DatatypeintMuseIO OSC path/muse/eeg/quantizationMuseIO OSC data formatiRange1, 2, 4, 8, 16, 32, 64,128Dropped EEG SamplesNumber of EEG samples dropped from bluetooth connection issues. This applies to all four/six (depending on preset) channels. One dropped sample here indicates one sample has been dropped from each channel.
Position of this message in the message stream indicates where the dropped samples occurred.DatatypeintMuseIO OSC path/muse/eeg/droppedsamplesMuseIO OSC data formatiRange0 - 65535Accelerometer Data. NOTE: If you use the –no-scale command-line option with MuseIO, you get the proprietary raw data, before it is converted to milli-g units. We do not recommend you use this as it may change at any time. Dropped Accelerometer SamplesNumber of accelerometer samples dropped from bluetooth connection issues. This applies to all three axes.
- There may be other problems that also block our ability to operate the Adobe Muse Exported Library file. Below is a list of possible problems. Corruption of a MULIB file which is being opened; Incorrect links to the MULIB file in registry entries. Accidental deletion of the description of the MULIB.
- Send the.mulib file to your team member via email attachment or transfer the file via a USB drive. The recipient of the.mulib file launches Muse, creates a new site, opens the Library panel, and clicks the Import button to import the file containing the swatches to their Library.
To install this widget in Muse double click the file you just download from the email sent by us. File Name is Background video Widgetcreativated.mulib. As soon as you double click on it It will be added to Library Panel In Muse. Library panel can be located from Windows Library in Muse.
One dropped sample here indicates one sample dropped from each axis. Position of this message in the message stream indicates where the dropped samples occurred.DatatypeintMuseIO OSC path/muse/acc/droppedsamplesMuseIO OSC data formatiRange0 - 65535Muse Elements Data. Raw FFTs for Each ChannelFFT stands for Fast Fourier Transform. This computes the power spectral density of each frequency on each channel. Basically, it shows which frequencies make up a signal, and “how much” of each frequency is present.These values are the basis for many of the subsequent DSP values in Muse Elements.Each path contains 129 decimal values with a range of roughly -40.0 to 20.0. Each array represents FFT coefficients (expressed as Power Spectral Density) for each channel, for a frequency range from 0hz-110Hz divided into 129 bins.
We use a Hamming window of 256 samples(at 220Hz), then for the next FFT we slide the window 22 samples over(1/10th of a second). This gives a 90% overlap from one window to the next. These values are emitted at 10Hz. Datatype129 floatsMuseIO OSC Paths/muse/elements/rawfft0/muse/elements/rawfft1/muse/elements/rawfft2/muse/elements/rawfft3MuseIO OSC Data FormatAll presets: fffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffMuseIO message contents129 coefficients representing the logarithm of Power Spectral density for frequencies in the range of 0-110HzUnitsdBRange0.0 - 1682.815 or 0 - 1023 with -no-scale flagSampling rateApproximately -40.0 to 20.0Understanding Frequency Bins. The FFTs are calculated using a 256 sample window, which gives a transform that has 256 components and is symmetric (i.e.
Mirrored) around an additional component at 0Hz. In other words, you have 128 components, followed by one for 0Hz, and then the mirror image of the same components. This means you need only consider half of them (because the other half are the same, only reflected) plus the one for 0Hz at the centre, which gives you 129 in total.To get the frequency resolution for the bins, you can divide the sampling rate by the FFT length, so in the case of Muse: 220/256 0.86Hz/binSo, the zeroth index of the FFT array represents 0Hz, the next index represents 0-0.86Hz, and so on up to 128.0.86 = 110Hz, which is the maximum frequency that our FFT with its 220Hz sampling rate can detect.Absolute Band Powers. MuseIO Paths/muse/elements/lowfreqsabsolute/muse/elements/deltaabsolute/muse/elements/thetaabsolute/muse/elements/alphaabsolute/muse/elements/betaabsolute/muse/elements/gammaabsoluteUnitsBels (B)DatatypefloatsTransmission frequency10 HzMuseIO OSC Data FormatFour channels (electrode sites) for each band power: ffffFrequency Ranges.NameFrequency Rangelowfreqs2.5-6.1Hzdeltaabsolute1-4Hzthetaabsolute4-8Hzalphaabsolute7.5-13Hzbetaabsolute13-30Hzgammaabsolute30-44Hz.
The boundaries of the frequency ranges are inclusive of the end values. Where 2 ranges overlap, a frequency in the overlapping area counts in both ranges.Relative Band Powers. The relative band powers are calculated by dividing the absolute linear-scale power in one band over the sum of the absolute linear-scale powers in all bands. The linear-scale band power can be calculated from the log-scale band power thusly: linear-scale band power = 10^ (log-scale band power).Therefore, the relative band powers can be calculated as percentages of linear-scale band powers in each band. For example:alpharelative = (10^alphaabsolute / (10^alphaabsolute + 10^betaabsolute + 10^deltaabsolute + 10^gammaabsolute + 10^thetaabsolute)). MuseIO OSC Paths/muse/elements/deltarelative/muse/elements/thetarelative/muse/elements/alpharelative/muse/elements/betarelative/muse/elements/gammarelativeUnitsBels (B)DatatypefloatsTransmission frequency10 HzMuseIO OSC Data FormatFour channels (electrode sites) for each band power: ffffFrequency Ranges.NameFrequency Rangedeltarelative1-4Hzthetarelative4-8Hzalpharelative7.5-13Hzbetarelative13-30Hzgammarelative30-44Hz. The boundaries of the frequency ranges are inclusive of the end values.
Where 2 ranges overlap, a frequency in the overlapping area counts in both ranges. The band session score is computed by comparing the current value of a band power to its history.
This current value is mapped to a score between 0 and 1 using a linear function that returns 0 if the current value is equal to or below the 10th percentile of the distribution of band powers, and returns 1 if it’s equal to or above the 90th percentile. Linear scoring between 0 and 1 is done for any value between these two percentiles.Be advised that these scores are based on recent history and it will take a few seconds before having a stable distribution to score the power against. The estimated distribution is continuously updated as long as the headband is on the head. However, every time it’s updated, the newest values are weighted to have more importance than the historical values. This means that eventually old values will not be present anymore in the estimated distribution. The half-life of the estimated distribution at any given point is around 10 s.The score will start being calculated as soon as the SDK has been started and the headband has established a good connection with the skin.
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Whenever the headset loses connection with the head (as determined by the DRL/REF contact quality) the estimated distributions are reset. This means that when the headband is removed, the session data from any previous user will be cleared. MuseIO Paths/muse/elements/deltasessionscore/muse/elements/thetasessionscore/muse/elements/alphasessionscore/muse/elements/betasessionscore/muse/elements/gammasessionscoreUnitsUnitlessDatatypefloatsTransmission frequency10 HzMuseIO OSC Data FormatFour channels (electrode sites) for each band power: ffffFrequency Ranges.NameFrequency RangeDelta Session Score1-4HzTheta Session Score4-8HzAlpha Session Score7.5-13HzBeta Session Score13-30HzGamma Session Score30-44Hz.
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The boundaries of the frequency ranges are inclusive of the end values. Where 2 ranges overlap, a frequency in the overlapping area counts in both ranges. WARNING: The paths in this section are highly experimental and can change with each release – they may even disappear entirely!These are high level values that can be used in applications where you don’t care about building your own algorithms and want to use something that will work out of the box.Note that it will take approximately 1 minute with Muse on the head before these values will start producing something relevant. These values are emitted at 10Hz. Each channel is scored independently for alpha/gamma for mellow/concentration, and the average of the two channels is taken every time. If there is bad data, the previous score is used, but there is always an average of channels. WARNING: This data stream is highly experimental and can change with each release – it may even disappear entirely!/muse/elements/experimental/mellow fThis is based on alpha, but with additional processing to make it more reflective of the user’s experience.This value goes up when you are relaxing, letting go of judgement, letting go of trying to control things, letting go of attachment to outcome, not thinking about anything with a goal, or being without an active task. You are not engaged in strenuous mental processing but still alert to your senses. A ready, waiting state.MuseIO Path/muse/elements/experimental/mellowDatatypefloatUnitsunitless (score)Transmission Frequency10HzRange0.0 - 1.0Battery Data.