Abstract: A method for stabilizing disrupted neural signals received by a brain-computer interface (BCI), where a translation model is trained on a clean and disrupted dataset and is used to translate a disrupted signal to a clean signal. The clean dataset is based on the data that is received the same day the BCI is calibrated and the disrupted dataset is based on data received the same day that the model is trained. Based on the variation in daily signal disruption, the training model is retrained each day and a new translation model is applied to a disrupted dataset.

Abstract: A sleep induction device includes a headband, multiple transcranial stimulation electrodes, and control electronics to drive the electrodes. The sleep induction device may be worn by an awake user prior to attempting sleep. The control electronics are configured to cause the stimulation electrodes to emit a sequence of stimulation waveforms separated by interstimulus periods. The stimulation waveforms may have the characteristics of low-delta waveforms that may characterize non-REM stage 3 sleep. The stimulation period may last from about 4-8 seconds and the interstimulus period may last from about 10 to 30 seconds. A sleep induction session may include multiple alternating stimulation and non-stimulation periods. The sleep induction session may last for about 5 minutes to about 30 minutes.