Modernizing Daily Function Assessment in Parkinson's Disease Using Capacity, Perception, and Performance Measures

Abstract

A BS TRACT: Many disease symptoms restrict the quality of life of the affected. This usually occurs indirectly, at least in most neurological diseases. Here, impaired daily function is interposed between the symptoms and the reduced quality of life. This is reflected in the International Classification of Function, Disability and Health model published by the World Health Organization in 2001. This correlation between symptom, daily function, and quality of life makes it clear that to evaluate the success of a therapy and develop new therapies, daily function must also be evaluated as accurately as possible. However, daily function is a complex construct and therefore difficult to quantify. To date, daily function has been measured primarily by capacity (clinical assessments) and perception (surveys and patient-reported outcomes) assessment approaches. Now, daily function can be captured in a new dimension, that is, performance, through new digital technologies that can be used in the home environment of patients. This viewpoint discusses the differences and interdependencies of capacity, perception, and performance assessment types using the example of Parkinson's disease. Options regarding how future study protocols should be designed to get the most comprehensive and validated picture of daily function in patients are presented.

Effect of Fear of Falling on Mobility Measured During Lab and Daily Activity Assessments in Parkinson’s Disease

“…Training three classifiers based on three sets of features, i.e., F1, F2, and F3, revealed that set F1 led to the most accurate classifier to distinguish the PD-FOF+ from the PD-FOF− group (Table 4). This selection, including features from both the lab and daily activity assessments, further supports the usefulness of including daily activity assessments in clinical practice as they have complementary information to the assessments performed in the lab (Maetzler et al, 2021). The more accurate classification of FOF with lab features (F2), compared with daily activity features (F3, Table 4), suggests that capacity aspects play an important role for the definition of FOF (Maetzler et al, 2021) and functional tests in the lab should always be performed for the evaluation in FOF.…”

“…This selection, including features from both the lab and daily activity assessments, further supports the usefulness of including daily activity assessments in clinical practice as they have complementary information to the assessments performed in the lab (Maetzler et al, 2021). The more accurate classification of FOF with lab features (F2), compared with daily activity features (F3, Table 4), suggests that capacity aspects play an important role for the definition of FOF (Maetzler et al, 2021) and functional tests in the lab should always be performed for the evaluation in FOF. Still, the inclusion of environmental context and psychological factors from daily life is a valuable addition and can contribute to increased specificity.…”

Will Artificial Intelligence Outperform the Clinical Neurologist in the Near Future? Yes

“…The concept of digital phenotyping has been applied in PD where the moment‐by‐moment quantification of the individual‐level patient phenotype with a personal digital device is now possible 18 . These capabilities offer several advantages for individualized and remote assessment of patients with PD in their own environment that directly determines a patient's performance, not capacity to recall as with most rating scales, in their daily tasks, and extends the opportunity for remote assessment during the current pandemic situation or in the underserved regions where face‐to‐face evaluations are not possible 19,20 . Recent evidence, which could be applied to our example case, suggested that ML can analyze wearable data, providing feedback information on motor performances to neurologists for the adjustment of dopaminergic medications resulting in improved clinical outcomes 21 .…”

“…18 These capabilities offer several advantages for individualized and remote assessment of patients with PD in their own environment that directly determines a patient's performance, not capacity to recall as with most rating scales, in their daily tasks, and extends the opportunity for remote assessment during the current pandemic situation or in the underserved regions where face-to-face evaluations are not possible. 19,20 Recent evidence, which could be applied to our example case, suggested that ML can analyze wearable data, providing feedback information on motor performances to neurologists for the adjustment of dopaminergic medications resulting in improved clinical outcomes. 21 Further to this, the use of mobile health technologies equipped with AI could accelerate the transition of a single objective domain assessment (eg, tremor or dyskinesia) to a set of activities that are part of patient-centered digital outcome measures with various applications being implemented into realworld assessments and novel therapeutic evaluations.…”

Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol

“…Objective evaluation methods can provide additional and potentially more ecologically valid measures. Wearable technology, more specifically inertial measurement Sensors 2021, 21, 5833 2 of 13 units (IMUs) are highly suited for objective movement analysis and can even be used to analyse mobility patterns outside the clinic and praxis, i.e., the usual environment [6,7].…”