Category Archives: Cardiac Electrophysiology

Cardiac Electrophysiology

ICDs, wandless telemetry, and encryption

Here’s something nobody has ever been able to tell me:

Do wandless ICDs (implantable cardioverter-defibrillators) employ any kind of encryption?

As far as I can tell, the answer is no.

Let me give you a little background. At the last Heart Rhythm Scientific Sessions (2005, in New Orleans) most of the big ICD companies were showing off their wonderful new “wandless telemetry” systems. Historically, ICDs have been programmed (after implantation) and interrogated with some variety of inductive communication. This was done by placing a “wand” over the part of the patient’s body where the device was implanted and then initiating communication. It has a short range, around a few inches. Device companies have begun to use radio-frequency (RF) communication instead, which has a longer range, something on the order of feet or meters.

This is a big problem.

Not one person I’ve asked (admittedly, sales people for the most part) has been able to tell me if the new RF (a.k.a wandless) telemetry communication is encrypted. I did some patent searching at uspto.gov, and found that no patents have been granted on anything like this yet. However, Medtronic did apply for a patent in September 2005. As the patent application says in its background, “With the advent of long range telemetry of messages, and the associated increase in communication range, the risk that a message can be compromised is increased. For example, a replay attack can be launched in which a message, or a piece of a message, can be captured and then maliciously used at a later time.”

So it does appear that someone is thinking about this. Most people don’t really think about or understand encryption, even technically-inclined people like medical device engineers.

Do you know anything about this? Do you know someone who might?

Implementing and Studying the Conjugate Gradient Method

When I start up a simulation on our cluster, I’m used to seeing this after some information scrolls by:

Solver = Conjugate gradient
preconditioner=block Jacobi with ILU(5) on each block

I knew before that this was some way of solving a big matrix representing the problem at hand, but never knew how it was done. (Un)luckily, my midterm project in one of my classes this semester is to implement and play around with the conjugate gradient method. We were given a little introduction to the method of steepest descent, then sent on our merry ways to the Mardi Gras and subsequent break.

I was terrified.

I started reading the course notes that we’re using for the class, but they used a bunch of terminology I’ve never heard of before. They were extremely concise. Attempts at understanding the information on MathWorld and other sites ended in confusion. And then, I came upon this title on google:

An Introduction to the Conjugate Gradient Method Without the Agonizing Pain

With the agonizing pain still acutely in my mind, I clicked on the link and gave it a try. It’s excellent! The author, Jonathan Richard Shewchuk, writes with clarity, knowledge that I’m probably not a numerical analysis professor, and a little dry humor here and there. After searching for him on google, I discovered why the name looked so familiar — I used his Triangle software to generate my 2D cross-section of our model of the rabbit ventricles! The CJ paper has pretty much saved me, and perhaps more importantly has shown me just how cool and clever numerical analysis can be.

If you want to learn about the CJ method, you really must read his paper.

Classes vs. Research

Classes have been hogging my attention lately, generating a lot of reading and homework. I have hardly touched my research projects in a month. Today I got the ball rolling again, completing a few “Next Actions” from each project.

It felt great.

It’s nice that, with GTD, I can just jump back into my projects as if they were the only thing that has been on my mind.

Wednesday Article Review: Unpinning of a Rotating Wave in Cardiac Muscle by an Electric Field

For the past few weeks, I’ve made Wednesday “Article Review” day. I’ll still post reviews that I deem pertinent on other days, but the goal is to post one each Wednesday at a minimum.

The Hubmed page for today’s article is here: Unpinning of a Rotating Wave in Cardiac Muscle by an Electric Field by Alain Pumir and Valentin Krinsky

Tachycardia (fast heart beat) is commonly caused by a rotating wave of activation in the heart. The study of rotating waves of this type has years of legacy in theoretical and chemical dynamics studies. Today’s article covers rotating waves pinned to anatomical obstacles such as valve openings in the heart. Rotating waves circle a core, which can be functional (a property of the wave shape and dynamics) or anatomical (an obstacle). In the case of an anatomical obstacle, the wave can be eliminated by ablation, which is commonly used in the atria, electrical defibrillation, or possibly unpinning / antitachycardia pacing (ATP). Ablation is typically invasive, requiring catheterization, and defibrillation requires an external shock, or surgery to implant an ICD. Defibrillation, either externally or internally, damages the heart, is painful, and often causes loss of consciousness. Antitachycardia pacing and electrical unpininning open the possibility of elimination of tachycardia with small shocks.

The principle of electrical unpinning, proposed by Huyet et al. (1998) and Krinsky et al. (1995), is that when a localized stimulus is applied in a certain part of the wave tail, it may move the core of the rotating wave. It’s difficult to place a stimulus in a particular place at a particular time in a patient’s heart, but it turns out that when an electrical field is applied over an obstacle, areas of depolarization (positive change) and hyperpolarization (negative change) manifest on the borders of the obstacle.

The paper by Pumir and Krinsky details how a small electrical field may be applied at a specific timing relative to wave rotation in order to create such a depolarization on an obstacle that will unpin a wave attached to that same obstacle. They used simplified models of cardiac action potentials, including the Beeler-Reuter and Fitzhugh models. Since the method deals with the dynamics of a spiral wave, and not with particulars of ionic currents, it’s a safe bet that the methods will apply in more complex models and cardiac tissue.

I won’t repeat the article’s simple and logical explanation of how it works — go read it. It’s only 9 pages, the figures are clear, and the math is mercifully simplified in a way that (ostensibly) doesn’t undermine the results.