Understanding the accuracy of step count estimations in Parkinson’s Disease (PD) is crucial for effective monitoring. This study explored the use of wearable sensors to predict step count errors. By analyzing the autocorrelation function and spectral entropy distribution, researchers were able to determine the likelihood of low or high error rates. Individuals with PD who maintained normal rhythmicity in walking had significantly lower error rates. Furthermore, those with low bradykinesia scores (a measure of slowness of movement) had step counts similar to individuals without PD, while those with high bradykinesia scores showed higher error rates. Treatment that reduced bradykinesia corresponded to increased step counts, and vice versa. The study also found that longer-duration walks were associated with lower error rates. These findings suggest that assessing the loss of rhythmicity in walking can help identify potential errors in step counting for individuals with PD. It is important for healthcare professionals and researchers to consider these factors when interpreting step count data in PD patients. Read the full article to delve deeper into the research and its implications for PD management.

ObjectivesThere 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 MethodsA 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).ResultsPeriods 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.ConclusionUsing 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.

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