Across species, sleep is characterized by a complex architecture. Sleep deprivation is a classic method to study the consequences of sleep loss, which include alterations in the activity of sleep circuits and detrimental consequences on well being. Automating the observation and manipulation of sleep is advantageous to study its regulation and functions. Caenorhabditis elegans shows sleep behavior similar to other animals that have a nervous system. However, a method for real-time automatic sleep detection that allows sleep-specific manipulations has not been established for this model animal. Also, our understanding of how sleep deprivation affects sleep neurons in this system is incomplete. Here we describe a system for real-time automatic sleep detection of C. elegans grown in microfluidic devices based on a frame-subtraction algorithm using a dynamic threshold. As proof of principle for this setup, we used automated mechanical stimulation to perturb sleep behavior and followed the activity of the sleep-active RIS neuron. We show that our system can automatically detect sleep bouts and deprive worms of sleep. We found that mechanical stimulation generally leads to the activation of the sleep-active RIS neuron, and this stimulation-induced RIS depolarization is most prominent during sleep deprivation.