public void DoFallDetection(ModelOutput modelOutput, int[] mRow)
{
if (ML.DetectMovingDown(mRow) && (modelOutput.Prediction == 4))
{
fallRegistered = true;
fallWarning();
}
if (fallRegistered)
{
getUpCounter++;
}
if (getUpCounter > 1)
{
if (GetEvent(modelOutput.Score[1]) || GetEvent(modelOutput.Score[2]) || GetEvent(modelOutput.Score[3]))
{
fallNotDetected();
fallRegistered = false;
getUpCounter = 0;
}
else if (getUpCounter == 10)
{
//Fall detected raise alarm
fallDetected();
}
}
}
/// <summary>
/// Called once in a second
/// </summary>
/// <param name="inputRow"></param>
private void DoMachineLearning(int[] inputRow, string file, bool isPredicting)
{
try
{
if (previousInputRow == null)
{
previousInputRow = new int[32];
inputRow.CopyTo(previousInputRow, 0);
return;
}
DateTime dtNow = DateTime.Now;
movementRow = new int[32];
for (int i = 0; i < 32; i++)
{
movementRow[i] = inputRow[i] - previousInputRow[i];
}
if (Properties.Settings.Default.MovementRow)
{
AddInfo(string.Join(",", movementRow));
}
inputRow.CopyTo(previousInputRow, 0);
if (isPredicting)
{
SetUpFallDetection();
ModelOutput modelOutput = ML.Predict(CalibratedInputRow(inputRow), movementRow);
ShowMLPrediction(modelOutput);
fallDetection.DoFallDetection(modelOutput, movementRow);
}
else if (trainingItem != MLTraining.FALLING || ML.DetectMovingDown(movementRow))
{
if (trainingItem == MLTraining.FALLING)
{
AddInfo("Moving down detected");
}
File.AppendAllText(file, (int)trainingItem + "\t" + string.Join("\t", CalibratedInputRow(inputRow)) + "\t" + string.Join("\t", movementRow) + Environment.NewLine);
}
}
catch (Exception ex)
{
AddInfo("Error training: " + ex.Message);
}
}