Nightcap: a home-based sleep monitoring system.
In an attempt to offer a home-based adjunct to traditional sleep laboratory methods, we developed a system to monitor sleep, and to predict algorithmically non-rapid-eye-movement (NREM) and rapid-eye-movement (REM) sleep states, using eye and body motility as the only parameters. Eye movement was measured using a strain gauge transducer applied to the eyelid of subjects, while body movement was measured using a piezo-ceramic phono cartridge. Both transducers were mounted on a tennis headband, along with electronics that amplified, filtered, and digitized the signals. Digital pulse signals were input to a portable computer in minute-long epochs, and state-predicting algorithms were run based on this motility data. Four subjects were monitored in the sleep lab with both our headgear and standard polysomnography. Hand-scored sleep records were compared with those predicted by computer algorithms. Algorithm-predicted states agreed with hand-scored ones an average of 85.57% (SEM +/- 1.7%). Mean values for sleep onset and REM latency were within 1.6 and 10.8 min of polysomnographic records, respectively. These results are encouraging, and suggest that this system could provide a comfortable, subject operable, and inexpensive method for the evaluation of sleep at home.
Mamelak
A
A
Laboratory of Neurophysiology, Harvard Medical School, Boston, Massachusetts 02115.
Hobson
J A
JA
D000328:Adult; D000465:Algorithms; D004569:Electroencephalography / Q000295:instrumentation*; D001330:Electronic Data Processing; D005260:Female; D006801:Humans; D008297:Male; D009068:Movement; D010045:Outpatients; D010361:Patients; D012890:Sleep; D012895:Sleep, REM