/// <summary>
/// Gets the singleton instance.
/// Only one instance of this object can be used in the program.
/// Multiple instances can produce java exceptions untreatable in the c# code.
/// </summary>
/// <returns>The singleton instance.</returns>
public static BluetoothConnector getInstance()
{
if (instance == null)
{
instance = new BluetoothConnector();
}
return(instance);
}
public LiveViewForm(BluetoothConnector connector)
{
InitializeComponent();
_connector = connector;
_connector.SubscribeTo(OnMessageReceived, BluetoothCommandResponse.AllPositions);
_creator = new DriveImageCreator();
_bitmap = new Bitmap(image.Width, image.Height);
image.Image = _bitmap;
_shallRefresh = true;
}
public override List <int> EndServiceDiscovery(IAsyncResult ar)
{
if (_sdpQuery == null)
{
throw new InvalidOperationException("BeginGetServiceRecords not called");
}
var list = _sdpQuery.EndQuery(ar);
var portList = BluetoothConnector.ListAllRfcommPortsInRecords(list);
return(portList);
}
List <int> IUsesBluetoothConnectorImplementsServiceLookup.EndServiceDiscovery(IAsyncResult ar)
{
if (_sdpQuery == null)
{
throw new InvalidOperationException("Begin not called.");
}
var records = _sdpQuery.EndQuery(ar);
var ports = BluetoothConnector.ListAllRfcommPortsInRecords(records);
return(ports);
}
public FormDriveControl()
{
InitializeComponent();
_connector = new BluetoothConnector();
_connector.SubscribeTo(_connector_OnMessageReceived, BluetoothCommandResponse.Started,
BluetoothCommandResponse.Status,
BluetoothCommandResponse.TrackReceived);
_connectWorker = new BackgroundWorker();
_connectWorker.DoWork += ConnectWorkerOnDoWork;
_connectWorker.RunWorkerCompleted += ConnectWorkerRunWorkerCompleted;
_discoverWorker = new BackgroundWorker();
_discoverWorker.DoWork += DiscoverWorkerOnDoWork;
_discoverWorker.RunWorkerCompleted += DiscoverWorkerOnRunDiscoverWorkerCompleted;
}
/// <summary>
/// Initializes a new instance of the <see cref="TamabinConnector"/> class.
/// Private construtor to prevent external access, the instance of this object shold be get by
/// <see cref="TamabinConnector.getInstance()"/> method.
/// </summary>
private TamabinConnector()
{
bluetoothConnector = BluetoothConnector.getInstance();
tamabinBluetoothName = null;
}
private void readDataTimer_Tick(object sender, EventArgs e)
{
#region Bluetooth Reconnection Code
#if (PocketPC)
//Start a reconnection thread
foreach (Receiver receiver in this.sensors.Receivers)
{
if (!receiver.Running) //&& (!receiver.Restarting))
{
aMITesActivityLogger.WriteLogComment("Connection broke with " + receiver.ID + ". Restarting");
//reconnectionThreadQuit[receiver.ID] = false;
BluetoothConnector btc=new BluetoothConnector(receiver, this.bluetoothControllers, this.mitesDecoders);
aMITesActivityLogger.WriteLogComment("Initializing reconnection thread");
//ts[receiver.ID] = new Thread(new ThreadStart(btc.Reconnect));
//ts[receiver.ID].Start();
btc.Reconnect();
aMITesActivityLogger.WriteLogComment("Reconnection thread started");
receiver.Restarting = true;
}
else if (receiver.Restarted)
{
aMITesActivityLogger.WriteLogComment("Reconnection completed");
receiver.Restarted = false;
receiver.Restarting = false;
receiver.Running = true;
}
}
#endif
#endregion Bluetooth Reconnection Code
#region Poll All Wockets and MITes and Decode Data
Receiver currentReceiver = null;
try
{
//Poll each CONNECTED receiver channel with the right decoder
foreach (Receiver receiver in this.sensors.Receivers)
{
currentReceiver = receiver;
#if (PocketPC)
if ((receiver.Type == SXML.Constants.RECEIVER_BLUETOOTH) && (receiver.Running == true))
{
if (receiver.Decoder == SXML.Constants.DECODER_MITES)
this.mitesDecoders[receiver.ID].GetSensorData(this.bluetoothControllers[receiver.ID], MITesDecoder.MITES_SENSOR);
else if (receiver.Decoder == SXML.Constants.DECODER_WOCKETS)
this.mitesDecoders[receiver.ID].GetSensorData(this.bluetoothControllers[receiver.ID], MITesDecoder.WOCKETS_SENSOR);
else if (receiver.Decoder == SXML.Constants.DECODER_SPARKFUN)
this.mitesDecoders[receiver.ID].GetSensorData(this.bluetoothControllers[receiver.ID], MITesDecoder.SPARKFUN_SENSOR);
}
else
#endif
if (receiver.Type == SXML.Constants.RECEIVER_USB)
this.mitesDecoders[receiver.ID].GetSensorData(this.mitesControllers[receiver.ID]);
}
if (++ttwcounter == 6000)
{
TextWriter ttw = new StreamWriter("\\Internal Storage\\ts.txt");
ttw.WriteLine(DateTime.Now.ToLongTimeString());
ttw.Close();
ttwcounter = 0;
}
}
//Thrown when there is a Bluetooth failure
//TODO: Make sure no USB failure happening
catch (Exception ex)
{
currentReceiver.Running = false;
//connectionLost = true;
return;
}
//Reset the index of the master decoder and copy all data in order into the master decoder
this.masterDecoder.someMITesDataIndex = 0;
//Only decode running receivers (i.e. with no connection failure)
foreach (Receiver receiver in this.sensors.Receivers)
if (receiver.Running)
this.masterDecoder.MergeDataOrderProperly(this.mitesDecoders[receiver.ID]);
#endregion Poll All Wockets and MITes and Decode Data
#region Poll Builtin Data
#if (PocketPC)
GenericAccelerometerData polledData = null;
if (unprocessedBuiltin == true)
{
this.builtinData.Timestamp = Environment.TickCount;
this.builtinData.Unixtimestamp = UnixTime.GetUnixTime();
polledData = this.builtinData;
}
#endif
#endregion Poll Builtin Data
#region Train in realtime and generate ARFF File
if (IsTraining == true)
{
//We are autotraining each activity after the other
if (AutoTraining == true)
{
//Get current activity to train
string current_activity = ((AXML.Label)((AXML.Category)this.annotation.Categories[0]).Labels[autoTrainingIndex]).Name;
//Check if trained
if (Extractor.IsTrained(current_activity))
{
//store the completed annotation and reset the variables
this.currentRecord.EndDate = DateTime.Now.ToString("yyyy'-'MM'-'dd' 'HH':'mm':'ssK");
this.currentRecord.EndHour = DateTime.Now.Hour;
this.currentRecord.EndMinute = DateTime.Now.Minute;
this.currentRecord.EndSecond = DateTime.Now.Second;
TimeSpan ts = (DateTime.Now - new DateTime(1970, 1, 1, 0, 0, 0));
this.currentRecord.EndUnix = ts.TotalSeconds;
this.annotation.Data.Add(this.currentRecord);
//each time an activity is stopped, rewrite the file on disk, need to backup file to avoid corruption
this.annotation.ToXMLFile();
this.annotation.ToCSVFile();
isExtracting = false;
//Point to the next activity and Calculate the delay to start training
this.startActivityTime = Environment.TickCount + Extractor.Configuration.TrainingWaitTime * 1000;//Constants.TRAINING_GAP;
autoTrainingIndex++;
//If we exceeded the last activity then training is completed
if (autoTrainingIndex == ((AXML.Category)this.annotation.Categories[0]).Labels.Count)
{
this.trainingLabel.Text = "Training Completed";
this.goodTimer.reset();
this.overallTimer.reset();
Thread.Sleep(3000);
EndTraining();
}
else // if there are still activities to train beep twice and reset good timer
{
this.goodTimer.reset();
#if (PocketPC)
PlaySound(@"\Windows\Voicbeep", IntPtr.Zero, (int)(PlaySoundFlags.SND_FILENAME | PlaySoundFlags.SND_SYNC));
PlaySound(@"\Windows\Voicbeep", IntPtr.Zero, (int)(PlaySoundFlags.SND_FILENAME | PlaySoundFlags.SND_SYNC));
#endif
}
}
//if the current activity is not trained and the start time is more that the current time
//then calculate the feature vector
else if (this.startActivityTime < Environment.TickCount) // TRAINING_GAP passed
{
//initialize for extraction
if (isExtracting == false)
{
this.trainingLabel.Text = "Training " + current_activity;
this.goodTimer.start();
//store the current state of the categories
this.currentRecord = new AnnotatedRecord();
this.currentRecord.StartDate = DateTime.Now.ToString("yyyy'-'MM'-'dd' 'HH':'mm':'ssK");
this.currentRecord.StartHour = DateTime.Now.Hour;
this.currentRecord.StartMinute = DateTime.Now.Minute;
this.currentRecord.StartSecond = DateTime.Now.Second;
TimeSpan ts = (DateTime.Now - new DateTime(1970, 1, 1, 0, 0, 0));
this.currentRecord.StartUnix = ts.TotalSeconds;
this.currentRecord.Labels.Add(new AXML.Label(current_activity, "none"));
isExtracting = true;
}
//Extract feature vector from accelerometer data and write an arff line
double lastTimeStamp = Extractor.StoreMITesWindow();
#if (PocketPC)
if ((this.sensors.HasBuiltinSensors) && (polledData != null))
{
//store it in Extractor Buffers as well
lastTimeStamp = Extractor.StoreBuiltinData(polledData);
}
#endif
if (Extractor.GenerateFeatureVector(lastTimeStamp))
{
Extractor.TrainingTime[current_activity] = (int)Extractor.TrainingTime[current_activity] + Extractor.Configuration.OverlapTime;// get it from configuration
string arffSample = Extractor.toString() + "," + current_activity.Replace(' ', '_');
this.tw.WriteLine(arffSample);
this.label8.Text = Extractor.DiscardedLossRateWindows.ToString();
}
}
//if we are waiting for the activity to be trained
else
this.trainingLabel.Text = "Training " + current_activity + " in " + ((int)(this.startActivityTime - Environment.TickCount) / 1000) + " secs";
}
else // Manual Training
{
}
}
#endregion Train in realtime and generate ARFF File
#region Classifying activities
#if (PocketPC)
if (isClassifying == true)
{
double lastTimeStamp = Extractor.StoreMITesWindow();
if ((this.sensors.HasBuiltinSensors) && (polledData != null))
{
//aMITesLoggerPLFormat.SaveRawMITesBuiltinData(polledData);
//store it in Extractor Buffers as well
lastTimeStamp = Extractor.StoreBuiltinData(polledData);
}
if (Extractor.GenerateFeatureVector(lastTimeStamp))
{
Instance newinstance = new Instance(instances.numAttributes());
newinstance.Dataset = instances;
for (int i = 0; (i < Extractor.Features.Length); i++)
newinstance.setValue(instances.attribute(i), Extractor.Features[i]);
double predicted = classifier.classifyInstance(newinstance);
string predicted_activity = newinstance.dataset().classAttribute().value_Renamed((int)predicted);
int currentIndex = (int)labelIndex[predicted_activity];
labelCounters[currentIndex] = (int)labelCounters[currentIndex] + 1;
classificationCounter++;
if (classificationCounter == Extractor.Configuration.SmoothWindows)
{
classificationCounter = 0;
int mostCount = 0;
string mostActivity = "";
for (int j = 0; (j < labelCounters.Length); j++)
{
if (labelCounters[j] > mostCount)
{
mostActivity = activityLabels[j];
mostCount = labelCounters[j];
}
labelCounters[j] = 0;
}
pieChart.SetActivity(mostActivity);
if (this.aList.getEmptyPercent() == 1)
this.aList.reset();
else
this.aList.increment(mostActivity);
if (previousActivity != mostActivity)
{
this.activityTimer.stop();
this.activityTimer.reset();
currentCalories = 0;
}
else
{
if (this.activityTimer.isRunning() == false)
this.activityTimer.start();
}
if (mostActivity == "standing")
{
currentCalories += 1;
totalCalories += 1;
}
else if (mostActivity == "walking")
{
currentCalories += 2;
totalCalories += 2;
}
else if (mostActivity == "brisk-walking")
{
currentCalories += 4;
totalCalories += 4;
}
else
{
currentCalories += 1;
totalCalories += 1;
}
pieChart.SetCalories(totalCalories, currentCalories);
pieChart.Data = this.aList.toPercentHashtable();
pieChart.Invalidate();
previousActivity = mostActivity;
}
}
}
#endif
#endregion Classifying activities
#region Storing CSV data for the grapher (PC Only)
#if (!PocketPC)
if (isCollectingDetailedData == true)
{
if (activityCountWindowSize > Extractor.Configuration.QualityWindowSize) //write a line to CSV and initialize
{
DateTime now = DateTime.Now;
DateTime origin = new DateTime(1970, 1, 1, 0, 0, 0, 0);
TimeSpan diff = now.Subtract(origin);
string timestamp = diff.TotalMilliseconds + "," + now.ToString("yyyy'-'MM'-'dd' 'HH':'mm':'ssK");
string master_csv_line = timestamp;
string hr_csv_line = timestamp;
//to restore the date
//DateTime restored = origin.AddMilliseconds(diff.TotalMilliseconds);
if (this.overallTimer.isRunning())
{
foreach (Button button in this.categoryButtons)
master_csv_line += "," + button.Text;
}
else
{
foreach (Button button in this.categoryButtons)
master_csv_line += ",";
}
foreach (Sensor sensor in this.sensors.Sensors)
{
string csv_line1 = timestamp;
string csv_line2 = timestamp;
string csv_line3 = timestamp;
int sensor_id = Convert.ToInt32(sensor.ID);
if (sensor_id > 0) //No HR
{
if (acCounters[sensor_id] > 0)
{
csv_line2 += "," + MITesDataFilterer.MITesPerformanceTracker[sensor_id].LastSamplingRate;
csv_line1 += "," + ((double)(averageX[sensor_id] / (double)acCounters[sensor_id])).ToString("00.00") + ",";
csv_line1 += ((double)(averageY[sensor_id] / (double)acCounters[sensor_id])).ToString("00.00") + ",";
csv_line1 += ((double)(averageZ[sensor_id] / (double)acCounters[sensor_id])).ToString("00.00");
csv_line3 += "," + ((int)(averageRawX[sensor_id] / acCounters[sensor_id])) + ",";
csv_line3 += ((int)(averageRawY[sensor_id] / acCounters[sensor_id])) + ",";
csv_line3 += ((int)(averageRawZ[sensor_id] / acCounters[sensor_id]));
master_csv_line += "," + MITesDataFilterer.MITesPerformanceTracker[sensor_id].LastSamplingRate;
master_csv_line += "," + ((int)(averageRawX[sensor_id] / acCounters[sensor_id])) + ",";
master_csv_line += ((int)(averageRawY[sensor_id] / acCounters[sensor_id])) + ",";
master_csv_line += ((int)(averageRawZ[sensor_id] / acCounters[sensor_id]));
master_csv_line += "," + ((double)(averageX[sensor_id] / (double)acCounters[sensor_id])).ToString("00.00") + ",";
master_csv_line += ((double)(averageY[sensor_id] / (double)acCounters[sensor_id])).ToString("00.00") + ",";
master_csv_line += ((double)(averageZ[sensor_id] / (double)acCounters[sensor_id])).ToString("00.00");
}
else
{
csv_line1 += ",,,,";
csv_line3 += ",,,,";
csv_line2 += ",0";
master_csv_line += ",0,,,,,,";
}
this.activityCountCSVs[sensor_id].WriteLine(csv_line1);
this.samplingCSVs[sensor_id].WriteLine(csv_line2);
this.averagedRaw[sensor_id].WriteLine(csv_line3);
}
averageX[sensor_id] = 0;
averageY[sensor_id] = 0;
averageZ[sensor_id] = 0;
averageRawX[sensor_id] = 0;
averageRawY[sensor_id] = 0;
averageRawZ[sensor_id] = 0;
prevX[sensor_id] = 0;
prevY[sensor_id] = 0;
prevY[sensor_id] = 0;
acCounters[sensor_id] = 0;
}
if (hrCount > 0)
{
this.hrCSV.WriteLine(hr_csv_line + "," + (int)(sumHR / hrCount));
this.masterCSV.WriteLine(master_csv_line + "," + (int)(sumHR / hrCount));
}
else
{
this.hrCSV.WriteLine(hr_csv_line + ",");
this.masterCSV.WriteLine(master_csv_line + ",");
}
hrCount = 0;
sumHR = 0;
activityCountWindowSize = 0;
}
activityCountWindowSize += 10; //add 10 milliseconds
}
#endif
#endregion Storing CSV data for the grapher (PC Only)
#region Calibration and CSV Calculateion Code
if ((isCalibrating) || (isCollectingDetailedData == true))
{
//store sum of abs values of consecutive accelerometer readings
for (int i = 0; (i < this.masterDecoder.someMITesDataIndex); i++)
{
if ((this.masterDecoder.someMITesData[i].type != (int)MITesTypes.NOISE) &&
(this.masterDecoder.someMITesData[i].type == (int)MITesTypes.ACCEL))
{
int channel = 0, x = 0, y = 0, z = 0;
channel = (int)this.masterDecoder.someMITesData[i].channel;
x = (int)this.masterDecoder.someMITesData[i].x;
y = (int)this.masterDecoder.someMITesData[i].y;
z = (int)this.masterDecoder.someMITesData[i].z;
#region Calibration Calculation
if (isCalibrating)
{
if (this.calSensor == -1)
{
if (this.currentCalibrationSensorIndex < this.sensors.Sensors.Count)
{
this.calX = new int[Constants.CALIBRATION_SAMPLES];
this.calY = new int[Constants.CALIBRATION_SAMPLES];
this.calZ = new int[Constants.CALIBRATION_SAMPLES];
this.calSensor = Convert.ToInt32(((Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).ID);
this.calSensorPosition = Constants.CALIBRATION_FLAT_HORIZONTAL_POSITION;
int receiver_id = Convert.ToInt32(((Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).Receiver);
int[] channels = new int[6];
#if (PockectPC)
if (this.calSensor != PhoneAccelerometers.Constants.BUILT_IN_ACCELEROMETER_CHANNEL_ID)
{
#endif
channels[0] = this.calSensor;
this.mitesControllers[receiver_id].SetChannels(1, channels);
#if (PockectPC)
}
#endif
}
else //all sensors are calibrated
{
TextWriter tw = new StreamWriter("SensorData.xml");
tw.WriteLine(this.sensors.toXML());
tw.Close();
MessageBox.Show("Calibration... Completed");
#if (PocketPC)
Application.Exit();
System.Diagnostics.Process.GetCurrentProcess().Kill();
#else
Environment.Exit(0);
#endif
}
}
if (channel == this.calSensor)
{
if (this.calSensorPosition == Constants.CALIBRATION_FLAT_HORIZONTAL_POSITION)
{
this.calX[this.calCounter] = x;
this.calY[this.calCounter] = y;
this.calCounter++;
}
else //vertical
{
this.calZ[this.calCounter] = z;
this.calCounter++;
}
// if all required samples are collected
if (this.calCounter == Constants.CALIBRATION_SAMPLES)
{
if (this.calSensorPosition == Constants.CALIBRATION_FLAT_HORIZONTAL_POSITION)
{
this.calSensorPosition = Constants.CALIBRATION_SIDE_VERTICAL_POSITION;
double meanX = 0.0, meanY = 0.0;
double stdX = 0.0, stdY = 0.0;
this.label17.Text = "Calibration Completed! Please place the sensor " + ((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).ID + " vertical on a flat surface then click start.";
this.pictureBox2.Image = this.verticalMITes;
this.button2.Enabled = true;
for (int j = 0; (j < this.calCounter); j++)
{
meanX += (double)this.calX[j];
meanY += (double)this.calY[j];
}
meanX = meanX / this.calCounter;
meanY = meanY / this.calCounter;
((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).XMean = meanX;
((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).YMean = meanY;
for (int j = 0; (j < this.calCounter); j++)
{
stdX += Math.Pow(this.calX[j] - meanX, 2);
stdY += Math.Pow(this.calY[j] - meanY, 2);
}
stdX = Math.Sqrt(stdX / (this.calCounter - 1));
stdY = Math.Sqrt(stdY / (this.calCounter - 1));
((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).XStd = stdX;
((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).YStd = stdY;
}
else
{
if (this.currentCalibrationSensorIndex < this.sensors.Sensors.Count)
{
this.label17.Text = "Calibration Completed! Please place the sensor " + ((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).ID + " horizontal on a flat surface then click start.";
this.pictureBox2.Image = this.horizontalMITes;
this.button2.Enabled = true;
}
this.calSensorPosition = Constants.CALIBRATION_FLAT_HORIZONTAL_POSITION;
double meanZ = 0.0;
double stdZ = 0.0;
for (int j = 0; (j < this.calCounter); j++)
meanZ += (double)this.calZ[j];
meanZ = meanZ / this.calCounter;
((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).ZMean = meanZ;
for (int j = 0; (j < this.calCounter); j++)
stdZ += Math.Pow(this.calZ[j] - meanZ, 2);
stdZ = Math.Sqrt(stdZ / (this.calCounter - 1));
((SXML.Sensor)this.sensors.Sensors[this.currentCalibrationSensorIndex]).ZStd = stdZ;
this.currentCalibrationSensorIndex++;
this.calSensor = -1;
}
this.isCalibrating = false;
this.calCounter = 0;
}
}
}
#endregion Calibration Calculation
#region CSV values calculation (PC Only)
#if (!PocketPC)
else if (isCollectingDetailedData)
{
if (channel <= this.sensors.MaximumSensorID) //if junk comes ignore it
{
if ((prevX[channel] > 0) && (prevY[channel] > 0) && (prevZ[channel] > 0) && (x > 0) && (y > 0) && (z > 0))
{
averageX[channel] = averageX[channel] + Math.Abs(prevX[channel] - x);
averageRawX[channel] = averageRawX[channel] + x;
averageY[channel] = averageY[channel] + Math.Abs(prevY[channel] - y);
averageRawY[channel] = averageRawY[channel] + y;
averageZ[channel] = averageZ[channel] + Math.Abs(prevZ[channel] - z);
averageRawZ[channel] = averageRawZ[channel] + z;
acCounters[channel] = acCounters[channel] + 1;
}
prevX[channel] = x;
prevY[channel] = y;
prevZ[channel] = z;
}
}
#endif
#endregion CSV values calculation (PC Only)
}
}
}
#endregion Calibration and CSV Calculateion Code
//Remove data with any values =0 or 1022
aMITesDataFilterer.RemoveZeroNoise();
this.masterDecoder.UpdateSamplingRate(aMITesDataFilterer.CountNonNoise());
if (printSamplingCount > 500)
{
//((System.Windows.Forms.Label)this.sensorLabels["SampRate"]).Text = "Samp: " + this.mitesDecoders[0].GetSamplingRate();
((System.Windows.Forms.Label)this.sensorLabels["SampRate"]).Text = "Samp: ttt";//+this.masterDecoder.GetSamplingRate();
//textBoxRate.Text = "Samp: " + aMITesDecoder.GetSamplingRate();
//aMITesLogger.WriteLogComment(textBoxUV.Text);
printSamplingCount = 0;
}
else
printSamplingCount++;
// Check HR values
int hr = aMITesHRAnalyzer.Update();
#if (PocketPC)
#else
if (hr > 0)
{
sumHR += hr;
hrCount++;
}
#endif
//Compute/get Activity Counts
for (int i = 0; (i < this.sensors.Sensors.Count); i++)
{
int sensor_id = Convert.ToInt32(((SXML.Sensor)this.sensors.Sensors[i]).ID);
if (sensor_id > 0)
((MITesActivityCounter)this.aMITesActivityCounters[sensor_id]).UpdateActivityCounts();
//else if (sensor_id == 0)
// aMITesHRAnalyzer.Update();
}
for (int i = 0; (i < this.sensors.Sensors.Count); i++)
{
int sensor_id = Convert.ToInt32(((SXML.Sensor)this.sensors.Sensors[i]).ID);
if (sensor_id > 0)
((MITesActivityCounter)this.aMITesActivityCounters[sensor_id]).PrintMaxMin();
}
if (((MITesActivityCounter)this.aMITesActivityCounters[this.sensors.FirstAccelerometer]).IsNewEpoch(1000))
{
aMITesHRAnalyzer.ComputeEpoch(30000);
//if (this.tabControl1.TabIndex == 0)
// ReportHR();
for (int i = 0; (i < this.sensors.Sensors.Count); i++)
{
int sensor_id = Convert.ToInt32(((SXML.Sensor)this.sensors.Sensors[i]).ID);
if (sensor_id > 0)
((MITesActivityCounter)this.aMITesActivityCounters[sensor_id]).ComputeEpoch();
}
if (!isWrittenKey) // Write the key once at the top of the file
{
isWrittenKey = true;
aMITesActivityLogger.StartReportKeyLine();
for (int i = 0; (i < this.sensors.Sensors.Count); i++)
{
int sensor_id = Convert.ToInt32(((SXML.Sensor)this.sensors.Sensors[i]).ID);
if (sensor_id > 0)
aMITesActivityLogger.AddKeyLine(((MITesActivityCounter)this.aMITesActivityCounters[sensor_id]));
}
aMITesActivityLogger.AddKeyLine(aMITesHRAnalyzer);
aMITesActivityLogger.SaveReportKeyLine();
}
aMITesActivityLogger.StartReportLine();
for (int i = 0; (i < this.sensors.Sensors.Count); i++)
{
int sensor_id = Convert.ToInt32(((SXML.Sensor)this.sensors.Sensors[i]).ID);
if (sensor_id > 0)
aMITesActivityLogger.AddReportLine(((MITesActivityCounter)this.aMITesActivityCounters[sensor_id]));
}
aMITesActivityLogger.AddReportLine(aMITesHRAnalyzer);
aMITesActivityLogger.SaveReportLine();
}
#region Store the sensor data
if (flushTimer == 0)
aMITesLoggerPLFormat.FlushBytes();
if (flushTimer > FLUSH_TIMER_MAX)
flushTimer = -1;
flushTimer++;
#endregion Store the sensor data
// Graph accelerometer data for multiple recievers
#if (PocketPC)
if (isPlotting)
GraphAccelerometerValues(polledData);
#endif
#if (PocketPC)
if (polledData != null)
{
this.builtinData = null;
this.unprocessedBuiltin = false;
}
#endif
}
