Noise Reduction in Neonatal ICU

Noise Reduction in Neonatal ICU
Paul Baker, Rogelio Grijalva, Elton Leung, Roberto Rios-Rios
University of California Merced
Mechanical Engineering Capstone Design Spring 2012
Neonatal Acoustic Solutions
Mission Statement Neonatal Acoustic Solution’s purpose, in cooperation with Children’s Hospital Central California (CHCC), is to find methods to reduce noise levels to 55 dB in the neonatal ICU through the application of existing technologies, creation of new products, and alteration of
patterns of behavior with a focus on efficiency and cost effectiveness, while minimizing the impact on hospital staff.
Excessive noise in the CHCC Neonatal ICU – OSHA standard mandates 55dB Max.
Medical research has demonstrated the importance of noise regulation in a hospital
setting. Noise can be harmful to the development of fragile neonates and has been
shown to increase recovery times. A previous study done by the hospital showed an
average noise level of 66-71dB. However, there were three main concerns in our
designs: they need to be safe for the babies, financially viable, and should not
prevent the hospital staff from performing their duties.
Course of
Our initial task was to measure the sound levels for ourselves. Some data from that
experiment is to the right. We discovered that there were two main sources of noise:
equipment and staff. The equipment produced low frequency periodic noise
whereas the staff were responsible for intermittent wide band bursts. These
represent very different types of noise pollution and demanded separate solutions.
We decided upon a three pronged solution: two targeted and one general. To
combat the periodic machine noise generated by the ventilators, oscillators, and
pumps we developed an Active Noise Reduction device. In response to the people
noise we devised an Active Feedback Sign which gives the staff immediate
feedback about their volume. Lastly, to cover everything our targeted solutions
missed, we recommended changing out the ceiling for better Acoustic Panels, which
affect all frequencies and provide overall noise reduction in the room.
Room #2605
Room Ambient:
Diaphragm Valve:
Suction Regulator A:
Suction Regulator B:
Room #2604
Room Ambient:
Room #2606
Wave Theory
Active Noise Reduction (ANR)
Active Feedback Signage
Sound is the vibration of the air, and when air
vibrates it creates areas of high and low
pressure. This pressure wave can be
described by this equation:
Active noise cancellation works on the principle of destructive interference. When two
waves with the same phase but opposite amplitudes overlap, the peaks of one
interfere with the troughs of the other, which leads to a reduction in total amplitude.
We found that noise made by hospital
staff was not continuous, but did spike
up to unacceptable levels during shift
changes and procedures that involved
more than a single nurse. While the staff
is trained to keep their voices down, this
clearly is not effective when they are
focused on other things. The goal of the
sign is to alert the staff when their voices
are getting too loud.
When two or more waves coincide the
interaction between them and resulting
combined pressure wave can be described
While this is helpful, for our purposes the
most important equation is this one:
This equation represents the resulting
amplitude when two waves interfere with
each other. Since we want to reduce noise
we need to either absorb sound or generate
a waveform which, when added to the
existing noise, causes the left side of this
equation to go toward zero. This concept is
referred to as destructive interference.
In our research we found that if you are able to keep the canceling source within ¼ of
a wavelength of the noise source you can achieve global cancellation without all the
complicated sensors, microphones and logic circuits that 3D cancellation normally
requires. For our project the frequency we needed to cancel out was in the 1-1000 Hz
range, and at 1000 Hz, ¼ of the wavelength is approximately 3.5 inches, so as long as
unit remains close to the source it should affect the entire room.
Our ANR circuit is comprised of 3 main parts: the input, inverter, and amplifier. The
input is a unidirectional microphone connected to a unity gain operational amplifier
acting as a pre-amp. This boosts the signal level of the microphone such that the rest
of the circuit can use it (microphones usually have very low voltages). The second
stage is an inverter, which in our circuit is again an operational amplifier though in this
case it is utilizing its inverting input. This chip takes the incoming microphone signal
and flips its phase 180°. This means that anywhere there used to be a peak there is
now a trough, and vice versa. The last stage is a low noise audio amplifier with 20200dB gain. This section gives the signal enough power to operate a speaker. The
specific components are noted in the circuit diagram below.
ANR Circuit
The concept is identical to the highway
speed signs that tell you your current
speed as you pass. While you know that
the speed limit is 65, that does not mean
you always travel at that speed.
Sometimes you end up going faster
without noticing, and the sign reminds
you to slow down. Similarly, our signs
are designed to alert the staff when their
voices are nearing the 55 dB level. This
prevents undue noise spikes, while our
other two solutions actively reduce the
ambient noise level.
Active Signage Circuit
Low Gain
Active Signage Model
COMSOL Room Model
ANR Device Model
Noise Reduction Calculation
To determine the improvement that could be expected from
swapping out the ceiling tiles, we performed a noise reduction
calculation. The concept behind this is a comparison between
the total absorptive area before and after the change. The
relationship is below:
NR = log Aa/Ab
Acoustic Tile
The procedure is to calculate the total surface area in a given
room (we used a typical ward with 6 beds). For each surface
multiply the area by the noise reduction coefficient (NRC) of
the material. The sum of these products represent the effective
absorptive area Ab. The second step is to assume a change in
the room composition. In our case this was a change in the
NRC value of the ceiling tiles (0.5 to 0.95). Following the same
procedure with the new ceiling generates Aa, from which we
get the noise reduction in dB.
Overall performance will be analyzed by a
COMSOL model of a sample room. We will
place equivalent point noise sources and
accurate material properties into the model
and run it using the acoustics module, which
generates a representation of existing sound
level pressures in the room.
Our research indicated that while ANR on
average reduces noise levels by around 10dB
for low frequency noise (less than 1500 Hz).
Using this 10dB as a starting point we will
reduce the output of the point sources by that
amount and change the NRC value of the
ceiling. After running the analysis again this will
give us a new graph which shows the
approximate reduction in overall room noise as
a result of our designs.
Our aim was to reduce noise levels to 55dB. With the ANR averaging 10dB and the new ceiling providing approximately
2dB, the overall noise reduction is expected to be around 12dB. Given a starting level of 67dB this means we achieve our
goal. That said, though we accomplished a great deal this semester, there is much that could be done to improve the design
of both our circuits.
The ANR circuitry works best against low frequency sound, but currently it is forced to process all noise. The addition of a
low pass filter following the pre-amp would allow us to exclude frequencies outside our ideal range. This would decrease
feedback potential, unintentional high frequency amplification, and could slightly decrease overall power consumption in the
circuit. Similarly, even though the sign is only intended to target human noise, it currently registers all surrounding noise,
which means alarms may cause it to generate false positives. An idea that we did not have time to implement was an
adjustable band pass filter. It would allow the user to select a range of frequencies in which the alarms operate and exclude
those noise from registering on the LED display. This is useful because if the sign is going into the red due to alarms the
staff may begin to ignore it, which defeats its purpose.
While COMSOL provides a decent representation of the acoustics of our room, there are more specialized pieces of
software that would give a more accurate picture. Odeon is one of these, and though we wanted to use it for this project it
did not fit in our budget this semester. Future work could include this analysis as well.