static int Update()
{
if ((board_shim == null) || (concentration == null))
{
Console.ReadLine();
return(-1);
}
int number_of_data_points = sampling_rate * 4; // 4 second window is recommended for concentration and relaxation calculations
double[,] data = board_shim.get_current_board_data(number_of_data_points);
if (data.GetRow(0).Length < number_of_data_points)
{
// wait for more data
return(0);
}
// prepare feature vector
Tuple <double[], double[]> bands = DataFilter.get_avg_band_powers(data, eeg_channels, sampling_rate, true);
double[] feature_vector = bands.Item1.Concatenate(bands.Item2);
// calc and print concetration level
// for synthetic board this value should be close to 1, because of sin waves ampls and freqs
Console.WriteLine("Concentration: " + concentration.predict(feature_vector));
return(0);
}
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();
}
void Update()
{
if ((board_shim == null) || (concentration == null))
{
Debug.Log("Not initialized");
return;
}
int number_of_data_points = sampling_rate * 4; // 4 second window is recommended for concentration and relaxation calculations
double[,] data = board_shim.get_current_board_data(number_of_data_points);
if (data.GetRow(0).Length < number_of_data_points)
{
// wait for more data
Debug.Log("Not enough data, data available: " + (data.GetRow(0).Length).ToString());
return;
}
// prepare feature vector
Tuple <double[], double[]> bands = DataFilter.get_avg_band_powers(data, eeg_channels, sampling_rate, true);
double[] feature_vector = bands.Item1.Concatenate(bands.Item2);
// calc and print concetration level
// for synthetic board this value should be close to 1, because of sin waves ampls and freqs
Debug.Log("Concentration: " + concentration.predict(feature_vector));
}
public static double predicts(float bpm, float zcr, float spectirr)
{
double p = m.predict(bpm, zcr, spectirr);
return(p);
}
