A Voice Command-Based Digital Microfluidic Platform for Programmable Hands-Free Droplet Manipulation

Digital microfluidics (DMF) platforms are automated sample-processing platforms that can electrically manipulate nanoliter-to-microliter-scale droplets to perform various droplet operations, such as transport, merging, splitting, and mixing. However, conventional DMF platforms mainly rely on GUI-based operation, requiring physical input devices. In this study, we propose a voice-command-based DMF platform that converts the user’s voice commands into electrode activation sequences for droplet manipulation through three components: a speech recognition module, a control signal conversion module, and a droplet actuation unit. The platform successfully executed voice commands for directional movement, target-position transport, merging, splitting, and repeated movement. The results confirmed that diverse voice commands could be converted into corresponding electrode activation sequences and executed as physical droplet manipulation. Quantitative evaluation showed a command-processing latency of 0.3–0.5 s and an average command execution accuracy of 93%. These values were obtained from a single English-speaking experimenter using predefined commands under uncharacterized laboratory noise conditions. Furthermore, a mixing operation composed of transport, merging, and repeated movement demonstrated the extensibility of the proposed framework to complex multistep droplet protocols. These results suggest that voice commands can serve as an intuitive hands-free interface for DMF platforms while reducing dependence on physical input devices.