From 40d7b7146163248405316ddc1c9d14dd3b17d39c Mon Sep 17 00:00:00 2001 From: Richard Waltman Date: Fri, 23 Jul 2021 22:12:28 -0500 Subject: [PATCH 1/6] First attempt auditory neurofeedback - Need to use minim library instead to change audio volume of mp3 --- OpenBCI_GUI/AuditoryNeurofeedback.pde | 84 ++++++++++++++++++++++++++ OpenBCI_GUI/ControlPanel.pde | 1 + OpenBCI_GUI/DataProcessing.pde | 6 +- OpenBCI_GUI/OpenBCI_GUI.pde | 6 +- OpenBCI_GUI/W_EMG.pde | 2 +- OpenBCI_GUI/W_Focus.pde | 29 ++++++--- OpenBCI_GUI/data/bp1.mp3 | Bin 0 -> 2165781 bytes OpenBCI_GUI/data/bp2.mp3 | Bin 0 -> 2041647 bytes OpenBCI_GUI/data/bp3.mp3 | Bin 0 -> 1891182 bytes OpenBCI_GUI/data/bp4.mp3 | Bin 0 -> 1771437 bytes OpenBCI_GUI/data/bp5.mp3 | Bin 0 -> 1568309 bytes 11 files changed, 114 insertions(+), 14 deletions(-) create mode 100644 OpenBCI_GUI/AuditoryNeurofeedback.pde create mode 100644 OpenBCI_GUI/data/bp1.mp3 create mode 100644 OpenBCI_GUI/data/bp2.mp3 create mode 100644 OpenBCI_GUI/data/bp3.mp3 create mode 100644 OpenBCI_GUI/data/bp4.mp3 create mode 100644 OpenBCI_GUI/data/bp5.mp3 diff --git a/OpenBCI_GUI/AuditoryNeurofeedback.pde b/OpenBCI_GUI/AuditoryNeurofeedback.pde new file mode 100644 index 000000000..294262d1b --- /dev/null +++ b/OpenBCI_GUI/AuditoryNeurofeedback.pde @@ -0,0 +1,84 @@ +//Used in the Focus Widget to provide auditory neurofeedback +//Adjust amplitude of calming audio samples using normalized band power data + +import processing.sound.*; + +class AuditoryNeurofeedback { + + private int x, y, w, h; + private ControlP5 localCP5; + private Button startStopButton; + private SoundFile[] soundFiles; + //There will always be 5 band powers, and 5 possible concurrent audio files for playback + private final int numSoundFiles = 5; + + AuditoryNeurofeedback(int _x, int _y, int _w, int _h) { + + localCP5 = new ControlP5(ourApplet); + localCP5.setGraphics(ourApplet, 0,0); + localCP5.setAutoDraw(false); + createStartStopButton(_x, _y, _w, _h); + + soundFiles = new SoundFile[numSoundFiles]; + for (int i = 0; i < numSoundFiles; i++) { + soundFiles[i] = new SoundFile(ourApplet, "bp" + (i+1) + ".mp3"); + //soundFiles[i].amp(0.7); + } + } + + public void update(double[] bandPowers) { + for (int i = numSoundFiles-1; i >= 0; i--) { + float val = map((float)bandPowers[i], 0.0, 1.0, 0.1, 0.7); + soundFiles[i].amp(val); + } + + } + + public void update(float val) { + if (val > .55) { + val = .55; + } + for (int i = 0; i < numSoundFiles; i++) { + soundFiles[i].amp(val); + } + } + + public void draw() { + localCP5.draw(); + } + + public void screenResized(int _x, int _y) { + localCP5.setGraphics(ourApplet, 0, 0); + startStopButton.setPosition(_x, _y); + } + + public void killAudio() { + for (int i = 0; i < numSoundFiles; i++) { + soundFiles[i].stop(); + } + } + + private void createStartStopButton(int _x, int _y, int _w, int _h) { + //This is a generalized createButton method that allows us to save code by using a few patterns and method overloading + startStopButton = createButton(localCP5, "startStopButton", "Toggle Neurofeedback", _x, _y, _w, _h, p4, 14, colorNotPressed, OPENBCI_DARKBLUE); + //Set the border color explicitely + startStopButton.setBorderColor(OBJECT_BORDER_GREY); + //For this button, only call the callback listener on mouse release + startStopButton.onRelease(new CallbackListener() { + public void controlEvent(CallbackEvent theEvent) { + //If using a TopNav object, ignore interaction with widget object (ex. widgetTemplateButton) + if (!topNav.configSelector.isVisible && !topNav.layoutSelector.isVisible) { + if (soundFiles[0].isPlaying()) { + killAudio(); + } else { + for (int i = 0; i < numSoundFiles; i++) { + soundFiles[i].loop(); + } + } + } + } + }); + startStopButton.setDescription("Here is the description for this UI object."); + } + +} \ No newline at end of file diff --git a/OpenBCI_GUI/ControlPanel.pde b/OpenBCI_GUI/ControlPanel.pde index 78fdeb9b3..144fb7c85 100644 --- a/OpenBCI_GUI/ControlPanel.pde +++ b/OpenBCI_GUI/ControlPanel.pde @@ -2786,6 +2786,7 @@ class InitBox { controlPanel.dataLogBoxGanglion.setSessionTextfieldText(directoryManager.getFileNameDateTime()); controlPanel.dataLogBoxGalea.setSessionTextfieldText(directoryManager.getFileNameDateTime()); controlPanel.wifiBox.setStaticIPTextfield(wifi_ipAddress); + w_focus.killAuditoryFeedback(); haltSystem(); } } diff --git a/OpenBCI_GUI/DataProcessing.pde b/OpenBCI_GUI/DataProcessing.pde index 49bcdcd1b..7dee70a1e 100644 --- a/OpenBCI_GUI/DataProcessing.pde +++ b/OpenBCI_GUI/DataProcessing.pde @@ -64,12 +64,12 @@ void processNewData() { } } -void initializeFFTObjects(FFT[] fftBuff, float[][] dataProcessingRawBuffer, int Nfft, float fs_Hz) { +void initializeFFTObjects(ddf.minim.analysis.FFT[] fftBuff, float[][] dataProcessingRawBuffer, int Nfft, float fs_Hz) { float[] fooData; for (int Ichan=0; Ichan < nchan; Ichan++) { //make the FFT objects...Following "SoundSpectrum" example that came with the Minim library - fftBuff[Ichan].window(FFT.HAMMING); + fftBuff[Ichan].window(ddf.minim.analysis.FFT.HAMMING); //do the FFT on the initial data if (isFFTFiltered == true) { @@ -237,7 +237,7 @@ class DataProcessing { } } - public void process(float[][] data_forDisplay_uV, FFT[] fftData) { //holds the FFT (frequency spectrum) of the latest data + public void process(float[][] data_forDisplay_uV, ddf.minim.analysis.FFT[] fftData) { //holds the FFT (frequency spectrum) of the latest data float prevFFTdata[] = new float[fftBuff[0].specSize()]; diff --git a/OpenBCI_GUI/OpenBCI_GUI.pde b/OpenBCI_GUI/OpenBCI_GUI.pde index 92c918415..98e2e1976 100644 --- a/OpenBCI_GUI/OpenBCI_GUI.pde +++ b/OpenBCI_GUI/OpenBCI_GUI.pde @@ -285,7 +285,7 @@ DirectoryManager directoryManager; final int navBarHeight = 32; TopNav topNav; -FFT[] fftBuff = new FFT[nchan]; //from the minim library +ddf.minim.analysis.FFT[] fftBuff = new ddf.minim.analysis.FFT[nchan]; //from the minim library boolean isFFTFiltered = true; //yes by default ... this is used in dataProcessing.pde to determine which uV array feeds the FFT calculation //------------------------------------------------------------------------ @@ -695,7 +695,7 @@ void initFFTObjectsAndBuffer() { //initialize the FFT objects for (int Ichan=0; Ichan < nchan; Ichan++) { // verbosePrint("Init FFT Buff – " + Ichan); - fftBuff[Ichan] = new FFT(getNfftSafe(), currentBoard.getSampleRate()); + fftBuff[Ichan] = new ddf.minim.analysis.FFT(getNfftSafe(), currentBoard.getSampleRate()); } //make the FFT objects //Attempt initialization. If error, print to console and exit function. @@ -912,7 +912,7 @@ void systemInitSession() { void updateToNChan(int _nchan) { nchan = _nchan; settings.slnchan = _nchan; //used in SoftwareSettings.pde only - fftBuff = new FFT[nchan]; //reinitialize the FFT buffer + fftBuff = new ddf.minim.analysis.FFT[nchan]; //reinitialize the FFT buffer println("OpenBCI_GUI: Channel count set to " + str(nchan)); } diff --git a/OpenBCI_GUI/W_EMG.pde b/OpenBCI_GUI/W_EMG.pde index 53eebf4a2..89b5491ac 100644 --- a/OpenBCI_GUI/W_EMG.pde +++ b/OpenBCI_GUI/W_EMG.pde @@ -268,7 +268,7 @@ class W_emg extends Widget { public void process( float[][] data_forDisplay_uV, //this data has been filtered and is ready for plotting on the screen - FFT[] fftData) { //holds the FFT (frequency spectrum) of the latest data + ddf.minim.analysis.FFT[] fftData) { //holds the FFT (frequency spectrum) of the latest data //for example, you could loop over each EEG channel to do some sort of time-domain processing //using the sample values that have already been filtered, as will be plotted on the display diff --git a/OpenBCI_GUI/W_Focus.pde b/OpenBCI_GUI/W_Focus.pde index 8a1e282eb..85ff9b969 100644 --- a/OpenBCI_GUI/W_Focus.pde +++ b/OpenBCI_GUI/W_Focus.pde @@ -25,10 +25,12 @@ class W_Focus extends Widget { //to see all core variables/methods of the Widget class, refer to Widget.pde //put your custom variables here... - private ControlP5 focus_cp5; - private Button widgetTemplateButton; + //private ControlP5 focus_cp5; + //private Button widgetTemplateButton; private ChannelSelect focusChanSelect; private boolean prevChanSelectIsVisible = false; + private AuditoryNeurofeedback auditoryNeurofeedback; + private Grid dataGrid; private final int numTableRows = 6; @@ -71,6 +73,8 @@ class W_Focus extends Widget { focusChanSelect = new ChannelSelect(pApplet, this, x, y, w, navH, "FocusChannelSelect"); focusChanSelect.activateAllButtons(); + auditoryNeurofeedback = new AuditoryNeurofeedback(x, y, 120, navBarHeight); + exgChannels = currentBoard.getEXGChannels(); channelCount = currentBoard.getNumEXGChannels(); dataArray = new double[channelCount][]; @@ -98,9 +102,9 @@ class W_Focus extends Widget { dataGrid.setString("Gamma (30-45Hz)", 5, 0); //Instantiate local cp5 for this box. This allows extra control of drawing cp5 elements specifically inside this class. - focus_cp5 = new ControlP5(ourApplet); - focus_cp5.setGraphics(ourApplet, 0,0); - focus_cp5.setAutoDraw(false); + //focus_cp5 = new ControlP5(ourApplet); + //focus_cp5.setGraphics(ourApplet, 0,0); + //focus_cp5.setAutoDraw(false); //create our focus graph updateGraphDims(); @@ -154,7 +158,8 @@ class W_Focus extends Widget { } //This draws all cp5 objects in the local instance - focus_cp5.draw(); + //focus_cp5.draw(); + auditoryNeurofeedback.draw(); //Draw the graph focusBar.draw(); @@ -166,7 +171,7 @@ class W_Focus extends Widget { super.screenResized(); //calls the parent screenResized() method of Widget (DON'T REMOVE) //Very important to allow users to interact with objects after app resize - focus_cp5.setGraphics(ourApplet, 0, 0); + //focus_cp5.setGraphics(ourApplet, 0, 0); resizeTable(); @@ -174,6 +179,7 @@ class W_Focus extends Widget { //widgetTemplateButton.setPosition(x + w/2 - widgetTemplateButton.getWidth()/2, y + h/2 - widgetTemplateButton.getHeight()/2); updateStatusCircle(); + auditoryNeurofeedback.screenResized((int)xc, (int)yc); updateGraphDims(); focusBar.screenResized(graphX, graphY, graphW, graphH); @@ -260,9 +266,14 @@ class W_Focus extends Widget { //Left array is Averages, right array is Standard Deviations. Update values using Averages. updateBandPowerTableValues(bands.getLeft()); + //Send band power data to AuditoryNeurofeedback class + //auditoryNeurofeedback.update(bands.getLeft()); + //Keep this here double prediction = mlModel.predict(featureVector); //println("Concentration: " + prediction); + + auditoryNeurofeedback.update((float)prediction); return prediction; @@ -387,6 +398,10 @@ class W_Focus extends Widget { public int getMetricExceedsThreshold() { return predictionExceedsThreshold ? 1 : 0; } + + public void killAuditoryFeedback() { + auditoryNeurofeedback.killAudio(); + } }; //end of class //The following global functions are used by the Focus widget dropdowns. 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