Category: Technology
Objective: The objective of this pilot study is to present data demonstrating the ability of a wearable medical device combining plantar pressure sensors, accelerometers, and gyroscopes for the assessments of gait-related motor symptom severity and their fluctuation during ON and OFF states in Parkinson’s disease (PD) under ambulatory conditions.
Background:
PD symptoms vary within and across patients over time, complicating the benchmarking of symptom severity at infrequent clinic visits and subsequent treatment decisions.
Method:
Gait functions were assessed in 21 PD patients, mean age: 63.7 years, mean disease duration: 9 years, H&Y II/III, during both ON and OFF states, using MDS-UPDRS part III and a newly developed technology to evaluate motor functions including gait characteristics. We used integrated sensor insoles to measure gait spatiotemporal parameters and plantar pressure. The technology combines pressure sensors and an inertial measurement unit allowing real-time temporal and spatial gait parameters. Gait parameters were measured during ON and OFF states and compared for each. Correlations between gait parameters and MDS-UPDRS III were evaluated. At the patient level, a decision tree learning model on the gait parameters ON and OFF was applied.
Results:
Gait parameters mean speed, stride length, the norm of center of pressure and the variation of weight transfer have shown a significant difference between ON and OFF states (p-value < 0.05). The mean speed was inversely correlated with the MDS- UPDRS III and the ON/OFF states (pearson correlation coefficient, r < -0.7). By using a decision tree learning model, an average score of 0.84 and 0.82 was obtained for sensitivity and specificity, respectively.
Conclusion:
Thus, this technology could provide measures of symptom severity, fluctuations of symptoms and progression complementary to established gait-related outcome measures not only in as ambulatory assessment under clinical settings as shown in this pilot study but also during unsupervised in-home testing, enabling better treatment decisions.
To cite this abstract in AMA style:
G. Monneret, D. Jacobs, L. Farid, A. Post, C. Moreau, G. Baille. Pilot study to assess gait-related motor symptoms in Parkinson’s disease by using a unique passive monitoring wearable technology [abstract]. Mov Disord. 2021; 36 (suppl 1). https://www.mdsabstracts.org/abstract/pilot-study-to-assess-gait-related-motor-symptoms-in-parkinsons-disease-by-using-a-unique-passive-monitoring-wearable-technology/. Accessed November 22, 2024.« Back to MDS Virtual Congress 2021
MDS Abstracts - https://www.mdsabstracts.org/abstract/pilot-study-to-assess-gait-related-motor-symptoms-in-parkinsons-disease-by-using-a-unique-passive-monitoring-wearable-technology/