Developing digital tools for diagnosing Parkinson's disease
Development of Digital Diagnostic Devices for Parkinson's Disease
machineMD AG · NCT06663826
This study is trying to develop new digital tools that use eye and movement data to help doctors diagnose and monitor Parkinson's disease more accurately.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 100 (estimated) |
| Sex | All |
| Sponsor | machineMD AG (industry) |
| Locations | 1 site (Zurich, Canton of Zurich) |
| Trial ID | NCT06663826 on ClinicalTrials.gov |
What this trial studies
This project aims to collect ocular motor, pupil, and gait data from individuals with Parkinson's disease to create machine learning models for improved diagnosis and monitoring. By utilizing advanced sensor technology and machine learning, the study seeks to enhance the accuracy and timeliness of Parkinson's disease diagnoses, moving beyond traditional subjective assessments. Participants will undergo standard clinical examinations alongside objective measurements using approved medical devices and consumer technology for continuous monitoring. The goal is to provide a more reliable and detailed understanding of the disease's progression.
Who should consider this trial
Good fit: Ideal candidates include individuals diagnosed with Parkinson's disease or atypical parkinsonian syndromes who can self-report their symptoms and meet specific ocular and mobility criteria.
Not a fit: Patients with other neurological diseases or those unable to comply with the examination requirements may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to earlier and more accurate diagnoses of Parkinson's disease, improving patient management and outcomes.
How similar studies have performed: While there have been advancements in digital diagnostics for various conditions, this specific approach integrating machine learning with ocular and gait data for Parkinson's disease is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Diagnosis of Parkinson's disease or of another parkinsonian syndrome (atypical Parkinson's) * Refractive error between -6 and +4 diopters, on both eyes * Informed consent by participant documented per signature * Able to self-report history of daily gait freezing and/or festination * Able to walk unsupported or using an aid for at least 5 minutes and if over 69 used to carrying out this level of exercise Exclusion Criteria: * Other known neurological diseases * Current medication/drugs that could potentially influence performance in ocular motor tasks and/or compliance in the judgement of the investigator (e.g. benzodiazepines, alcohol, stimulants, or recreational drugs) - except Parkinson's medications * Incapacity to understand and comply with the examination (e.g. due to advanced cognitive decline, failure to comply with easy experimental instructions and tasks) * Any injury or disorder that may affect eye movement measurements or balance (other than Parkinson's or referring primary condition) * Any skin conditions or broken skin in the calf and behind the knee area * Lack of access or limited connectivity to WiFi in home setting
Where this trial is running
Zurich, Canton of Zurich
- University Hospital of Zurich — Zurich, Canton of Zurich, Switzerland (RECRUITING)
Study contacts
- Principal investigator: Konrad Weber, Prof. Dr. med. — University of Zurich
- Study coordinator: Ana Coito, Ph.D.
- Email: ana.coito@machinemd.com
- Phone: +41 (0)31 589 67 92
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Parkinson Disease, Parkinson', s disease, oculomotor, ocular motor, gait, eye movements, pupil