I’ve done a lot of random things the last few months, but few things were as random, cool, or googled-for as my Do-It-Yourself Electrocardiography project . My goal was to produce an effective ECG machine which interfaced the computer sound card for as little cost as possible. I started out small with an extremely simple circuit which technically worked, but required a lot of custom-written software to do a ton of math to decipher the ECG signal from the noise (such as inverse fast flourier transformations after band-stopping several bands of predictable, high-frequency noise). I later started building more complicated circuits in an attempt to minimize the noise, which worked well but were much more difficult to construct. For some reason, my nice ECG circuit died (burned? broke? don’t know why) right after I started to actually generate useful data about my occasional double-beats (which apparently are common, normal, and even expected during basal physiological states).
UPDATE: [2am, nextday] Here’s some video of the prototype briefly demonstrating the concept of how to use a minimum of parts to generate a great ECG trace using digital signal processing on the PC side.

simple_ecg_circuit_output

I’ve decided to revitalize this project quickly and effectively, going back to its roots and focusing on cost-minimal solutions, and using software (rather than complicated analog circuitry) to eliminate the noise. This will be a beautiful marriage of biomedical analog circuitry with software-based processing and linear data analysis, all on the cheap. If there were ever a project that represented my early 20s life, this would be it. Briefly, I built a circuit with only 3 components (!) which produces extraordinary results (above). That’s the signal after minimal processing.

Check it out yourself! I’ll provide data file for this trace (snd2.zip) along with the Python code to graph it (below) which requires numpy and matplotlib in addition to the Python scripting language. I’ll post the circuity along with some more intricate code when my project progresses a little further.

import numpy, pylab

def trim(data,degree=100):
    i,data2=0,[]
    while i<len(data):
        data2.append(sum(data[i:i+degree])/degree)
        i+=degree
    return data2

def genXs(length,trim=100,hz=44100):
    step = 1.0/(hz/trim)
    xs=[]
    for i in range(length):
        xs.append(step*i)
    return xs

data = numpy.memmap("ecg2.snd", dtype='h', mode='r')
data = trim(data)
pylab.grid(alpha=.2)
pylab.plot(genXs(len(data)),data)
pylab.title("Simplified ECG Circuit Output")
pylab.xlabel("Time (seconds)")
pylab.ylabel("Potential (Au)")
pylab.show()




Additional Resources

Does your web hosting company block access to access.log, the text file containing raw website log files? If so, you’re like me, and it sucks. There’s a plethora of gorgeous and extremely insightful website traffic analyzers, but all of them require access to raw HTTP access logs. Today I propose a semi-efficient way to generate such logs utilizing PHP to determine page load data (time, user IP, requested page, referring page, user client, etc) and SQL to save such data for easy retrieval later. Note that this method is a HUGE improvement of my previous project which used PHP scripts to store HTTP access logs as flat files. Although it worked in theory, in all practicality the process of opening, writing to, and closing a text file (which grew a few MB a week) was too cumbersome for my server to comfortable handle. The method described on this page utilizes SQL, a database engine well-suited to meet these exact demands. When we’re done, you’ll be able to use a web interface to view your access log (pictured, converting long, complicated search queries to web search and image search strings automatically), or have the option to export it directly to an access.log text file in a standard Apache-style format.
sql_php_http_log_viewer

First, make sure your database is structured appropriately. This page is written for those with a working knowledge of PHP and SQL, but if you’re new to the field I encourage you to learn! W3Schools.com is an awesome resource to rapidly learn new languages. Also, when starting-out with SQL (like me), phpMyAdmin is a awesome. The code, as it’s currently written (below) is designed to store data in the “nibjb” database under the “logs” table. Briefly, it uses PHP to determine user data (time, ip, requested page, etc.) and injects this information into the SQL database. In fact, it’s doing it to you right now! Don’t believe me? View the source of this web page and scroll to the bottom. BAM! There you are.

// logme.php
<?php

if ( !isset($wp_did_header) ) {
	$wp_did_header = true;
	require_once( '/home/content/n/i/b/nibjb/html/blog/wp-load.php' );
	//wp();
	//require_once( '/home/content/n/i/b/nibjb/html/blog/wp-includes/template-loader.php' );
}

function logwriter_handlevar($varname,$defaultvalue){
    $tempvar = getenv($varname);
    if(!empty($tempvar)) {
        return $tempvar;
    } else {
        return $defaultvalue;
    }
}

if (!empty($REMOTE_HOST)) {
$logwriter_remote_vistor = $REMOTE_HOST;
}else{
$logwriter_remote_vistor = logwriter_handlevar("REMOTE_ADDR","-");
}

$logwriter_remote_ident = logwriter_handlevar("REMOTE_IDENT","-");
$logwriter_remote_user = logwriter_handlevar("REMOTE_USER","-");
$logwriter_date = date("d/M/Y:H:i:s");
$logwriter_request_method = logwriter_handlevar("REQUEST_METHOD","GET");
$logwriter_request_uri = logwriter_handlevar("REQUEST_URI","");
$logwriter_server_protocol = logwriter_handlevar("SERVER_PROTOCOL","HTTP/1.1");
$logwriter_http_referer = logwriter_handlevar("HTTP_REFERER","-");
$logwriter_http_user_agent = logwriter_handlevar("HTTP_USER_AGENT","");
$logwriter_logstring = "$logwriter_remote_vistor $logwriter_remote_ident $logwriter_remote_user [$logwriter_date $logwriter_timezone] "$logwriter_request_method $logwriter_request_uri $logwriter_server_protocol" 200 - "$logwriter_http_referer" "$logwriter_http_user_agent"n";
?>

<?php
$username="YOUR_USERNAME";
$password="YOUR_PASSWORD";
$database="nibjb";
mysql_connect('mysql157.secureserver.net',$username,$password);
//mysql_connect(localhost,$username,$password);

$query = "INSERT INTO logs VALUES ('','$logwriter_date','$logwriter_remote_vistor','$logwriter_request_method','$logwriter_request_uri','$logwriter_server_protocol','$logwriter_http_referer','$logwriter_http_user_agent')";
mysql_query($query);
mysql_close();
?>

<!--
LOG DETAILS:
time: <?php echo($logwriter_date); ?>
vistor: <?php echo($logwriter_remote_vistor); ?>
method: <?php echo($logwriter_request_method); ?>
request: <?php echo($logwriter_request_uri); ?>
protocol: <?php echo($logwriter_server_protocol); ?>
referrer: <?php echo($logwriter_http_referer); ?>
agent: <?php echo($logwriter_http_user_agent); ?>
HTML LOG LINE:
<?php echo($logwriter_logstring); ?>
 -->

All right, that was easy. Every time we load logme.php, it adds the data to the SQL database. To add data every time you go to a particular web page, you could use a PHP include() statement in each webpage, or you could take advantage of the PHP’s auto_append_file feature! Simply insert the following line into your php.ini file if you have access to yours:

auto_append_file = "/path/to/html/logme.php"

How do we access this data once it’s been loaded into the database? There are many different ways, but I’ve chosen to get a little creative with a sleek, yet minimalistic web-based fronted. It basically just shows the last [x] number of entries in the access log. You can adjust the number of entries displayed by slapping on some arguments to the URL, transforming viewLast.php into viewLast.php?limit=123 or something (see the screenshot above). I won’t discuss the details of this script. It’s self-explanatory.

// viewLast.php
<html>
<head>
<style type="text/css">
td {
font-family: verdana, arial;
font-size:10px;
}
</style>
</head>
<body>
<?php

$limit = (int)$_GET['limit'];
if ($limit===0) {$limit=25;}

$username="YOUR_USERNAME";
$password="YOUR_PASSWORD";
$database="nibjb";
mysql_connect('mysql157.secureserver.net',$username,$password);
mysql_select_db($database) or die( "Unable to select database");
$query="
SELECT * FROM logs WHERE
request NOT LIKE "%testlog.php%"
AND request NOT LIKE  "%/logs/%"
AND request NOT LIKE "%/wp-admin/%"
ORDER BY ID DESC LIMIT 0,$limit
";
//$query="SELECT * FROM logs WHERE referrer LIKE "%&q=%" or referrer LIKE "%&prev=%" ";
$result=mysql_query($query);
$num=mysql_numrows($result);
mysql_close();
?>

<b><?php echo($query); ?></b>
<table border="1">
<tr>
<td>id</td>
<td>time</td>
<td>visitor</td>
<td>request</td>
<td>referrer</td>
</tr>

<?php
$i=1;
while ($i<$num) {
$id=mysql_result($result,$i,"id");
$time=mysql_result($result,$i,"time");
$visitor=mysql_result($result,$i,"visitor");
$method=mysql_result($result,$i,"method");
$request=mysql_result($result,$i,"request");
$protocol=mysql_result($result,$i,"protocol");
$referrer=mysql_result($result,$i,"referrer");
$referrer2=str_replace("&", "& ", $referrer);
$agent=mysql_result($result,$i,"agent");
$searchWords="";
$searchEngine="";
if (strpos($referrer, "q=")>0 and strpos($referrer, "google")>0) {$searchEngine="Google Web Search: ";}
if (strpos($referrer, "prev=/images")>0 and strpos($referrer, "google")>0) {$searchEngine="Google Image Search: ";}

// SEARCH EXTRACTION //
$j=0;
$rTemp=str_replace("prev=/images%3Fq%3D", "q=", $referrer);
$rTemp=str_replace("?q=","&q=", $rTemp);
$rTemp=str_replace("%2B"," ", $rTemp);
$rTemp=str_replace("%26"," ", $rTemp);
$rTemp=str_replace("%3D"," ", $rTemp);
$rTemp=str_replace("+"," ", $rTemp);
$wvars=split("&",$rTemp);
while ($j<count($wvars)){
	if (substr($wvars[$j],0,2) === "q=") {
		$searchWords = $searchWords . $wvars[$j] . " ";
		}
	$j++;
}

$searchWords=substr($searchWords,strpos($searchWords, "q=")+2);
if (strlen($searchWords)<3) {$searchWords=$referrer;}
////////////////////////

echo "
<tr>
<td>$id</td>
<td>$time</td>
<td>$visitor</td>
<td><a href='$request'>$request</a></td>
<td>$searchEngine <a href='$referrer'>$searchWords</a></td>
</td>
";
$i++;
}
?>
</table>
</body>
</html>

And you’re done! This example is a simplified, bare bones example. You can take this a long way if you’d like. My goal is lite & flexible. A quick query from Python and Matplotlib (for example) yields gorgeous visual representations of otherwise-convoluted data!

If you have any questions, or end-up developing something awesome with this code, shoot me an email! It’s not luxurious, but this code works for me, and I share it with the best of intentions.