Parkinson’s Disease (PD) is a neurodegenerative disease that predominantly alter patients’ motor performance and compromises the speed, the automaticity and fluidity of natural movements. The patients fluctuate between periods in which they can move almost normally for some hours (ON state) and periods with motor disorders (OFF state). Gait properties are affected by the motor state of a patient: reduced stride length, reduced gait speed, increased stride width etc. The ability to assess the motor states (ON/OFF) on a continuous basis for long time without disturbing the patients’ daily life activities is an important component of PD management. An accurate report of motor states could allow clinics to adjust the medication regimen to avoid OFF periods. The real-time monitoring will also allow an online treatment by combining, for instance, with automatic drug-administration pump doses. Many studies have attempted to extract gait properties through a belt-worn single tri-axial accelerometer. In this paper, a user friendly position is proposed to place the accelerometer and three step detection methods and three step length estimators are compared considering the proposed sensor placement in signals obtained from healthy volunteers and PD patients. Adaptation methods to these step length estimators are also proposed and compared. The comparison shows that the adapted estimators improve the performance with the new proposed step detection method and reduce errors in respect of the original methods.