Parkinson's disease (PD) is the second most common neurodegenerative disorder, with serious motor and non-motor complications associated. Freezing of gait (FOG) is a form of akinesia (loss of movement) affecting most of PD patients in advanced stages of the disease, and represents one of the most disabling symptoms of PD. Current therapies are highly effecting in ameliorating the symptoms of the disease, but their delivery need to be patient-specific, based on motor fluctuations and progression of the disease in each patient. Wereable sensors have been recently proposed for providing objective assessment of FOG during the real life. This study aimed to the construction of an algorithm capable of automated FOG detection, in order to prove the feasibility of a simple, small and low cost detection system for home monitoring of FOG episodes in PD patients.