Non-verbal information is essential to understand intentions and emotions and to facilitate social interaction between humans and between humans and computers. One reliable source of such information is the eyes. We investigated the eye-based interaction (recognizing eye gestures or eye movements) using an eyewear device for facial expression recognition. The device incorporates 16 low-cost optical sensors. The system allows hands-free interaction in many situations. Using the device, we evaluated three eye-based interactions. First, we evaluated the accuracy of detecting the gestures with nine participants. The average accuracy of detecting seven different eye gestures is 89.1% with user-dependent training. We used dynamic time warping (DTW) for gesture recognition. Second, we evaluated the accuracy of eye gaze position estimation with five users holding a neutral face. The system showed potential to track the approximate direction of the eyes, with higher accuracy in detecting position y than x. Finally, we did a feasibility study of one user reading jokes while wearing the device. The system was capable of analyzing facial expressions and eye movements in daily contexts.