Data-Driven Prediction of Freezing of Gait Events From Stepping Data.

Freezing of gait (FoG) is typically a symptom of advanced Parkinson's disease (PD) that negatively influences the quality of life and is often resistant to pharmacological interventions. Novel treatment options that make use of auditory or sensory cues might be optimized by prediction of freezing events. These predictions might help to trigger external sensory cues-shown to improve walking performance-when behavior is changed in a manner indicative of an impending freeze (i.

Ankle Push-Off Based Mathematical Model for Freezing of Gait in Parkinson's Disease.

Freezing is an involuntary stopping of gait observed in late-stage Parkinson's disease (PD) patients. This is a highly debilitating symptom lacking a clear understanding of its causes. Walking in these patients is also associated with high variability, making both prediction of freezing and its understanding difficult.