Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
This study compares the validity and usability of smartphone software for home monitoring of symptoms and signs in Parkinson's disease as compared to the current clinical gold standard - the Unified Parkinsons Disease Rating Scale.
Parkinson's Disease (PD) is a neurodegenerative condition, which when treated can result in fluctuating motor activity - sometimes too much movement, sometimes too little.
A series of tests, run on a smartphone, will be used to evaluate the motor signs of Parkinson's and related to a clinical evaluation based on the Unified Parkinson's Disease Rating Scale. 60 participants will be recruited.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Clinical Assessment | Active Comparator | Motor assessment will be performed by a clinician using the Unified Parkinson's Disease Rating Scale. |
|
| Smartphone assessment | Experimental | CloudUPDRS smartphone software assessment will be performed. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| CloudUPDRS smartphone software assessment | Device | Smartphone software consisting of a series of tapping and tremor-measurement tests designed to measure a subset of the UPDRS. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Validity of smartphone software for home monitoring in Parkinson's disease | The primary objective is to measure the validity (bias and reliability) of the smartphone UPDRS (smartphone derived UPDRS). The primary objective outcome measure is the accuracy (and error) of the smartphone UPDRS predictions of the clinical UPDRS rating score. This will be ascertained by using multiple cross-validation runs in which the data are randomly split into 'calibration' and 'testing' cohorts. The model will be trained on the 'calibration' dataset, and the accuracy and error from the out-of-sample predictions will be summarised into a mean accuracy and error score. | 3 years |
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| Data exploration | Data from this study will be subjected to post hoc analysis to explore future hypotheses in this area. | 3years |
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Kailash Bhatia, MD | University College, London | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ashwani Jha | London | WC1N 3BG | United Kingdom |
Not provided
Not provided
Not provided
Not provided
Not provided
| Type | Date | Date Unknown |
|---|---|---|
| Release | Apr 27, 2021 | |
| Reset | May 21, 2021 |
Not provided
Not provided
| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Apr 27, 2021 | May 21, 2021 |
| ID | Term |
|---|---|
| D010300 | Parkinson Disease |
| ID | Term |
|---|---|
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Clinical assessment | Other | A clinician will assess the motor signs of the participant using the Unified Parkinson's Disease Rating Scale. The examination will be videoed and rated by 3 blinded examiners. |
|
| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |