Gait monitoring system for patients with Parkinson’s disease

Abstract

BackgroundWearable monitoring devices based on inertial sensors have the potential to be used as a quantitative method in clinical practice for continuous assessment of gait disabilities in Parkinson’s disease (PD). MethodsThis manuscript introduces a new gait monitoring system adapted to patients with PD, based on a wearable monitoring device. To eliminate inter- and intra-subject variability, the computational method was based on heuristic rules with adaptive thresholds and ranges and a motion compensation strategy. The experimental trials involved repeated measurements of walking trials from two cross-sectional studies: the first study was performed in order to validate the effectiveness of the system against a robust 3D motion analysis with 10 healthy subjects; and the second-one aimed to validate our approach against a well-studied wearable IMU-based system on a hospital environment with 20 patients with PD. ResultsThe proposed system proved to be efficient (Experiment I: sensitivity = 95,09% and accuracy = 93,64%; Experiment II: sensitivity = 99,53% and accuracy = 97,42%), time-effective (Experiment I: earlies = 13,71 ms and delays = 12,91 ms; Experiment II: earlies = 12,94 ms and delays = 12,71 ms), user and user-motion adaptable and a low computational-load strategy for real-time gait events detection. Further, it was measured the percentage of absolute error classified with a good acceptability (Experiment I: 3,02 ≤ ε%≤12,94; Experiment II: 2,81 ≤ ε%≤13,45). Lastly, regarding the measured gait parameters, it was observed a reflection of the typical levels of motor impairment for the different disease stages. ConclusionThe achieved outcomes enabled to verify that the proposed system can be suitable for gait analysis in the assistance and rehabilitation fields.