Accuracy of Step Count Estimations in Parkinson's Disease Can Be Predicted Using Ambulatory Monitoring

Navid Shokouhi; Hamid Khodakarami; Chathurini Fernando; Sarah Osborn; Malcolm Horne

doi:10.3389/fnagi.2022.904895

Accuracy of Step Count Estimations in Parkinson's Disease Can Be Predicted Using Ambulatory Monitoring

Front Aging Neurosci. 2022 Jun 16:14:904895. doi: 10.3389/fnagi.2022.904895. eCollection 2022.

Authors

Navid Shokouhi¹, Hamid Khodakarami¹, Chathurini Fernando^{2

3}, Sarah Osborn^{2

3}, Malcolm Horne^{2

3}

Affiliations

¹ Global Kinetics Pty Ltd., Melbourne, VIC, Australia.
² Parkinson's Laboratory, Florey Institute of Neurosciences and Mental Health, Parkville, VIC, Australia.
³ Department of Clinical Neurosciences, St Vincent's Hospital, Fitzroy, VIC, Australia.

Abstract

Objectives: There are concerns regarding the accuracy of step count in Parkinson's disease (PD) when wearable sensors are used. In this study, it was predicted that providing the normal rhythmicity of walking was maintained, the autocorrelation function used to measure step count would provide relatively low errors in step count.

Materials and methods: A total of 21 normal walkers (10 without PD) and 27 abnormal walkers were videoed while wearing a sensor [Parkinson's KinetiGraph (PKG)]. Median step count error rates were observed to be <3% in normal walkers but ≥3% in abnormal walkers. The simultaneous accelerometry data and data from a 6-day PKG were examined and revealed that the 5th percentile of the spectral entropy distribution, among 10-s walking epochs (obtained separately), predicted whether subjects had low error rate on step count with reference to the manual step count from the video recording. Subjects with low error rates had lower Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) scores and UPDRS III Q10-14 scores than the high error rate counterparts who also had high freezing of gait scores (i.e., freezing of gait questionnaire).

Results: Periods when walking occurred were identified in a 6-day PKG from 190 non-PD subjects aged over 60, and 155 people with PD were examined and the 5th percentile of the spectral entropy distribution, among 10-s walking epochs, was extracted. A total of 84% of controls and 72% of people with PD had low predicted error rates. People with PD with low bradykinesia scores (measured by the PKG) had step counts similar to controls, whereas those with high bradykinesia scores had step counts similar to those with high error rates. On subsequent PKGs, step counts increased when bradykinesia was reduced by treatment and decreased when bradykinesia increased. Among both control and people with PD, low error rates were associated with those who spent considerable time making walks of more than 1-min duration.

Conclusion: Using a measure of the loss of rhythmicity in walking appears to be a useful method for detecting the likelihood of error in step count. Bradykinesia in subjects with low predicted error in their step count is related to overall step count but when the predicted error is high, the step count should be assessed with caution.

Keywords: Parkinson’s disease; balance; freezing of gait; gait; sensors; step count.