SLEEP 2011 Abstract Supplement

B. Clinical Sleep Science I. Sleep Disorders – Breathing
REI>19 (sensitivity=0.71±0.08, specificity=0.89±0.04). Best cut-off
for max h-REI with AHI>10 is max h-REI>17 (sensitivity=0.80±0.05,
specificity=0.76±0.09) and with AHI>30 is max h-REI>26 (sensitivity=0.93±0.04,
specificity=0.78±0.05)
Conclusion: Results show that best sensitivity for this ambulatory
screening device is obtained for severe apnea with the second criterion
max h-REI>26. Therefore this device seems to be appropriate to quickly
send patients with supposed severe OSAS to sleep specialist.
Support (If Any): PHILIPS-RESPIRONICS for technical support
0375
ASSESSMENT OF A SIMPLE PIEZOELECTRIC SENSOR
SYSTEM FOR APNEA/HYPOPNEA MONITORING
Sato S 1 , Koyama T 2 , Kanbayashi T 3 , Igarashi G 2 , Tokunaga J 3 , Sato M 3 ,
Watanabe H 2 , Ono K 1 , Ito H 2 , Shimizu T 3
1
Cell Physiology, Akita University Graduate School of Medicine, Akita,
Japan, 2 Cardiovascular and Respiratory Medicine, Akita University
Graduate School of Medicine, Akita, Japan, 3 Neuropsychiatry, Akita
University Graduate School of Medicine, Akita, Japan
Introduction: Polysomnography (PSG) is widely used for sleep analysis
and also for monitoring of apnea/hypopnea during sleep. However,
it is often unpleasant for patients because they must be attached with
a respiratory flow sensor to their nose and belt sensors to their chest
and abdomen. These uncomfortable sensor settings may induce a stress
that might affect the quality of sleep and the result of PSG. Therefore,
we designed a new piezoelectric transducer (PZT) sensor, which neither
contacts to their skin nor binds their body, for the noninvasive monitoring
of respiratory events, apnea/hypopnea.
Methods: A flat and thin PZT sensor (30 × 200 × 1 mm) was placed
under a towel on a bed on which total of 44 cardiology inpatients underwent
the simultaneous recording with the PZT sensor system and PSG.
Patients were scored as having sleep disordered breathing (SDB) when
they exhibited apneas/hypopneas of >30 times (AHI5 × 6h) in chainstokes-like
breathings in the PZT-sensor signal. Hypopneas were scored
as obstructive apneas in the PZT-sensor-signal analysis because they
were hardly distinguishable.
Results: In the PZT-sensor-signal analysis, we found SDB in 97%
(34/35) of the patients with Apnea Hypopnea Index (AHI) of >10 judged
by PSG, but no SDB was found in rest 9 patients with AHI 5) revealed
a sensitivity of 81% and specificity of 86% when compared to the
14-channel PSG.
Conclusion: A new algorithm for automated detection of respiratory
events that uses PM signals was developed and tested with high correlation,
sensitivity and specificity to a 14-channel PSG. Overall, this
algorithm could serve as an effective tool to enhance data analysis of PM
studies including home sleep evaluations.
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SLEEP, Volume 34, Abstract Supplement, 2011