Premium
Apnoea detection: human performance and reliability of a computer algorithm
Author(s) -
Macey PM,
Ford RPK,
Brown PJ,
Larkin J,
Fright WR,
Garden KL
Publication year - 1995
Publication title -
acta pædiatrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 115
eISSN - 1651-2227
pISSN - 0803-5253
DOI - 10.1111/j.1651-2227.1995.tb13505.x
Subject(s) - reliability (semiconductor) , breathing , medicine , consistency (knowledge bases) , signal (programming language) , sleep (system call) , computer science , pattern recognition (psychology) , artificial intelligence , anesthesia , power (physics) , physics , quantum mechanics , programming language , operating system
We examined the consistency of apnoea recognition between three human experts. The hypothesis was that computer detection of apnoea could emulate human expert apnoea recognition. The aim was to detect apnoeas with the highest possible accuracy from a single breathing signal, by both human experts and computer. Three human experts independently examined recordings of breathing waveform from overnight sleep studies from 10 infants aged 3‐17 weeks. All apnoeas of 5 s or more were identified and reviewed. However, there still remained 10% disagreement. A computer apnoea detector was implemented. An algorithm analysed statistical properties of the signal to find breathing pauses. Optimal performance was 1 % missed apnoeas (compared with the agreed apnoeas identified by the three experts) and 29% false detections. This computer algorithm reliably identified most apnoeas but did not replace the human expert. Algorithm, apnoea, breathing, detection, expert