UPDATE: An improved ECG design was posted in August, 2016.
Check out: http://www.swharden.com/wp/2016-08-08-diy-ecg-with-1-op-amp/

Last night my wife put her head on my chest while we were watching a movie. A minute or two later I felt a light sinking feeling in my upper chest, and my wife looked up at me in horror. “Your heart stopped beating!” I assured her that everything was okay (it quickly resumed), and that it happens all the time. I feel the sinking feeling often, know it’s because my heart is briefly beating irregularly, and assume it’s normal. After all, your heart isn’t a robot, it’s a living organ doing the best it can. It’s never perfectly regular, and presumably everybody has momentary irregularities, they just don’t notice them. When I got in bed I began wondering how regular irregular heartbeats are. What would the chances be that I have some kind of arrhythmia? I’ve had a checkup not too long ago by a family practice physician who used a stethoscope on my back to listen to my heartbeat, and he didn’t notice anything. Then again, how often do general practice doctors detect subtle arrhythmia?
I know that whatever problem I have is likely too small to cause any serious troubles, but at the same time I’m becoming obsessed as to determining exactly what my problem is. How many times a day does my heart skip beats? What about nighttime? If only there were some way to record heartbeat data, then I could analyze it and determine the severity of my problem. But wait, data? That would be hours of heartbeat recordings… that means… YES!!!! HOME MADE DO-IT-YOURSELF HARDWARE! WRITING SOFTWARE TO ANALYZE LARGE AMOUNT OF DATA! SUPER-COOL SCIENCY STUFF THAT I CAN MAKE MYSELF, COMBINING BASIC ELECTRONICS WITH BIOMEDICAL DATA ANALYSIS AND, HARAY, PROGRAMMING WITH PYTHON!
Naturally, my thoughts began to overwhelm my reality as soon as Python entered the scene. I wondered how I could use my PC to record my heartbeat, without spending much money on hardware, and only using software I write myself. I pondered this on the way to work this morning, and came up with two possible methods:
Method 1: acoustical recordings. This would be the easiest way to record my heartbeat. I could tape a stethoscope to my chest, insert a small microphone in the earpiece, connect the microphone to my PC, and record sound data for several hours. Theoretically it would work, but it would be highly prone to noise from breathing, and I would have to lay perfectly still to avoid noise caused by movements. The data (trace) would have to be smoothed, processed with a band-pass filter (to eliminate interference), and heartbeats could be calculated. However, this would only give me heart beat time information…
Method 1: electrical recordings. This would be a little more complicated, but generate much more information. I could record the electrical activity of my heart, and the charts would look like the cool electrocardiograms (ECGs) that you see on TV shows and stuff. I would have to build some circuity to amplify the 1mV heartbeat signal recorded from electrodes taped to my chest, but then again what’s more fun than ghetto-building circuits! (I apologize for any people reading this blog who actually live in the ghetto and enjoy building circuits.) I did a little Googling and found that similar things have been done before with a handful of diodes, resisters, and 6 op-amps. I think I’m going to follow the guide on this page and build the circuit seen below:

Schematic of a crude ECG circuit

Supposedly, the data I can obtain looks something like the image at the bottom of this blog entry. I’d attach 3 electrodes to my body (chest, arm, and leg), hook them up to my little circuit, then connect to circuit to my PCs sound card. I’d record the trace (maybe while I sleep?) and analyze it with Python, Numpy, Scipy, and Matplotlib (gosh I love Python). There are several websites which demonstrate how to build DIY ECG recording devices, but none of these actually ANALYZE the data they obtain! Hopefully I could fill this little niche on the internet. We’ll see what happens. I have my thesis to work on, and a whole bunch of other stuff on my plate right now.

A sample recording from the circuit pictured above

The terms assigned to different parts of the heartbeat

UPDATE: I found an extremely crude ECG circuit which I can make from parts I already have at my house. It has tons of noise, but maybe I can filter it out? Perhaps I’ll try this tonight? [ponders]

Additional Resources

I’ve been stuck in the laboratory all day! I’m currently writing software to convert data from images (microscope scans) into massive 4-dimensional arrays (handled by numpy and Python) which are then analyzed statistically (that’s the code I’m working on today). Since these data files are so huge, it usually takes at least 30 seconds just to load these massive arrays into memory before the calculations can be performed (which only take a second). The frustrating part is that the calculations don’t work right, so I make a change in the code and try again, and have to wait half a minute before another failed result. After doing this for hours (with only about 10 minutes of actual work – the rest of the time spent waiting) I began screaming at my PC. It’s ironic that (in my frustration-spawned break) I logged into Facebook and noticed that Tom Hayward posted a video entitled “shouting at your computer increases hard drive latency”. Do I need to say more? [dies laughing]

Additional Resources

I recently swapped my two main PCs in my house. The “headless” (no monitor) media PC (whose job consists of downloading, storing, and playing movies) connected directly to my TV, and our standard desktop PC which my wife uses most of the time. I decided to do the swap because the media PC was way nicer than our desktop PC, and since the media PC is just playing movies and downloading torrents, I figured the extra processing power / ram / video acceleration could be put to better use. Anyhow, I decided (in both cases) to completely start fresh by wiping hard drives clean and reinstalling Ubuntu linux (I’m using 8.10 currently). However, after the installation I noticed a peculiar problem. I’ll quote it to emphasize it…

Browsing the internet was very slow. When I’d click a link on a website, it would take several seconds before it seemed to even try to go to the next page. The same thing would happen if I manually typed-in a new website. I tried disabling IPv6 in firefox’s about:config and in the /etc/init.d/aliases file, but it didn’t help!

The solution for me was simple, and since I spent a lot of time searching forums I know I’m not the only one with this problem. Disabling IPv6 was suggested in 99% of similar posts. My solution took a while to uncover, so I figured I’d write it here. The basic problem is that my DHCP (auto-configured IP address) settings were screwed up, and my manually setting them I fixed the problem. Here’s what I did…

Start by right-clicking your network icon (wireless in my case) and selecting connection information

Check out your current configuration. Is a local address (192.168.*.*) set for the primary DNS server? If so, that’s your problem! Note your secondary server. We’ll set it as your primary…

Continue by right-clicking your network icon (wireless in my case) and selecting edit connections*. Open the tab corresponding to your internet connection (wired or wireless – wireless in my case), select your connection, and click Edit

Use this screen to manually enter the information from the information screen you saw earlier, but making sure not to list any local IP addresses as the DNS servers. Save your settings, close the windows, and the problem should be immediately corrected. Leave “search domains” blank, that’s important too. Good luck!!!

Additional Resources

While writing code for my graduate research thesis I came across the need to lightly compress a huge and complex variable (a massive 3D data array) and store it in a text file for later retrieval. I decided to use the zlib compression library because it’s open source and works pretty much on every platform. I ran into a snag for a while though, because whenever I loaded data from a text file it wouldn’t properly decompress. I fixed this problem by adding the “rb” to the open line, forcing python to read the text file as binary data rather than ascii data. Below is my code, written in two functions to save/load compressed string data to/from files in Python.


 import zlib  


 def saveIt(data,fname):  








 def openIt(fname,evaluate=True):  





     if evaluate: data=eval(data)  

     return data  


Oh yeah, don’t forget the evaluate option in the openIt function. If set to True (default), the returned variable will be an evaluated object. For example, “[[1,2],[3,4]]” will be returned as an actual 2D list, not just a string. How convenient is that?

Additional Resources

I accidentally nuked my laptop’s 80G hard drive this morning (D’OH!) while shuffling around partitions. Supposedly there’s a valid windows (XP) installation on there still that’s about 20G. I’d love to repair it so I can use it today while I’m in the confocal room, but I don’t have an Ubuntu CD, Windows CD, or any CD for that matter! I looked around, but I guess blank CD-Rs aren’t something that’s standard in molecular biology laboratories. Anyhow, I wanted to install the new Ubuntu 8.10 Linux distribution, and I’ve downloaded the ISO, but since I can’t find a CD to burn it to I decided to try booting from a USB drive (something I’ve never done before). I found an AWESOME program which specialized in putting ISO files onto bootable USB drives. It’s called UNetBootin and it’s free (of course), runs on Linux or Windows, and has some built-in options for various linux distributions. I can repair my PC now! Yay!