Comparison of Laboratory and Daily-Life Gait Speed Assessment during ON and OFF States in Parkinson’s Disease

Abstract

Accurate assessment of Parkinson’s disease (PD) ON and OFF states in the usual environment is essential for tailoring optimal treatments. Wearables facilitate measurements of gait in novel and unsupervised environments; however, differences between unsupervised and in-laboratory measures have been reported in PD. We aimed to investigate whether unsupervised gait speed discriminates medication states and which supervised tests most accurately represent home performance. In-lab gait speeds from different gait tasks were compared to home speeds of 27 PD patients at ON and OFF states using inertial sensors. Daily gait speed distribution was expressed in percentiles and walking bout (WB) length. Gait speeds differentiated ON and OFF states in the lab and the home. When comparing lab with home performance, ON assessments in the lab showed moderate-to-high correlations with faster gait speeds in unsupervised environment (r = 0.69; p < 0.001), associated with long WB. OFF gait assessments in the lab showed moderate correlation values with slow gait speeds during OFF state at home (r = 0.56; p = 0.004), associated with short WB. In-lab and daily assessments of gait speed with wearables capture additional integrative aspects of PD, reflecting different aspects of mobility. Unsupervised assessment using wearables adds complementary information to the clinical assessment of motor fluctuations in PD.

A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts

“…As there is increasing evidence that gait measured in the lab does not reflect daily-life gait [ 19 , 20 , 21 ], there is increasingly more interest in measurement systems that allow for continuous gait analysis in ambulatory settings. Therefore, the use of inertial measurement units (IMUs) is especially attractive, as these can be used to measure gait in ecologically valid environments, such as the home environment, thereby painting a more complete picture of health status [ 22 , 23 ] and providing clinical information that is complementary to standardized lab-based assessments [ 20 , 21 , 24 , 25 ].…”

Comparison on gait characteristics between controlled and free-living conditions in old adults

“…This value is also a good choice according to the previous research [8], in which bout length is suggested to be larger than 10s or longer for better between group difference of gait characteristics. Another research by Corrà et al [7] also generates gait speed per bout on a interval longer than 15s so as to guarantee the accuracy of further analysis. Gait characteristics in this research are derived from video data collected with 3D camera as biosensor.…”

“…They found that gait speed is distinct in different conditions and suggested to combine them together in predicting disease conditions. Corrà et al [7] studied how to use gait speed in daily life to discriminate disease ON and OFF states. They found that gait speed in daily life reflects different aspects of mobility of PD and can complement that in clinic.…”

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

“…Altered gait characteristics occur early in Parkinson’s disease (PD) ( Rehman et al, 2019 ) and even years prior to diagnosis ( Del Din et al, 2019 ), with the most consistent abnormalities being a slower gait, increased variability, and asymmetry ( Del Din et al, 2019 ; Rehman et al, 2019 ; Corra et al, 2021 ). These features are related to bradykinesia and improve with levodopa ( Chien et al, 2006 ; Bryant et al, 2016 ; Corra et al, 2021 ).…”

“…Altered gait characteristics occur early in Parkinson’s disease (PD) ( Rehman et al, 2019 ) and even years prior to diagnosis ( Del Din et al, 2019 ), with the most consistent abnormalities being a slower gait, increased variability, and asymmetry ( Del Din et al, 2019 ; Rehman et al, 2019 ; Corra et al, 2021 ). These features are related to bradykinesia and improve with levodopa ( Chien et al, 2006 ; Bryant et al, 2016 ; Corra et al, 2021 ). Approximately 25% of people with PD (PwP) have unstable posture at diagnosis ( Kohat et al, 2021 ), and the incidence increases with time from diagnosis ( Kohat et al, 2021 ) often with the development of freezing of gait (FOG) ( Ge et al, 2020 ).…”