Freezing of gait (FOG) is a common gait deficit in advanced Parkinsonpsilas disease (PD). It is often a cause of falls, interferes with daily activities and significantly impairs quality of life. Gait deficits in PD patients are often resistant to pharmacologic treatment; therefore effective nonpharmacologic assistance is needed. In this paper we show the potential of context aware assistance for PD patients with FOG and present our first results on start and turn FOG assistance using our modular wearable research platform. We developed a real-time FOG detection system which provides external acoustic cues when FOG is detected from on-body motion sensors, until the subject resumes walking. In an evaluation study, ten PD patients tested our device. We recorded over 8 h of data. Eight patients experienced FOG during the study, and 237 FOG events have been identified by physiotherapists in a post video analysis. For the first time PD patients with the FOG syndrome were assisted by a context-aware wearable system. We report a high accuracy of freeze detection (73.1% sensitivity, 81.6% specificity, user independent). Based on subjective reports, the majority of patients indicated a benefit from the automatic cueing. We discuss how additional sensor modalities can paint a more complete view of the userpsilas context and may increase the systempsilas accuracy, decrease its latency, and eventually allow going from freeze detection to freeze preemption.