Objective: To evaluate the ability of inertial measurement units (IMUs) in detecting the severity of motor symptoms in Parkinson’s disease (PD) by examining the relationship between IMU-derived gait parameters and established disease severity scales, including the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS III), Hoehn and Yahr (H&Y) scale, and Postural Instability and Gait Disorders (PIGD) scale.

Background: PD is a progressive neurodegenerative disorder, traditional clinical assessments of PD severity are subjective and prone to variability. Wearable sensors, particularly IMUs, offer an objective and quantitative approach to assessing gait abnormalities, which are critical markers of disease progression. However, the utility of IMU-derived gait parameters as biomarkers of PD severity remains underexplored.

Method: A systematic search was conducted across PubMed, Web of Science, and Cochrane Central databases from January 1, 2007, to February 20, 2024. Studies were included if they assessed gait parameters using IMUs in PD patients and reported correlations with MDS-UPDRS III, H&Y, or PIGD scales. Data extraction included study characteristics, participant demographics, sensor details, and gait assessment protocols.

Results: The review included 93 studies, with 21 providing data for meta-analysis. Key findings revealed significant negative correlations between gait velocity with MDS-UPDRS III, H&Y, and PIGD scales. Furthermore, negative correlations between toe off angle, and strike angle with MDS-UPDRS III and H&Y. Positive correlations were observed for stance time and step time, indicating longer durations in more severe PD. Sensor distribution analysis showed a focus on lower body kinematics, with the feet and waist being the most common sensor locations. The majority of studies demonstrated low risk of bias, supporting the reliability of the findings.

Conclusion: Gait velocity, stride length, and strike angle, show promise as objective biomarkers for assessing PD severity. These findings highlight the potential of wearable sensors to complement traditional clinical assessments, enabling more precise monitoring of disease progression and treatment efficacy. This study underscores the importance of integrating wearable technology into PD management to improve diagnostic accuracy and patient outcomes.

Frequency and percentage distribution

Correlation between gait parameters and scales

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MDS Abstracts - https://www.mdsabstracts.org/abstract/can-wearable-inertial-sensors-accurately-reflect-parkinsons-disease-severity-a-systematic-review-and-meta-analysis/