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viable solution for establishing interoperability between

medical devices. For this reason, CANopen was chosen as the

communication protocol between the measured respiration

pattern and the hospital bed movements. The CANopen

protocol stack was implemented in a Motorola HCS12

microcontroller. The HCS12 also has an analog to digital

converter which is needed for interfacing with the pressure

transducer.

III METHODS

The pressure transducer outputs an analog voltage reading,

which must be converted to a digital signal for storage and

analysis. The HCS12 processor has a

10

bit analog to digital

convertor, and accepts analog voltages in the range

of

0 to

5.12V. The voltage output from the transducer must be

amplified and biased around 2.5V to work in the HCS12, so

an operational amplifier circuit was designed to convert the

pressure transducer voltage to acceptable values.

The pressure transducer is highly sensitive so that it can

detect the slight respiration patterns in humans, but it will also

be susceptible to noise factors. Therefore, a

th

order

Butterworth band pass filter was designed to filter the

respiration waveform from the pressure transducer output. A

typical adults respiration rate is anywhere from

12

to 20

breaths per minute, so a band pass range

of

0.1 to 0.4 Hz was

selected.

The filtered data was continuously stored in the HCS12

microprocessor, and a peak detection algorithm was

implemented to count the peaks in the filtered respiration

waveform. The time between peaks was calculated and used

to represent the instantaneous respiration rate. When a

subjects respiration rate ceased, the peak detection algorithm

detected no peaks, and

if

no peaks were detected for 10

seconds, a bed adjustment was issued.

The bed adjustment is a command issued by the CANopen

protocol. Specifically for this project, a command was

configured to be issued automatically upon a 10 second timer

in which no respiration peaks were detected in the filtered

respiration waveform.

IV. RESULTS AND DISCUSSION

A system was developed that can detect a patient's

respiration rate without the need for any physically attached

equipment. The patient must only be lying in the hospital bed

for the system to accurately detect their respiration rate.

Furthermore, the system is able to automatically respond to

respiration failure by triggering a bed adjustment that alters

the patients sleeping posture.

Due to the nature

of

the monitoring method, the respiration

measurements can be slightly impacted by the weight and

position of the patient. The peak detection algorithm might

need to be customized to the specific patient attributes.

Because

of

limited access to bed functions, the bed

adjustment method employed in this project was a

modification in the overall tilt of the hospital bed. Other

adjustments are possible, like the ability to roll the patient to

one side, but are not implemented in this project. While not

necessary for the project, more in-depth access to the various

bed adjustment functions could provide a more beneficial

treatment to obstructive sleep apnea.

V. CONCLUSIONS

In conclusion, this project demonstrates the possibility to

monitor a patient's respiration rate in an advanced hospital

bed with no need for constraining or invasive medical

equipment. Additionally, with the use

of

a medical device

communication protocol, a further benefit can be realized by

providing an automated first response to a patient suffering

from obstructive sleep apnea.

ACKNOWLEDGMENTS

This study was supported by the University of New

Hampshire. The authors gratefully thank Mr. Frank Hludik

from UNH, Mr. Wayne Smith from UNH, and Mr. William

Seitz, President

of

IXXAT for their help and support.

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