This paper presents the results of the analysis of trends in the occurrence of eyeblinks for devising new input channels in handheld and wearable information devices. However, engineering a system that can distinguish between voluntary and spontaneous blinks is difficult. The study analyzes trends in the occurrence of eyeblinks of 50 subjects to classify blink types via experiments. However, noticeable differences between voluntary and spontaneous blinks exist for each subject. Three types of trends based on shape feature parameters (duration and amplitude) of eyeblinks were discovered. This study determines that the system can automatically and effectively classify voluntary and spontaneous eyeblinks.