Background The effects of levodopa on balance and gait function in people with Parkinson’s disease (PD) is controversial. This study compared the relative responsiveness to levodopa on six domains of balance and gait: postural sway in stance, gait pace, dynamic stability, gait initiation, arm swing, and turning in people with mild and severe PD, with and without dyskinesia. Methods We studied 104 subjects with idiopathic PD (Hohen & Yahr II (n=52) and III-IV (n=52)) and 64 age-matched controls. Subjects performed a mobility task in the practical OFF state and ON levodopa: standing quietly for 30 seconds, initiating gait, walking 7 meters, and turning 180 degrees. Thirty-four measures of mobility were computed from inertial sensors. Standardized response means were used to determine the relative responsiveness to levodopa. Results The largest improvements with levodopa were found for arm swing and pace-related gait measures. Gait dynamic stability was unaffected by PD and not responsive to levodopa. Levodopa reduced turning duration, but only in subjects with severe PD. In contrast to gait, postural sway in quiet standing increased with levodopa, especially in the more severely affected subjects. The increase in postural sway, as well as decrease in turning duration and exaggerated arm swing with levodopa was observed only for subjects with dyskinesia at the time of testing. Conclusions The observed spectrum of levodopa responsiveness in balance and gait measures suggests multiple neural circuits control balance and gait. Many of the negative effects of levodopa may be directly or indirectly caused by dyskinesia.

Objective: Gait provides a sensitive measurement for signs of aging and neurodegenerative conditions. Measurement of gait is transitioning from the laboratory environment to the clinic with the use of inertial measurement units, providing a simple and cost-effective assessment tool. However, such assessments first need validation against reference systems. The aim of this study was to validate the APDM Mobility Lab (ML) system (version 2) against a pressure sensor walkway in younger adults (n = 18), older adults (n = 18) and people with mild Parkinson's disease (n = 21) in the laboratory. Approach: Participants completed a two-minute walk over a pressure sensor walkway whilst wearing three sensors (strapped to the lumbar spine and both feet). Comparison of output from the systems was then performed. Main results: Overall, we identified that ML provided good to excellent agreement (ICC > 0.75) for gait velocity, stride length, stride length SD, cadence, stride time and stride time SD. Measures of double support time, single support time and swing time had moderate to poor agreement (ICC 0.213-0.725), particularly for younger adults and PD. Significance: Overall, Mobility Lab provides a valid system for gait data collection for clinical and research application.

Background Although a growing number of studies focus on the measurement and detection of freezing of gait (FoG) in laboratory settings, only a few studies have attempted to measure FoG during daily life with body-worn sensors. Here, we presented a novel algorithm to detect FoG in a group of people with Parkinson’s disease (PD) in the laboratory (Study I) and extended the algorithm in a second cohort of people with PD at home during daily life (Study II). Methods In Study I, we described of our novel FoG detection algorithm based on five inertial sensors attached to the feet, shins and lumbar region while walking in 40 participants with PD. We compared the performance of the algorithm with two expert clinical raters who scored the number of FoG episodes from video recordings of walking and turning based on duration of the episodes: very short (< 1 s), short (2–5 s), and long (> 5 s). In Study II, a different cohort of 48 people with PD (with and without FoG) wore 3 wearable sensors on their feet and lumbar region for 7 days. Our primary outcome measures for freezing were the % time spent freezing and its variability. Results We showed moderate to good agreement in the number of FoG episodes detected in the laboratory (Study I) between clinical raters and the algorithm (if wearable sensors were placed on the feet) for short and long FoG episodes, but not for very short FoG episodes. When extending this methodology to unsupervised home monitoring (Study II), we found that percent time spent freezing and the variability of time spent freezing differentiated between people with and without FoG (p < 0.05), and that short FoG episodes account for 69% of the total FoG episodes. Conclusion Our findings showed that objective measures of freezing in PD using inertial sensors on the feet in the laboratory are matching well with clinical scores. Although results found during daily life are promising, they need to be validated. Objective measures of FoG with wearable technology during community-living would be useful for managing this distressing feature of mobility disability in PD.

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