The aim of this study was to address whether deficits in the central cholinergic activity may contribute to the increased difficulty to allocate attention during gait in the elderly with heightened risk of falls. We recruited 50 participants with a history of two or more falls (33 patients with Parkinson's Disease and 17 older adults) and 14...
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2016 (v1)PublicationUploaded on: April 14, 2023
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2017 (v1)Publication
Background: Virtual reality (VR) technology is a relatively new rehabilitation tool that can deliver a combination of cognitive and motor training for fall prevention. The attitudes of older people to such training are currently unclear. Objective: This study aimed to investigate: (1) the attitudes of fall-prone older people towards fall...
Uploaded on: April 14, 2023 -
2024 (v1)Publication
Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a...
Uploaded on: October 16, 2024 -
2019 (v1)Publication
Introduction: Recent work suggests that wearables can augment conventional measures of Parkinson's disease (PD). We evaluated the relationship between conventional measures of disease and motor severity (e.g., MDS-UPDRS part III), laboratory-based measures of gait and balance, and daily-living physical activity measures in patients with PD....
Uploaded on: April 14, 2023 -
2016 (v1)Publication
Background Age-associated motor and cognitive deficits increase the risk of falls, a major cause of morbidity and mortality. Because of the significant ramifications of falls, many interventions have been proposed, but few have aimed to prevent falls via an integrated approach targeting both motor and cognitive function. We aimed to test the...
Uploaded on: April 14, 2023 -
2024 (v1)Publication
BackgroundReal-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to...
Uploaded on: October 16, 2024