>
+					<DefaultValue>10.0</DefaultValue>
+					<Value>10</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x512a166f, 0x5c3ef83f)</TypeIdentifier>
+					<Name>Time interval (s)</Name>
+					<DefaultValue>0.0</DefaultValue>
+					<Value>0</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
+					<Name>m (pattern length)</Name>
+					<DefaultValue>2</DefaultValue>
+					<Value>2</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x512a166f, 0x5c3ef83f)</TypeIdentifier>
+					<Name>r (tolerance)</Name>
+					<DefaultValue>0.2</DefaultValue>
+					<Value>0.2</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
+					<Name>Scale</Name>
+					<DefaultValue>1</DefaultValue>
+					<Value>4</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
+					<Name>Multivariate</Name>
+					<DefaultValue>false</DefaultValue>
+					<Value>false</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+			</Settings>
+			<Attributes>
+				<Attribute>
+					<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
+					<Value>-128</Value>
+				</Attribute>
+				<Attribute>
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+					<Value>144</Value>
+				</Attribute>
+				<Attribute>
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+				<Attribute>
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+					<Value>1</Value>
+				</Attribute>
+				<Attribute>
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+				</Attribute>
+				<Attribute>
+					<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
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+				</Attribute>
+			</Attributes>
+		</Box>
+		<Box>
+			<Identifier>(0x0000290e, 0x00005050)</Identifier>
+			<Name>Timeout</Name>
+			<AlgorithmClassIdentifier>(0x24fcd292, 0x5c8f6aa8)</AlgorithmClassIdentifier>
+			<Inputs>
+				<Input>
+					<TypeIdentifier>(0x544a003e, 0x6dcba5f6)</TypeIdentifier>
+					<Name>Input Stream</Name>
+				</Input>
+			</Inputs>
+			<Outputs>
+				<Output>
+					<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
+					<Name>Output Stimulations</Name>
+				</Output>
+			</Outputs>
+			<Settings>
+				<Setting>
+					<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
+					<Name>Timeout delay</Name>
+					<DefaultValue>5</DefaultValue>
+					<Value>10</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
+					<Name>Output Stimulation</Name>
+					<DefaultValue>OVTK_StimulationId_Label_00</DefaultValue>
+					<Value>OVTK_StimulationId_Label_00</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+			</Settings>
+			<Attributes>
+				<Attribute>
+					<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
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+				</Attribute>
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+		<Box>
+			<Identifier>(0x000041a1, 0x00003606)</Identifier>
+			<Name>Player Controller</Name>
+			<AlgorithmClassIdentifier>(0x5f426dce, 0x08456e13)</AlgorithmClassIdentifier>
+			<Inputs>
+				<Input>
+					<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
+					<Name>Stimulations</Name>
+				</Input>
+			</Inputs>
+			<Settings>
+				<Setting>
+					<TypeIdentifier>(0x2c132d6e, 0x44ab0d97)</TypeIdentifier>
+					<Name>Stimulation name</Name>
+					<DefaultValue>OVTK_StimulationId_Label_00</DefaultValue>
+					<Value>OVTK_StimulationId_Label_00</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0xcc14d8d6, 0xf27ecb73)</TypeIdentifier>
+					<Name>Action to perform</Name>
+					<DefaultValue>Pause</DefaultValue>
+					<Value>Stop</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+			</Settings>
+			<Attributes>
+				<Attribute>
+					<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
+					<Value>-16</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
+					<Value>320</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
+					<Value>(0x568d148e, 0x650792b3)</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
+					<Value>2</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
+					<Value>1</Value>
+				</Attribute>
+			</Attributes>
+		</Box>
+		<Box>
+			<Identifier>(0x000042fc, 0x00005161)</Identifier>
+			<Name>CSV File Writer</Name>
+			<AlgorithmClassIdentifier>(0x428375e8, 0x325f2db9)</AlgorithmClassIdentifier>
+			<Inputs>
+				<Input>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Input stream</Name>
+				</Input>
+				<Input>
+					<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
+					<Name>Stimulations stream</Name>
+				</Input>
+			</Inputs>
+			<Settings>
+				<Setting>
+					<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
+					<Name>Filename</Name>
+					<DefaultValue>record-[$core{date}-$core{time}].csv</DefaultValue>
+					<Value>${Player_ScenarioDirectory}/$var{I-O File Names}-output.csv</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier>
+					<Name>Precision</Name>
+					<DefaultValue>10</DefaultValue>
+					<Value>10</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
+					<Name>Append data</Name>
+					<DefaultValue>false</DefaultValue>
+					<Value>false</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+				<Setting>
+					<TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier>
+					<Name>Only last matrix</Name>
+					<DefaultValue>false</DefaultValue>
+					<Value>false</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+			</Settings>
+			<Attributes>
+				<Attribute>
+					<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
+					<Value>32</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
+					<Value>144</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
+					<Value>(0xc33e47e0, 0x70e5f31b)</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x527ad68d, 0x16d746a0)</Identifier>
+					<Value></Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
+					<Value>4</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
+					<Value>2</Value>
+				</Attribute>
+			</Attributes>
+		</Box>
+		<Box>
+			<Identifier>(0x000051f3, 0x000007af)</Identifier>
+			<Name>CSV File Reader</Name>
+			<AlgorithmClassIdentifier>(0x336a3d9a, 0x753f1ba4)</AlgorithmClassIdentifier>
+			<Outputs>
+				<Output>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Output stream</Name>
+				</Output>
+				<Output>
+					<TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier>
+					<Name>Output stimulation</Name>
+				</Output>
+			</Outputs>
+			<Settings>
+				<Setting>
+					<TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier>
+					<Name>Filename</Name>
+					<DefaultValue></DefaultValue>
+					<Value>${Player_ScenarioDirectory}/$var{I-O File Names}-input.csv</Value>
+					<Modifiability>false</Modifiability>
+				</Setting>
+			</Settings>
+			<Attributes>
+				<Attribute>
+					<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
+					<Value>-192</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
+					<Value>144</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x30a4e5c9, 0x83502953)</Identifier>
+					<Value></Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
+					<Value>(0xa9cdc629, 0xb153eb33)</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xc80ce8af, 0xf699f813)</Identifier>
+					<Value>2</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xce18836a, 0x9c0eb403)</Identifier>
+					<Value>1</Value>
+				</Attribute>
+			</Attributes>
+		</Box>
+		<Box>
+			<Identifier>(0x00006878, 0x000009e3)</Identifier>
+			<Name>Signal Merger</Name>
+			<AlgorithmClassIdentifier>(0x4bf9326f, 0x75603102)</AlgorithmClassIdentifier>
+			<Inputs>
+				<Input>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Input 1</Name>
+				</Input>
+				<Input>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Input 2</Name>
+				</Input>
+				<Input>
+					<Identifier>(0xe991e469, 0x79d3635c)</Identifier>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Input 3</Name>
+				</Input>
+				<Input>
+					<Identifier>(0xe1d0f6d2, 0x9f7af780)</Identifier>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Input 4</Name>
+				</Input>
+			</Inputs>
+			<Outputs>
+				<Output>
+					<TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier>
+					<Name>Merged</Name>
+				</Output>
+			</Outputs>
+			<Attributes>
+				<Attribute>
+					<Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier>
+					<Value>-48</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x207c9054, 0x3c841b63)</Identifier>
+					<Value>144</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0x4e7b798a, 0x183beafb)</Identifier>
+					<Value>(0x990c5a68, 0x0d4024a3)</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xc80ce8af, 0xf699f813)</Identifier>
+					<Value>1</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier>
+					<Value>2</Value>
+				</Attribute>
+				<Attribute>
+					<Identifier>(0xfba64161, 0x65304e21)</Identifier>
+					<Value></Value>
+				</Attribute>
+			</Attributes>
+		</Box>
+	</Boxes>
+	<Links>
+		<Link>
+			<Identifier>(0x000001bf, 0x00007450)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x000051f3, 0x000007af)</BoxIdentifier>
+				<BoxOutputIndex>0</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier>
+				<BoxInputIndex>0</BoxInputIndex>
+			</Target>
+		</Link>
+		<Link>
+			<Identifier>(0x000008f5, 0x0000115c)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier>
+				<BoxOutputIndex>3</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier>
+				<BoxInputIdentifier>(0xe1d0f6d2, 0x9f7af780)</BoxInputIdentifier>
+			</Target>
+		</Link>
+		<Link>
+			<Identifier>(0x00000f4b, 0x000040d2)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier>
+				<BoxOutputIndex>0</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x000042fc, 0x00005161)</BoxIdentifier>
+				<BoxInputIndex>0</BoxInputIndex>
+			</Target>
+		</Link>
+		<Link>
+			<Identifier>(0x0000329d, 0x0000451a)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x0000290e, 0x00005050)</BoxIdentifier>
+				<BoxOutputIndex>0</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x000041a1, 0x00003606)</BoxIdentifier>
+				<BoxInputIndex>0</BoxInputIndex>
+			</Target>
+		</Link>
+		<Link>
+			<Identifier>(0x0000565b, 0x00006a8c)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier>
+				<BoxOutputIndex>2</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier>
+				<BoxInputIdentifier>(0xe991e469, 0x79d3635c)</BoxInputIdentifier>
+			</Target>
+		</Link>
+		<Link>
+			<Identifier>(0x00006367, 0x000006ec)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier>
+				<BoxOutputIndex>1</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier>
+				<BoxInputIndex>1</BoxInputIndex>
+			</Target>
+		</Link>
+		<Link>
+			<Identifier>(0x00006bf4, 0x000069ea)</Identifier>
+			<Source>
+				<BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier>
+				<BoxOutputIndex>0</BoxOutputIndex>
+			</Source>
+			<Target>
+				<BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier>
+				<BoxInputIndex>0</BoxInputIndex>
+			</Target>
+		</Link>
+	</Links>
+	<Comments></Comments>
+	<Metadata>
+		<Entry>
+			<Identifier>(0x00007a14, 0x000060c9)</Identifier>
+			<Type>(0x3bcce5d2, 0x43f2d968)</Type>
+			<Data>[{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"height":320,"identifier":"(0x0000381e, 0x000065b2)","name":"Default window","parentIdentifier":"(0xffffffff, 0xffffffff)","type":1,"width":480},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"identifier":"(0x00002f66, 0x000056ec)","index":0,"name":"Default tab","parentIdentifier":"(0x0000381e, 0x000065b2)","type":2},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":0,"identifier":"(0x00001e9c, 0x00006839)","index":0,"name":"Empty","parentIdentifier":"(0x00002f66, 0x000056ec)","type":0}]</Data>
+		</Entry>
+	</Metadata>
+</OpenViBE-Scenario>
\ No newline at end of file