ACTIVITY-BASED SLEEP-WAKE IDENTIFICATION - AN EMPIRICAL-TEST OF METHODOLOGICAL ISSUES

The effects of actigraph placement and device sensitivity on actigraph ic automatic sleep-wake scoring were assessed using concomitant polyso mnographic and wrist actigraphic data from dominant and nondominant ha nds of 20 adults and 16 adolescents during 1 laboratory night. Althoug h activity levels differed between dominant and nondominant wrists dur ing periods of sleep (F = 4.57; p < 0.05) and wake (F = 15.5; p < 0.00 05), resulting sleep-wake scoring algorithms were essentially the same and were equally explanatory (R(2) = 0.64; P < 0.0001). When the slee p-wake scoring algorithm derived from the nondominant hand was used to score the nondominant data for sleep-wake, overall agreement rates wi th polysomnography scoring ranged between 91 and 93% for the calibrati on and validation samples. Results obtained with the same algorithm fo r the dominant-wrist data were within the same range. Agreement for sl eep scoring was consistently higher than for wake scoring. Statistical manipulation of activity levels before applying the scoring algorithm indicated that this algorithm is quite robust toward moderate changes in activity level. Use of ''twin-wrist actigraphy'' enables identific ation of artifacts that may result from breathing-related motions.