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Current evidence has shown that, overall, actigraphy is an excellent tool for unobtrusive documentation of sleep/wake activity in normal individuals. However, a number of methodological issues remain to be resolved to warrant its use in clinical research. In this paper, we report the results of a study aimed at the development of a new scoring software that can accurately identify sleep and wakefulness. Using total sleep time as an index of comparison, the software was optimized on a calibration sample and prospectively tested on a validation sample. A strong correlation coefficient (r = 0.93, p < 0.008), with an average discrepancy value of 10 minutes, was observed for the calibration sample. The application of the optimal software to the validation sample revealed an even higher correlation coefficient (r = 0.97, p < 0.0001), with an average discrepancy value of 12 minutes.
Jean‐Louis et al. (Fri,) studied this question.