/// <summary>
/// Get the current windowing type for band power calculation
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="type">windowing type enum from IEE_WindowingTypes (default: IEE_HANNING)</param>
/// <returns>EDK_ERROR_CODE</returns>
public void IEE_FFTGetWindowingType(UInt32 userId, EdkDll.IEE_WindowingTypes type)
{
errorHandler(EdkDll.IEE_FFTGetWindowingType(userId, type));
}
/// <summary>
/// Query the number of channels of available sensor contact quality data
/// </summary>
/// <returns>number of channels for which contact quality data is available</returns>
public Int32 GetNumContactQualityChannels()
{
return(EdkDll.ES_GetNumContactQualityChannels(hEmoState));
}
/// <summary>
/// Set the training control flag for Cognitiv training
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="control">pre-defined Cognitiv training control</param>
public void CognitivSetTrainingControl(UInt32 userId, EdkDll.EE_CognitivTrainingControl_t control)
{
errorHandler(EdkDll.EE_CognitivSetTrainingControl(userId, control));
}
/// <summary>
/// Set the current facial expression for Expressiv training
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="action">which facial expression would like to be trained</param>
public void ExpressivSetTrainingAction(UInt32 userId, EdkDll.EE_ExpressivAlgo_t action)
{
errorHandler(EdkDll.EE_ExpressivSetTrainingAction(userId, action));
}
/// <summary>
/// Query the eyelids state of the user
/// </summary>
/// <remarks>
/// The left and right eyelid state are stored in the parameter leftEye and rightEye
/// respectively. They are floating point values ranging from 0.0 to 1.0.
/// 0.0 indicates that the eyelid is fully opened while 1.0 indicates that the
/// eyelid is fully closed.
/// </remarks>
/// <param name="leftEye">the left eyelid state (0.0 to 1.0)</param>
/// <param name="rightEye">the right eyelid state (0.0 to 1.0)</param>
public void FacialExpressionGetEyelidState(out Single leftEye, out Single rightEye)
{
EdkDll.IS_FacialExpressionGetEyelidState(hEmoState, out leftEye, out rightEye);
}
/// <summary>
/// Get a list of vital algorithms of specific suite from optimization parameter
/// </summary>
/// <param name="suite">suite that you are interested in</param>
/// <returns>returns a list of vital algorithm composed of EE_ExpressivAlgo_t, EE_AffectivAlgo_t or EE_CognitivAction_t depending on the suite parameter</returns>
public UInt32 GetVitalAlgorithm(EdkDll.EE_EmotivSuite_t suite)
{
UInt32 vitalAlgorithmBitVectorOut = 0;
EmoEngine.errorHandler(EdkDll.EE_OptimizationGetVitalAlgorithm(hOptimizationParam, suite, out vitalAlgorithmBitVectorOut));
return vitalAlgorithmBitVectorOut;
}
/// <summary>
/// Gets the current skill rating for particular MentalCommand actions of the user
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="action">a particular action of IEE_MentalCommandAction_t contant</param>
/// <returns>receives the action skill rating [from 0.0 to 1.0]</returns>
public Single MentalCommandGetActionSkillRating(UInt32 userId, EdkDll.IEE_MentalCommandAction_t action)
{
Single actionSkillRatingOut = 0.0F;
errorHandler(EdkDll.IEE_MentalCommandGetActionSkillRating(userId, action, out actionSkillRatingOut));
return actionSkillRatingOut;
}
/// <summary>
/// Query whether the eyes of the user are opened at the time the EmoState is captured.
/// </summary>
/// <returns>eye open status (true: eyes open, false: eyes closed)</returns>
public Boolean FacialExpressionIsEyesOpen()
{
return(EdkDll.IS_FacialExpressionIsEyesOpen(hEmoState));
}
/// <summary>
/// Set the current facial expression for FacialExpression training
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="action">which facial expression would like to be trained</param>
public void FacialExpressionSetTrainingAction(UInt32 userId, EdkDll.IEE_FacialExpressionAlgo_t action)
{
errorHandler(EdkDll.IEE_FacialExpressionSetTrainingAction(userId, action));
}
/// <summary>
/// Set the control flag for FacialExpression training
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="control">pre-defined control command</param>
public void FacialExpressionSetTrainingControl(UInt32 userId, EdkDll.IEE_FacialExpressionTrainingControl_t control)
{
errorHandler(EdkDll.IEE_FacialExpressionSetTrainingControl(userId, control));
}
/// <summary>
/// Set threshold for FacialExpression algorithms
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="algoName">FacialExpression algorithm type</param>
/// <param name="thresholdName">FacialExpression threshold type</param>
/// <param name="value">threshold value (min: 0 max: 1000)</param>
public void FacialExpressionSetThreshold(UInt32 userId, EdkDll.IEE_FacialExpressionAlgo_t algoName, EdkDll.IEE_FacialExpressionThreshold_t thresholdName, Int32 value)
{
errorHandler(EdkDll.IEE_FacialExpressionSetThreshold(userId, algoName, thresholdName, value));
}
/// <summary>
/// Configures the FacialExpression suite to use either the built-in, universal signature or a personal, trained signature
/// </summary>
/// <remarks>
/// FacialExpression defaults to use its universal signature. This function will fail if IEE_FacialExpressionGetTrainedSignatureAvailable returns false.
/// </remarks>
/// <param name="userId">user ID</param>
/// <param name="sigType">signature type to use</param>
public void FacialExpressionSetSignatureType(UInt32 userId, EdkDll.IEE_FacialExpressionSignature_t sigType)
{
errorHandler(EdkDll.IEE_FacialExpressionSetSignatureType(userId, sigType));
}
/// <summary>
/// Get threshold from FacialExpression algorithms
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="algoName">FacialExpression algorithm type</param>
/// <param name="thresholdName">FacialExpression threshold type</param>
/// <returns>receives threshold value</returns>
public Int32 FacialExpressionGetThreshold(UInt32 userId, EdkDll.IEE_FacialExpressionAlgo_t algoName, EdkDll.IEE_FacialExpressionThreshold_t thresholdName)
{
Int32 valueOut = 0;
errorHandler(EdkDll.IEE_FacialExpressionGetThreshold(userId, algoName, thresholdName, out valueOut));
return valueOut;
}
/// <summary>
/// Query the contact quality of all the electrodes in one single call
/// </summary>
/// <remarks>
/// The contact quality will be stored in the array, contactQuality, passed to the function.
/// The value stored in contactQuality[0] is identical to the result returned by
/// IS_GetContactQuality(state, 0)
/// The value stored in contactQuality[1] is identical to the result returned by
/// IS_GetContactQuality(state, 1). etc.
/// The ordering of the array is consistent with the ordering of the logical input
/// channels in IEE_InputChannels_enum.
/// </remarks>
/// <returns>Number of signal quality values copied to the contactQuality array.</returns>
public EdkDll.IEE_EEG_ContactQuality_t[] GetContactQualityFromAllChannels()
{
EdkDll.IEE_EEG_ContactQuality_t[] contactQuality;
EdkDll.IS_GetContactQualityFromAllChannels(hEmoState, out contactQuality);
return(contactQuality);
}
/// <summary>
/// Set the type of MentalCommand action to be trained
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="action">which action would like to be trained</param>
public void MentalCommandSetTrainingAction(UInt32 userId, EdkDll.IEE_MentalCommandAction_t action)
{
errorHandler(EdkDll.IEE_MentalCommandSetTrainingAction(userId, action));
}
/// <summary>
/// Get the level of charge remaining in the headset battery
/// </summary>
/// <param name="chargeLevel">the current level of charge in the headset battery</param>
/// <param name="maxChargeLevel">the maximum level of charge in the battery</param>
public void GetBatteryChargeLevel(out Int32 chargeLevel, out Int32 maxChargeLevel)
{
EdkDll.IS_GetBatteryChargeLevel(hEmoState, out chargeLevel, out maxChargeLevel);
}
/// <summary>
/// Set the training control flag for MentalCommand training
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="control">pre-defined MentalCommand training control</param>
public void MentalCommandSetTrainingControl(UInt32 userId, EdkDll.IEE_MentalCommandTrainingControl_t control)
{
errorHandler(EdkDll.IEE_MentalCommandSetTrainingControl(userId, control));
}
/// <summary>
/// Query whether the user is looking down at the time the EmoState is captured.
/// </summary>
/// <returns>eyes position (true: looking down, false: not looking down)</returns>
public Boolean FacialExpressionIsLookingDown()
{
return(EdkDll.IS_FacialExpressionIsLookingDown(hEmoState));
}
/// <summary>
/// Returns the clench extent of the user (Obsolete function)
/// </summary>
/// <returns>clench extent value (0.0 to 1.0)</returns>
public Single ExpressivGetClenchExtent()
{
return(EdkDll.ES_ExpressivGetClenchExtent(hEmoState));
}
/// <summary>
/// Query whether the signal is too noisy for Expressiv detection to be active
/// </summary>
/// <param name="type">Expressiv detection type</param>
/// <returns>detection state (false: Not Active, true: Active)</returns>
public Boolean ExpressivIsActive(EdkDll.EE_ExpressivAlgo_t type)
{
return EdkDll.ES_ExpressivIsActive(hEmoState, type);
}
/// <summary>
/// Constructor
/// </summary>
public EmoState()
{
hEmoState = EdkDll.ES_Create();
}
/// <summary>
/// Gets the current skill rating for particular Cognitiv actions of the user
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="action">a particular action of EE_CognitivAction_t contant</param>
/// <returns>receives the action skill rating [from 0.0 to 1.0]</returns>
public Single CognitivGetActionSkillRating(UInt32 userId, EdkDll.EE_CognitivAction_t action)
{
Single actionSkillRatingOut = 0.0F;
errorHandler(EdkDll.EE_CognitivGetActionSkillRating(userId, action, out actionSkillRatingOut));
return actionSkillRatingOut;
}
/// <summary>
/// Returns the detected lower face Expressiv action of the user
/// </summary>
/// <returns>pre-defined Expressiv action types</returns>
public EdkDll.EE_ExpressivAlgo_t ExpressivGetLowerFaceAction()
{
return(EdkDll.ES_ExpressivGetLowerFaceAction(hEmoState));
}
/// <summary>
/// Configures the Expressiv suite to use either the built-in, universal signature or a personal, trained signature
/// </summary>
/// <remarks>
/// Expressiv defaults to use its universal signature. This function will fail if EE_ExpressivGetTrainedSignatureAvailable returns false.
/// </remarks>
/// <param name="userId">user ID</param>
/// <param name="sigType">signature type to use</param>
public void ExpressivSetSignatureType(UInt32 userId, EdkDll.EE_ExpressivSignature_t sigType)
{
errorHandler(EdkDll.EE_ExpressivSetSignatureType(userId, sigType));
}
/// <summary>
/// Returns the detected lower face Expressiv action power of the user
/// </summary>
/// <returns>power value (0.0 to 1.0)</returns>
public Single ExpressivGetLowerFaceActionPower()
{
return(EdkDll.ES_ExpressivGetLowerFaceActionPower(hEmoState));
}
/// <summary>
/// Returns a struct containing details about the specified EEG channel's headset
/// </summary>
/// <param name="channelId">channel identifier</param>
/// <returns>provides detailed sensor location and other info</returns>
public EdkDll.InputSensorDescriptor_t HeadsetGetSensorDetails(EdkDll.EE_InputChannels_t channelId)
{
EdkDll.InputSensorDescriptor_t descriptorOut;
errorHandler(EdkDll.EE_HeadsetGetSensorDetails(channelId, out descriptorOut));
return descriptorOut;
}
/// <summary>
/// Query whether the signal is too noisy for Expressiv detection to be active
/// </summary>
/// <param name="type">Expressiv detection type</param>
/// <returns>detection state (false: Not Active, true: Active)</returns>
public Boolean ExpressivIsActive(EdkDll.EE_ExpressivAlgo_t type)
{
return(EdkDll.ES_ExpressivIsActive(hEmoState, type));
}
/// <summary>
/// Return whether the headset has been put on correctly or not
/// </summary>
/// <remarks>
/// If the headset cannot not be detected on the head, then signal quality will not report
/// any results for all the channels
/// </remarks>
/// <returns>int (1: On, 0: Off)</returns>
public Int32 GetHeadsetOn()
{
return(EdkDll.ES_GetHeadsetOn(hEmoState));
}
/// <summary>
/// Returns short term excitement level of the user
/// </summary>
/// <returns>excitement level (0.0 to 1.0)</returns>
public Single AffectivGetExcitementShortTermScore()
{
return(EdkDll.ES_AffectivGetExcitementShortTermScore(hEmoState));
}
/// <summary>
/// Query the contact quality of a specific EEG electrode
/// </summary>
/// <param name="electroIdx">The index of the electrode for query</param>
/// <returns>Enumerated value that characterizes the EEG electrode contact for the specified input channel</returns>
public EdkDll.IEE_EEG_ContactQuality_t GetContactQuality(Int32 electroIdx)
{
return(EdkDll.IS_GetContactQuality(hEmoState, electroIdx));
}
/// <summary>
/// Query whether the signal is too noisy for Affectiv detection to be active
/// </summary>
/// <param name="type">Affectiv detection type</param>
/// <returns>detection state (false: Not Active, true: Active)</returns>
public Boolean AffectivIsActive(EdkDll.EE_AffectivAlgo_t type)
{
return(EdkDll.ES_AffectivIsActive(hEmoState, type));
}
/// <summary>
/// Query of the current wireless signal strength
/// </summary>
/// <returns>
/// wireless signal strength [No Signal, Bad, Fair, Good, Excellent].
/// </returns>
public EdkDll.IEE_SignalStrength_t GetWirelessSignalStatus()
{
return(EdkDll.IS_GetWirelessSignalStatus(hEmoState));
}
/// <summary>
/// Returns frustration level of the user
/// </summary>
/// <returns>frustration level (0.0 to 1.0)</returns>
public Single AffectivGetFrustrationScore()
{
return(EdkDll.ES_AffectivGetFrustrationScore(hEmoState));
}
/// <summary>
/// Query whether the user is winking right at the time the EmoState is captured.
/// </summary>
/// <returns>right wink status (true: wink, false: not wink)</returns>
public Boolean FacialExpressionIsRightWink()
{
return(EdkDll.IS_FacialExpressionIsRightWink(hEmoState));
}
/// <summary>
/// Returns engagement/boredom level of the user
/// </summary>
/// <returns>engagement/boredom level (0.0 to 1.0)</returns>
public Single AffectivGetEngagementBoredomScore()
{
return(EdkDll.ES_AffectivGetEngagementBoredomScore(hEmoState));
}
/// <summary>
/// Copy constructor
/// </summary>
/// <param name="es">EmoState to be copied</param>
public EmoState(EmoState es)
{
this.hEmoState = EdkDll.IS_Create();
EdkDll.IS_Copy(this.hEmoState, es.GetHandle());
}
/// <summary>
/// Returns the detected Cognitiv action of the user
/// </summary>
/// <returns>Cognitiv action type</returns>
public EdkDll.EE_CognitivAction_t CognitivGetCurrentAction()
{
return(EdkDll.ES_CognitivGetCurrentAction(hEmoState));
}
/// <summary>
/// Query whether the user is looking right at the time the EmoState is captured with EPOC/EPOC+ headset.
/// </summary>
/// <returns>return eye position (1: looking right, 0: not looking right)</returns>
public Int32 FacialExpressionIsLookingRight()
{
return(EdkDll.IS_FacialExpressionIsLookingRight(hEmoState));
}
/// <summary>
/// Returns the detected Cognitiv action power of the user
/// </summary>
/// <returns>Cognitiv action power (0.0 to 1.0)</returns>
public Single CognitivGetCurrentActionPower()
{
return(EdkDll.ES_CognitivGetCurrentActionPower(hEmoState));
}
/// <summary>
/// Query whether the signal is too noisy for Affectiv detection to be active
/// </summary>
/// <param name="type">Affectiv detection type</param>
/// <returns>detection state (false: Not Active, true: Active)</returns>
public Boolean AffectivIsActive(EdkDll.EE_AffectivAlgo_t type)
{
return EdkDll.ES_AffectivIsActive(hEmoState, type);
}
/// <summary>
/// Query whether the signal is too noisy for Cognitiv detection to be active
/// </summary>
/// <returns>detection state (false: Not Active, true: Active)</returns>
public Boolean CognitivIsActive()
{
return(EdkDll.ES_CognitivIsActive(hEmoState));
}
/// <summary>
/// Resets all settings and user-specific profile data for the specified detection suite
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="suite">detection suite (Expressiv, Affectiv, or Cognitiv)</param>
/// <param name="detectionBitVector">identifies specific detections. Set to zero for all detections.</param>
public void ResetDetection(UInt32 userId, EdkDll.EE_EmotivSuite_t suite, UInt32 detectionBitVector)
{
errorHandler(EdkDll.EE_ResetDetection(userId, suite, detectionBitVector));
}
/// <summary>
/// Check whether two states are with identical 'emotiv' state
/// </summary>
/// <param name="state">EmoState</param>
/// <returns>true: Equal, false: Different</returns>
public Boolean AffectivEqual(EmoState state)
{
return(EdkDll.ES_AffectivEqual(GetHandle(), state.GetHandle()));
}
/// <summary>
/// Set a list of vital algorithms of specific suite to optimization parameter
/// </summary>
/// <param name="suite">suite that you are interested in</param>
/// <param name="vitalAlgorithmBitVector">a list of vital algorithm composed of EE_ExpressivAlgo_t, EE_AffectivAlgo_t or EE_CognitivAction_t depended on the suite parameter passed in</param>
public void SetVitalAlgorithm(EdkDll.EE_EmotivSuite_t suite, UInt32 vitalAlgorithmBitVector)
{
EmoEngine.errorHandler(EdkDll.EE_OptimizationSetVitalAlgorithm(hOptimizationParam, suite, vitalAlgorithmBitVector));
}
/// <summary>
/// Check whether two states are with identical Expressiv state, i.e. are both state representing the same facial expression
/// </summary>
/// <param name="state">EmoState</param>
/// <returns>true: Equal, false: Different</returns>
public Boolean ExpressivEqual(EmoState state)
{
return(EdkDll.ES_ExpressivEqual(GetHandle(), state.GetHandle()));
}
/// <summary>
/// Set the type of Cognitiv action to be trained
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="action">which action would like to be trained</param>
public void CognitivSetTrainingAction(UInt32 userId, EdkDll.EE_CognitivAction_t action)
{
errorHandler(EdkDll.EE_CognitivSetTrainingAction(userId, action));
}
/// <summary>
/// Check whether two states are with identical Cognitiv state
/// </summary>
/// <param name="state">EmoState</param>
/// <returns>true: Equal, false: Different</returns>
public Boolean CognitivEqual(EmoState state)
{
return(EdkDll.ES_CognitivEqual(GetHandle(), state.GetHandle()));
}
/// <summary>
/// Get threshold from Expressiv algorithms
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="algoName">Expressiv algorithm type</param>
/// <param name="thresholdName">Expressiv threshold type</param>
/// <returns>receives threshold value</returns>
public Int32 ExpressivGetThreshold(UInt32 userId, EdkDll.EE_ExpressivAlgo_t algoName, EdkDll.EE_ExpressivThreshold_t thresholdName)
{
Int32 valueOut = 0;
errorHandler(EdkDll.EE_ExpressivGetThreshold(userId, algoName, thresholdName, out valueOut));
return valueOut;
}
/// <summary>
/// Check whether two states are with identical EmoEngine state.
/// </summary>
/// <remarks>
/// This function is comparing the time since EmoEngine start,
/// the wireless signal strength and the signal quality of different channels
/// </remarks>
/// <param name="state">EmoState</param>
/// <returns>true: Equal, false: Different</returns>
public Boolean EmoEngineEqual(EmoState state)
{
return(EdkDll.ES_EmoEngineEqual(GetHandle(), state.GetHandle()));
}
/// <summary>
/// Set threshold for Expressiv algorithms
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="algoName">Expressiv algorithm type</param>
/// <param name="thresholdName">Expressiv threshold type</param>
/// <param name="value">threshold value (min: 0 max: 1000)</param>
public void ExpressivSetThreshold(UInt32 userId, EdkDll.EE_ExpressivAlgo_t algoName, EdkDll.EE_ExpressivThreshold_t thresholdName, Int32 value)
{
errorHandler(EdkDll.EE_ExpressivSetThreshold(userId, algoName, thresholdName, value));
}
/// <summary>
/// Check whether two EmoStateHandles are identical
/// </summary>
/// <param name="a">EmoState</param>
/// <param name="b">EmoState</param>
/// <returns></returns>
public Boolean Equals(EmoState a, EmoState b)
{
return(EdkDll.ES_Equal(a.GetHandle(), b.GetHandle()));
}
/// <summary>
/// Set the control flag for Expressiv training
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="control">pre-defined control command</param>
public void ExpressivSetTrainingControl(UInt32 userId, EdkDll.EE_ExpressivTrainingControl_t control)
{
errorHandler(EdkDll.EE_ExpressivSetTrainingControl(userId, control));
}
/// <summary>
/// Return the time since EmoEngine has been successfully connected to the headset
/// </summary>
/// <remarks>
/// If the headset is disconnected from EmoEngine due to low battery or weak
/// wireless signal, the time will be reset to zero.
/// </remarks>
/// <returns>time in second</returns>
public Single GetTimeFromStart()
{
return(EdkDll.ES_GetTimeFromStart(hEmoState));
}
/// <summary>
/// Query whether the signal is too noisy for Expressiv detection to be active
/// </summary>
/// <param name="type">Expressiv detection type</param>
/// <returns>detection state (false: Not Active, true: Active)</returns>
public Boolean FacialExpressionIsActive(EdkDll.IEE_FacialExpressionAlgo_t type)
{
return EdkDll.IS_FacialExpressionIsActive(hEmoState, type);
}
/// <summary>
/// Get averge band power values for a channel
/// </summary>
/// <param name="userId">user ID</param>
/// <param name="channel">channel that is interested in</param>
/// <param name="theta">theta band value (4-8 Hz)</param>
/// <param name="alpha">alpha band value (8-12 Hz)</param>
/// <param name="low_beta">low-beta value (12-16 Hz)</param>
/// <param name="high_beta">high-beta value (16-25 Hz)</param>
/// <param name="gamma">gamma value (25-45 Hz)</param>
/// <returns>EDK_ERROR_CODE</returns>
public Int32 IEE_GetAverageBandPowers(UInt32 userId, EdkDll.IEE_DataChannel_t channel, Double[] theta, Double[] alpha, Double[] low_beta, Double[] high_beta, Double[] gamma)
{
return EdkDll.IEE_GetAverageBandPowers(userId, channel, theta, alpha, low_beta, high_beta, gamma);
}
