This paper introduces an encapsulated sensor node that is devised to monitor and record motion patterns over long, quotidian periods of time with potential application in psychological studies. Its design fuses different sensing modalities to allow efficient capturing of tilt and acceleration stimuli, as well as embedded algorithms that abstract from the raw sensory data to indicative features. By combining tilt switches and accelerometers with customized processing techniques, it is argued that a power-efficient yet information-rich approach is reached for the observation and logging of human motion-based activity.