Step Length Is a Promising Progression Marker in Parkinson's Disease

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 7; p. 2292
• Main Authors: Welzel, Julius, Wendtland, David, Warmerdam, Elke, Romijnders, Robbin, Elshehabi, Morad, Geritz, Johanna, Berg, Daniela, Hansen, Clint, Maetzler, Walter
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 25.03.2021; MDPI
• Subjects: Age; Brief Report; Evaluation; Gait; Gait Disorders, Neurologic; Gait recognition; Humans; inertial measurement unit; Inertial platforms; Markers; movement disorders; Parkinson Disease - diagnosis; Parkinson's disease; Sensors; Signs and symptoms; Technology assessment; Walking; Wearable Electronic Devices; Wearable technology; Germany; inertial measurement unit; movement disorders; gait; Parkinson’s disease
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s21072292

Current research on Parkinson's disease (PD) is increasingly concerned with the identification of objective and specific markers to make reliable statements about the effect of therapy and disease progression. Parameters from inertial measurement units (IMUs) are objective and accurate, and thus an interesting option to be included in the regular assessment of these patients. In this study, 68 patients with PD (PwP) in Hoehn and Yahr (H&Y) stages 1-4 were assessed with two gait tasks-20 m straight walk and circular walk-using IMUs. In an ANCOVA model, we found a significant and large effect of the H&Y scores on step length in both tasks, and only a minor effect on step time. This study provides evidence that from the two potentially most important gait parameters currently accessible with wearable technology under supervised assessment strategies, step length changes substantially over the course of PD, while step time shows surprisingly little change in the progression of PD. These results show the importance of carefully evaluating quantitative gait parameters to make assumptions about disease progression, and the potential of the granular evaluation of symptoms such as gait deficits when monitoring chronic progressive diseases such as PD.