Hi, my name is Mike Hawes and I'm an application engineer with Agilent Technologies. Today
I'm going to show you a new solution that Agilent has for medical device designers;
in particular wireless or mobile medical devices. This new solution gives them the ability to
look at transient activity from their medical device, which will give them additional insight
into characterizing and predicting their battery life. So let me show you the solution that
we have. This is a DC Power Analyzer. It's a general purpose R&D tool for a R&D bench,
has four modular supplies. We're only using one of those. We have it connected to a wireless
blood pressure monitor. This is actually the world's first Wi-Fi wireless blood pressure
monitor. We'll be using this as our medical device for our experiment today. Channel one
is connected to an SMU or a Source Measurement Unit. The unique thing about this source measurement
unit is that it has four current ranges. Three of those you can actually switch between seamlessly.
This is a patented technique that we have that gives you 28 bits of dynamic range. This
enables you to measure the sleep currents at 10 uA and the execution or operating
currents, for example when you're transmitting RF at say 100s of uA. Then finally
we have our software that's controlling the system and going to be presenting the information
that will give you that additional insight. So let me go ahead and turn around and get
started. As you look at the SMU it's at six volts, so we're simulating the battery and
our medical device. I'm going to go ahead and start the data logger and we're going
to log for five minutes. So here you can see the basic data logging has started. I'll go
ahead and put on the blood pressure cuff and I'll take my blood pressure. You can see from
the device here that the pump is going, you can probably hear the pump starting. This
process takes probably about five minutes. So now that we have the data log, let's take
a look at the current trace. You'll notice that I have a couple of markers that I can
set up. So I'm going to go ahead and move those markers. The first thing I'm going to
look at is this peak. This was a peak when it turned on the pump and the blood pressure
cuff was squeezing my arm. You can see that the peak for this is about 570 uA.
We can also use these markers and I'm going to move to the sleep mode when the device
was sleeping. Here we can see that the average is 53 uA, but the minimum and the maximum
are only 5.8 uA peak-to-peak. So we've got considerably less sleep current. This
level of accurate measurement is not available with a standard technique. It's the seamless
ranging that allows you to both measure that peak at 570 milliamps and the sleep current
down at 5 uA or excuse me 53 uA. We also have something else that's interesting
and this is where you get a lot of insight and it's the charge per energy. What we end
up doing here is understanding how we're depleting the capacity of the battery. So I can go ahead
and move these markers throughout the whole cycle of taking my blood pressure and see
for every time you take a blood pressure measurement you're going to be depleting the battery by
about 2.1 milliamp hours. So this software gives you very good insight into being able
to determine and predict the battery life for your medical device. So that's pretty
much it. In summary we've used the wireless blood pressure monitor blip and we've shown
how our solution provides you good insight as the designer to predict and maximize battery
life for your medical device. Thanks for watching.