The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control

Abstract

Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions—including Parkinson’s disease, ataxia, and dementia—we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel ‘big data’ approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction.

Prediction of Individual Progression Rate in Parkinson’s Disease Using Clinical Measures and Biomechanical Measures of Gait and Postural Stability

“…Gait and postural stability measures were chosen as independent variables for our models because they have been previously found to be predictive of PD risk, disease severity, and PD diagnosis. 2,3 Baseline clinical measures were also investigated because of the potential they have to be predictive of PD progression rate. The most closely related study is by Latourelle et al, 4 where the predictive power of a composite biomarker set consisting of genetic, CSF, DaTscan, clinical and demographic features was examined.…”

Gait Asymmetry Post-Stroke: Determining Valid and Reliable Methods Using a Single Accelerometer Located on the Trunk

“…Instrumented walkways can objectively measure asymmetry and have shown excellent intra and inter-rater reliability in subacute stroke [11]. Practically, they are costly and need a controlled dedicated environment with a trained specialist to operate; therefore, they are mainly limited to research settings [12]. From a biomechanical perspective, they limit the number of steps collected per trial and solely obtain information of the participant's footfall.…”

“…Traditionally, gaining this information would rely on three-dimensional motion analysis systems. However, due to the even higher cost, required experience, and time to use relative to instrumented mats, their application is also limited to research settings [12]. Therefore, a need exists for a valid tool that is capable of quantifying whole body asymmetry, while also being feasible for routine clinical adoption.Wearable accelerometers are a relatively low-cost alternative that are capable of measuring human movement from a variety of contexts while capturing parameters that are difficult to quantify from clinical inspection by the human eye [1,14].…”

Towards ecologically valid biomarkers: real-life gait assessment in cerebellar ataxia

“…Moreover, driven by advances in sensor technologies, wearable sensors increasingly enable remote capturing of patients' movements in their real life. This might allow to capture patients' real-world motor performance and ecologically meaningful intervention-induced improvements, rather than "snapshot" performance during constrained and partly "artificial" surrogate motor tasks assessed by clinical scores or lab conditions 21 .…”

“…For both types of trials, measuring real-life movements bears several other advantages -in addition to the higher effect sizes gained from real-life assessments, likely caused by larger amount of sampled walking strides. These advantages include objective quantitative measurement of (i) day-to day variability instead of snapshot evaluations weeks or months apart during clinical visits21 and of (ii) patients' real-world motor performance instead of partly "artificial" motor tasks of clinical scores or lab conditions, which serve as surrogate parameters at best. While assessment of constrained tasks at snapshot visits represents patients' real-world functioning only in a limited fashion51 , measures of real-life motor performance add ecological validity and can thus help to inform upcoming treatment trials in degenerative cerebellar ataxias and FDA approval of novel treatments.…”