Intelligent Fall Prevention for Parkinson’s Disease Patients based on Detecting Posture Instabilily and Freezing of Gait

Abstract

Parkinson's disease (PD) is a disorder that affects nerve cells in a part of the brain, and results from a progressive loss of dopaminergic and other sub-cortical neurons. Symptoms of Parkinson's disease may include resting tremor, bradykinesia, rigidity, a forward stooped posture, postural instability, and freezing of gait. As reported by several researchers, the forward stooped posture and freezing of gait are the most critical reasons to make the Parkinson's disease patients fall. The main objective of this research is to develop a fall prevention system for Parkinson's disease patients. There are two phases in the fall prevention protocol. The first phase is to detect and recognize the stooped posture and freezing of gait symptoms from the patient's movement activities. The next phase is to alarm an audio cue to break the block of freezing. An accelerometer based sensor network is designed to sense the movement information. The recorded data are transferred to the smartphone, which served as the core calculator unit, by Bluetooth communication protocol. The input signals are recognized and classified into the target symptoms. The main advantages of this proposed approach includes: (1) the safety: to detect the stooped posture and freezing of gait and to produce audio cue to help the patients to break the block; (2) the portability: not limited at specific locations; and (3) the expendability: easy to update or upgrade by using app install online.