A Wearable Mobility Monitoring System (WMMS) can be a useful tool for rehabilitation decision-making. This paper presents preliminary design and evaluation of a WMMS proof-of-concept system. Software was developed for the BlackBerry 9550, using the integrated three axes accelerometer, GPS, video camera, and timer to identify mobility changes-of-state (CoS) between static activities, walking-related activities, taking an elevator, bathroom activities, working in the kitchen, and meal preparation (five able-bodied subjects). This pilot project provides insight into new algorithms and features that recognize CoS and activities in real-time. Following features extraction from the sensor data, two decision trees were used to distinguish the CoS and activities. Real-time CoS identification triggered BlackBerry video recording for improved mobility context analysis during post-processing.