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
| Name | Class |
|---|---|
| Koneksa Health | INDUSTRY |
| Michael J. Fox Foundation for Parkinson's Research | OTHER |
Not provided
Not provided
Not provided
The aim of this research program is to develop and validate a smartphone app-based digital measurement concept that:
Although multiple approaches to this problem have been proposed in addition to commercially available speech analytics platforms, there is currently no established measure which incorporates the disparate aspects of affected speech to fully characterize Parkinson's symptom progression, particularly in the prodromal phase.
The measurement concept being evaluated in the present study utilizes a custom smartphone-based speech assessment tool to extract multiple hypothesis-driven acoustic features from patient speech in a real-life environment. The resultant features will be used to train a pair of supervised machine learning models to predict clinical PD symptom severity scores, and to distinguish prodromal PD patients from both healthy matched controls and PD patients in more advanced phases of disease progression.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| PD Cohort 1 | PD patients assessed via the Hoehn & Yahr (H&Y) Scale to be in Stages 1-2 of PD (inclusive) |
| |
| PD Cohort 2 | PD patients assessed via the H&Y Scale to be in Stages 3-4 of PD (inclusive) |
| |
| Prodromal PD | Patients who meet PI-defined criteria for prodromal PD, i.e., the latent phase of disease progression during which clinical PD symptoms have yet to manifest |
| |
| Age and Sex-matched Healthy Control | Age & sex matched healthy control subjects who have not been diagnosed with PD |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Digital Speech Application | Device | A custom smartphone-based speech assessment tool to extract multiple hypothesis-driven acoustic features from patient speech in a real-life environment. |
| Measure | Description | Time Frame |
|---|---|---|
| Compliance of digital speech assessment data recorded via smartphone assessments | o % Interpretable minutes of data per patient | 8 weeks |
| Quality of digital speech assessment data recorded via smartphone assessments | o % Interpretable vs. expected number of minutes of data per patient by complete days on study | 8 weeks |
| Usability of digital speech assessments | o SUS Usability scores by score, grade and adjective rating | 8 weeks |
| Content validity of digital speech assessments | o Percent of patients that score Excellent or Good for usability ratings | 8 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Characterization and reliability of digital speech assessment features | o Candidate feature characterization: response distributions, and outlier analysis. Stratification of sustained phonation measures by MDS-UPDRS relevant speech items | 8 weeks |
| Reliability of digital speech assessment features |
Not provided
Inclusion Criteria:
PD:
Male or female age 30 years or older at Screening Visit.
Diagnosis of PD as defined by MDS PD diagnostic criteria [1]
PD severity at Screening Visit of either:
Able and willing to complete all aspects of the study, including at home smartphone app and Zoom telehealth assessments.
Able to provide informed consent.
Prodromal PD:
Confirmation that participant is eligible based on clinician determined predictive criteria of known risk of PD including
Male or female age 30 or older at Screening Visit.
Able and willing to complete all aspects of the study, including at home smartphone app and Zoom telehealth assessments
Able to provide informed consent.
Age & Sex Matched Healthy Control:
Exclusion Criteria:
PD:
Prodromal PD:
Age & Sex Matched Healthy Control:
Not provided
Not provided
Not provided
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Northwestern University | Chicago | Illinois | 60611 | United States |
Not provided
Not provided
Not provided
Not provided
Not provided
| Type | Date | Date Unknown |
|---|---|---|
| Release | Mar 30, 2026 | |
| Reset | Apr 16, 2026 |
Not provided
Not provided
| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Mar 30, 2026 | Apr 16, 2026 |
| 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
internal consistency and test-retest reliability |
| 8 weeks |
| Predictive performance of machine learning (ML) regression model | o Construct validity: convergent validity of each model output versus relevant MDS-UPDRS speech items and Parts I-IV total score, respectively; and versus Hoehn & Yahr Stage | 8 weeks |
| Predictive performance of ML classification model | o Known group validity by cohort (including by H&Y Stage/ MDS-UPDRS Parts I-IV total score) | 8 weeks |
| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |