Using Wearable and Mobile Data to Diagnose and Monitor Movement Disorders

Summary

Participation Requirements

Description

Movement disorders are a group of neurological conditions that alter human movements. They lead to functional impairments, diminished quality of life, and significant societal, economic, and familial burden. Due to the increase in population and longer life expectancy [1], more and more people will ...

Movement disorders are a group of neurological conditions that alter human movements. They lead to functional impairments, diminished quality of life, and significant societal, economic, and familial burden. Due to the increase in population and longer life expectancy [1], more and more people will have to live with movement disorders. However, access to movement disorder specialists is already limited and will get worse [2]. Therefore, there is an urgent need to develop tools to aid non-specialist medical professionals identify and manage the symptoms (both motor and non-motor) of those disorders such that specialist can focus on more severe and complex cases. While there are several conditions that can be classified as movement disorders, the current proposal will focus on six disorders that have overlapping symptoms and could prove difficult to differentiate for non-specialists and/or clinicians that do not readily have access to genetic testing or imaging facilities: Essential tremor (ET), Parkinson's disease (PD), Huntington's disease (HD), primary focal dystonia (PFD), spinocerebellar ataxia (SCA), and functional movement disorders (FMD). While trained movement disorder specialists may correctly identify each of these disorders and provide optimal treatment, general practitioners and clinicians living in rural areas that do not have access to the most up-to-date diagnostic tools, such as neuroimaging and genetic testing, may face difficulty when treating those patients due to symptom variability and overlap in symptom presentation between different disorders; leading to sub-optimal treatment outcomes. As such, the development of simple, accurate, and inexpensive tools to help guide their clinical decisions is warranted. The ubiquity of mobile technology and wearable sensors may enable the development of such a tool. In recent years, our group and others have used mobile phones and wearable technology to assess symptoms in a multitude of disorders. This highlights the feasibility of our proposed system for the assessment and monitoring of symptom severity in individuals with movement disorders.

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