Abstract: Methods and apparatus for circadian lighting are disclosed. In particular, improved lighting is described in relation to a novel definition of an optimum relative circadian spectral sensitivity distribution (“Circadian Potency SSD”) with a peak sensitivity at approximately 470 nm-480 nm (preferable embodiments at 472 nm or 478 nm) with a full width at half maximum (“FWHM”) of approximately 50 nm which is skewed asymmetrically between approximately 440 nm and approximately 490 nm. Methods and approaches to determine the Circadian Potency of light sources from their spectral power distributions (SPD) and use the CircadianPotency SSD to optimize healthy circadian function under normal indoor and outdoor illumination conditions are described herein, and incorporated into various light sources, including white light sources, dimmable light sources, and daytime/nighttime light sources.

Abstract: A method and apparatus for determining, monitoring and predicting levels of alertness by detecting microsleep episodes includes a plurality of channel processing units and a channel combining unit. Each of the channel processing units receives an information channel which conveys information associated with the mental state of the subject, such as an EEG channel, and classifies the information into a distinct category. Such categories may include microsleep, non-microsleep, one or more of a plurality of stages of sleep, one or more of a plurality of stages of wakefulness, or a transition state characterized by a transition from one of the aforementioned states to another. Each of the channel processing units includes a neural network which has been trained with a set of example input/result vector pairs.

Abstract: A method and apparatus for determining, monitoring and predicting levels of alertness by detecting microsleep episodes includes a plurality of channel processing units and a channel combining unit. Each of the channel processing units receives an information channel which conveys information associated with the mental and behavorial state of the subject, such as for example an EEG channel, and classifies the information into a distinct category. Such categories may include microsleep, non-microsleep, one or more of a plurality of stages of sleep, one or more of a plurality of stages of wakefulness, or a transition state characterized by a transition from one of the aforementioned states to another. Each of the channel processing units includes a neural network which has been trained with a set of example input/result vector pairs.