/// <summary>
/// Write the measurement data into a CSV file with 1 column for each channel of data.
/// </summary>
/// <param name="channels">The channels of data.</param>
/// <param name="csvFilename">The name of the output file.</param>
private static void WriteToLogFile(Measurements channels, string csvFilename)
{
string filepath = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, csvFilename);
StreamWriter csvOutput = new StreamWriter(filepath);
for (int channel = 0; channel < Measurements.ChannelsOfData; channel++)
{
for (int reading = 0; reading < channels.Readings.GetUpperBound(0); reading++)
{
csvOutput.WriteLine("{0},{1},{2},{3},{4},{5}",
channels.Readings[reading, 0],
channels.Readings[reading, 1],
channels.Readings[reading, 2],
channels.Readings[reading, 3],
channels.Readings[reading, 4],
channels.Readings[reading, 5]);
}
}
csvOutput.Close();
}
/// <summary>
/// Where all the action happens!
/// </summary>
/// <param name="args">None but the above constants could be parameterized.</param>
static void Main(string[] args)
{
// Read the data from the input file. We read the whole file here, which is OK on a PC,
// but it would need refactoring to read blocks at a time on an embedded system.
string ecgStream = OpenInputFile(ecgSampleFilename);
// Convert the text stream into a list of ECG packet objects
List<ModeECGPacket> packets = ParseECGStream(ecgStream);
// Convert the ECG data values for each channel into an array. This makes it easier
// to analyse.
Measurements channels = new Measurements(packets);
// Output to csv file for analysis. This isn't really necessary but it's quick to
// produce a chart in Excel.
WriteToLogFile(channels, csvFilename);
// Detect heartrates from the channel data.
List<double> heartrates = GetHeartrates(channels);
// Display our findings to the user.
ReportFindings(heartrates);
// Keep the console up so the user has a chance to read the heartbeats found.
Console.ReadLine();
}
/// <summary>
/// Write the measurement data into a CSV file with 1 column for each channel of data.
/// </summary>
/// <param name="channels">The channels of data.</param>
/// <param name="csvFilename">The name of the output file.</param>
private static void WriteToLogFile(Measurements channels, string csvFilename)
{
string filepath = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, csvFilename);
StreamWriter csvOutput = new StreamWriter(filepath);
for (int channel = 0; channel < Measurements.ChannelsOfData; channel++)
{
for (int reading = 0; reading < channels.Readings.GetUpperBound(0); reading++)
{
csvOutput.WriteLine("{0},{1},{2},{3},{4},{5}",
channels.Readings[reading, 0],
channels.Readings[reading, 1],
channels.Readings[reading, 2],
channels.Readings[reading, 3],
channels.Readings[reading, 4],
channels.Readings[reading, 5]);
}
}
csvOutput.Close();
}
/// <summary>
/// Work out what heartrates we can from the channel data. At this point, we don't
/// know which channel contains viable data. Here we take a look at how the data fluctuates
/// and if it's more than a differential threshold, we take it that this channel is the
/// one containing the ECG data. With the sample file of data, there's only one channel
/// of data (channel 0 actually); all others are flat-liners so presumably the test
/// subjects on channels 1 to 5 are deceased! Oh no, call the doc... :-)
/// </summary>
/// <param name="channels">The data from all channels.</param>
/// <returns>The list of heartrates that have been calculated.</returns>
private static List<double> GetHeartrates(Measurements channels)
{
// We'll store the indices of readings in here.
List<int> intervals = new List<int>();
// Go through each of the channels to detect one that contains data.
for (int channel = 0; channel < Measurements.ChannelsOfData; channel++)
{
UInt16 currentReading = 0;
UInt16 previousReading = channels.Readings[0, channel];
for (int reading = 1; reading < channels.Readings.GetUpperBound(0); reading++)
{
currentReading = channels.Readings[reading, channel];
UInt16 differential = (UInt16)Math.Abs(currentReading - previousReading);
if (differential > differentialThreshold)
{
intervals.Add(reading);
}
previousReading = currentReading;
}
// If we have at least 2 values, we have an interval so we can calculate a
// heartrate. It may be that the interval between them is too small though.
if (intervals.Count >= 2) break;
}
// If we haven't detected any suitable channel of data, we can't calculate the
// heartrates.
if (intervals.Count == 0) return null;
// Calculate heartrates from the intervals we've recorded.
List<double> heartrates = new List<double>();
int interval1 = intervals[0];
for (int i = 1; i < intervals.Count; i++)
{
int interval2 = intervals[i];
double rate = 60 / (((double)(interval2 - interval1)) / samplingRateHz);
if (rate < maximumPossibleHeartRateBPM)
{
heartrates.Add(rate);
}
interval1 = interval2;
}
return heartrates;
}
