static void Main(string[] args)
{
// use synthetic board for demo
BoardShim.enable_dev_board_logger();
BrainFlowInputParams input_params = new BrainFlowInputParams();
int board_id = parse_args(args, input_params);
BoardShim board_shim = new BoardShim(board_id, input_params);
int sampling_rate = BoardShim.get_sampling_rate(board_shim.get_board_id());
int nfft = DataFilter.get_nearest_power_of_two(sampling_rate);
int[] eeg_channels = BoardShim.get_eeg_channels(board_shim.get_board_id());
board_shim.prepare_session();
board_shim.start_stream(3600);
System.Threading.Thread.Sleep(10000);
board_shim.stop_stream();
double[,] data = board_shim.get_board_data();
board_shim.release_session();
Tuple <double[], double[]> bands = DataFilter.get_avg_band_powers(data, eeg_channels, sampling_rate, true);
double[] feature_vector = bands.Item1.Concatenate(bands.Item2);
BrainFlowModelParams model_params = new BrainFlowModelParams((int)BrainFlowMetrics.CONCENTRATION, (int)BrainFlowClassifiers.REGRESSION);
MLModel concentration = new MLModel(model_params);
concentration.prepare();
Console.WriteLine("Concentration: " + concentration.predict(feature_vector));
concentration.release();
}
private void OnDestroy()
{
if (board_shim != null)
{
try
{
board_shim.release_session();
concentration.release();
}
catch (BrainFlowException e)
{
Debug.Log(e);
}
Debug.Log("Brainflow streaming was stopped");
}
}
static void Main(string[] args)
{
try
{
BoardShim.enable_dev_board_logger();
BrainFlowInputParams input_params = new BrainFlowInputParams();
int board_id = (int)BoardIds.MINDROVE_WIFI_BOARD;//= parse_args(args, input_params);
board_shim = new BoardShim(board_id, input_params);
board_shim.prepare_session();
board_shim.start_stream(); // use this for default options
//board_shim.start_stream(450000, "file://file_stream.csv:w");
board_shim.config_board(BoardShim.MindroveWifiConfigMode.EEG_MODE);
BrainFlowModelParams concentration_params = new BrainFlowModelParams((int)BrainFlowMetrics.CONCENTRATION, (int)BrainFlowClassifiers.REGRESSION);
concentration = new MLModel(concentration_params);
concentration.prepare();
sampling_rate = BoardShim.get_sampling_rate(board_id);
eeg_channels = BoardShim.get_eeg_channels(board_id);
counter_idx = BoardShim.get_package_num_channel(board_id);
}
catch (BrainFlowException ex)
{
Console.WriteLine(ex);
}
while (Update() >= 0)
{
}
if (board_shim != null)
{
try
{
board_shim.release_session();
concentration.release();
}
catch (BrainFlowException e)
{
Console.WriteLine(e);
}
Console.WriteLine("Brainflow streaming was stopped");
}
Console.ReadLine();
}
