Habitual snoring has been known to increase the risk for serious health problems in addition to affecting the quality of others' sleep. Several recent consumer products aim to automatically detect snoring events and wake the snorer to elicit a posture change. In this paper, we present a study comparing two of the methods, electromyography vs. accelerometry, proposed for automated snoring detection and incorporation of these into a wearable system. The study includes (a) the testing of various sensor configurations and placements to obtain optimal electromyography and accelerometry signals, (b) a review of the accuracy of a variety of snore detection algorithms from previously attained biological signals, and (3) design of an embedded device with integrated sensors and haptic feedback capability. Our preliminary results indicate superiority of accelerometry over electromyography. Further research opportunities to prove the concept and improve the design are then detailed for future work.