Application of single wrist-wearable accelerometry for objective motor diary assessment in fluctuating Parkinson's disease

Advanced Parkinson's disease (PD) is characterized by motor fluctuations including unpredictable oscillations remarkably impairing quality of life. Effective management and development of novel therapies for these response fluctuations largely depend on clinical rating instruments such as the widely-used PD home diary, which are associated with biases and errors. Recent advancements in digital health technologies provide user-friendly wearables that can be tailored for continuous monitoring of motor fluctuations. Their criterion validity under real-world conditions using clinical examination as the gold standard remains to be determined. We prospectively examined this validity of a wearable accelerometer-based digital Parkinson's Motor Diary (adPMD) using the Parkinson's Kinetigraph (PKG®) in an alternative application by converting its continuous data into one of the three motor categories of the PD home diary (Off, On and Dyskinetic state). Sixty-three out of 91 eligible participants with fluctuating PD (46% men, average age 66) had predefined sufficient adPMD datasets (>70% of half-hour periods) from 2 consecutive days. 92% of per-protocol assessments were completed. adPMD monitoring of daily times in motor states showed moderate validity for Off and Dyskinetic state (ICC = 0.43-0.51), while inter-rating methods agreements on half-hour-level can be characterized as poor (median Cohen's κ = 0.13-0.21). Individualization of adPMD thresholds for transferring accelerometer data into diary categories improved temporal agreements up to moderate level for Dyskinetic state detection (median Cohen's κ = 0.25-0.41). Here we report that adPMD real-world-monitoring captures daily times in Off and Dyskinetic state in advanced PD with moderate validities, while temporal agreement of adPMD and clinical observer diary data is limited.

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

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.

A method for measuring time spent in bradykinesia and dyskinesia in people with Parkinson's disease using an ambulatory monitor

Background

Fluctuations in motor function in Parkinson’s Disease (PD) are frequent and cause significant disability. Frequently device assisted therapies are required to treat them. Currently, fluctuations are self-reported through diaries and history yet frequently people with PD do not accurately identify and report fluctuations. As the management of fluctuations and the outcomes of many clinical trials depend on accurately measuring fluctuations a means of objectively measuring time spent with bradykinesia or dyskinesia would be important. The aim of this study was to present a system that uses wearable sensors to measure the percentage of time that bradykinesia or dyskinesia scores are above a target as a means for assessing levels of treatment and fluctuations in PD.

Methods

Data in a database of 228 people with Parkinson’s Disease and 157 control subjects, who had worn the Parkinson’s Kinetigraph ((PKG, Global Kinetics Corporation™, Australia) and scores from the Unified Parkinson’s Disease Rating Scale (UPDRS) and other clinic scales were used. The PKG’s provided score for bradykinesia and dyskinesia every two minutes and these were compared to a previously established target range representing a UPDRS III score of 35. The proportion of these scores above target over the 6 days that the PKG was worn were used to derive the percent time in bradykinesia (PTB) and percent time in dyskinesia (PTD). As well, a previously describe algorithm for estimating the amplitude of the levodopa response was used to determine whether a subject was a fluctuator or non-fluctuator.

Results

Using this approach, a normal range of PTB and PTD based on Control subject was developed. The level of PTB and PTD experienced by people with PD was compared with their levels of fluctuation. There was a correlation (Pearson’s ρ = 0.4) between UPDRS II scores and PTB: the correlation between Parkinson Disease Questionnaire scores and UPDRS Total scores and PTB and slightly lower. PTB and PTD fell in response to treatment for bradykinesia or dyskinesia (respectively) with greater sensitivity than clinical scales.

Conclusions

This approach provides an objective assessment of the severity of fluctuations in Parkinson’s Disease that could be used in in clinical trials and routine care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00905-4.

Duobinary pulse shaping for frequency chirp enabled complex modulation

The frequency chirp of optical direct modulation (DM) used to be a performance barrier of optical transmission system, because it broadens the signal optical spectrum, which becomes more susceptible to chromatic dispersion induced inter-symbol interference (ISI). However, by considering the chirp as frequency modulation, the single DM simultaneously generates a 2-D signal containing the intensity and phase (namely, the time integral of frequency). This complex modulation concept significantly increases the optical signal to noise ratio (OSNR) sensitivity of DM systems. This Letter studies the duobinary pulse shaping (DB-PS) for chirp enabled DM and its impact on the optical bandwidth and system OSNR sensitivity. DB-PS relieves the bandwidth requirement, at the sacrifice of system OSNR sensitivity. As DB-PS induces a controlled ISI, the receiver requires one more tap for maximum likelihood sequence estimation (MLSE). We verify this modified MLSE with a 10-Gbaud duobinary PAM-4 transmission experiment.