- ICH GCP
- US-Register für klinische Studien
- Klinische Studie NCT07580612
AID-FOG: Artificial Intelligence-Driven Freezing of Gait Detection in the Home (AID-FOG)
Artificial Intelligence-Driven Freezing Of Gait Detection in the Home: Investigating How Free-living Activities Affect the Algorithm
Studienübersicht
Status
Studientyp
Einschreibung (Geschätzt)
Kontakte und Standorte
Studienorte
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Leuven, Belgien, 3001
- Rekrutierung
- Department of Rehabilitation Sciences
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Kontakt:
- Moran Gilat
- Telefonnummer: +3216 32 94 27
- E-Mail: moran.gilat@kuleuven.be
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Kontakt:
- Margot Genbrugge
- Telefonnummer: +3216 19 44 94
- E-Mail: margot.genbrugge@kuleuven.be
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Hauptermittler:
- Moran Gilat
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Hamburg, Deutschland, 20457
- Noch keine Rekrutierung
- Sports Science and Neurorehabilitation
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Kontakt:
- Christian Schlenstedt
- Telefonnummer: +4940.361 226 43206
- E-Mail: christian.schlenstedt@medicalschool-hamburg.de
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Tel Aviv, Israel, 64
- Noch keine Rekrutierung
- Center for the study of movement, cognition and mobility
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Kontakt:
- Jeffrey M Hausdorff
- Telefonnummer: +972-3-6973081
- E-Mail: jhausdor@tlvmx.gov.il
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Teilnahmekriterien
Zulassungskriterien
Studienberechtigtes Alter
- Erwachsene
- Älterer Erwachsener
Akzeptiert gesunde Freiwillige
Probenahmeverfahren
Studienpopulation
Beschreibung
Inclusion Criteria:
For all participants
- Voluntary written informed consent of the participant has been obtained prior to any study-related procedures, except the non-recorded pre-screening questions;
- At least 18 years of age at the time of signing the Informed Consent Form (ICF);
- Person is cognitively able to follow and understand instructions and provide voluntary written informed consent;
- Person is able to walk for short distances (± 10 meters) independently, with- or without use of a walking aid;
- Person does not live in a temporary or permanent care facility.
For participants with PD:
- Clinical diagnosis of Parkinson's disease (PD) made by a neurologist according to the Movement Disorders Society guidelines;
- Person self-reports to experience daily FOG (for recruitment of freezers only);
- Person is willing to temporarily delay the morning anti-Parkinsonian medication during the standardized assessment visit.
Exclusion criteria:
- Occurrence of any of the following within 3 months prior to informed consent: myocardial infarction, hospitalization for unstable angina, stroke, coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), implantation of a cardiac resynchronization therapy device (CRTD), active treatment for cancer or other malignant disease, uncontrolled congestive heart disease (NYHA class >3), acute psychosis or major psychiatric disorders or continued substance abuse, other neurological (than PD) or orthopaedic impairment that significantly impacts on gait;
- Participant self-reports daily falls;
- Participation in another interventional study, with or without an investigational medicinal product (IMP) or device (IMD)
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
Kohorten und Interventionen
Gruppe / Kohorte |
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Gesunde Kontrollen
Gesunde ältere Erwachsene
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Freezers
Patients with Parkinson's disease who self-report to experience Freezing of Gait daily.
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Non-freezers
Patients with Parkinson's disease who do not experience Freezing of Gait.
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Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Comparing the agreement between AID-FOG and gold-standard expert annotation to detect the percentage of time spent with freezing of gait (FOG) in relation to total time duration (%TF).
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The primary outcome (percentage of time spent with FOG in relation to total task duration = %TF) will be established by manual annotations of video footage by an experienced assessor (=gold-standard reference) and by the automated AID-FOG algorithm v1.0 applied post-hoc (i.e.
offline) to IMU data collected during the same walking tasks.
This will be calculated for standardized walking tasks on which the AID-FOG algorithm has been trained, standardized walking tasks on which the AID-FOG algorithm was not trained, and a free-living walking condition on which the AID-FOG algorithm was not trained.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
Sekundäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
F1-score
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
Same as primary outcome, but now for the F1-score (rather than percent TF).
F1 scores range between 0 and 1, the higher the score the better.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
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Number of FOG episodes
Zeitfenster: T0: free-living gait (5 hours), T1: free-living gait (5 hours) and T2: standardized gait (4 hours)
|
Same as primary outcome, but now for the absolute number of FOG episodes.
|
T0: free-living gait (5 hours), T1: free-living gait (5 hours) and T2: standardized gait (4 hours)
|
|
The performance of the AID-FOG algorithm to differentiate between the FOG manifestations.
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
Freezing of gait (FOG) manifests in multiple forms, including akinetic and kinetic subtypes, which may be associated with trembling or occur without it.
This study investigates the performance of AID-FOG in discriminating between these manifestations, using expert annotations as the reference standard.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
Comparing performance of AID-FOG to detect freezing in OFF and ON medication states.
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The FOG outcomes as obtained by the human expert and the offline AID-FOG algorithm v1.0 will be calculated for both the OFF and ON medication states.
These scores will be compared to evaluate the change in algorithm performance depending on medication status.
The FOG outcomes will be the percentage TF which ranges between 0-100 percent.
The higher the percentage the more freezing the patient has.
But also the F1-score which ranges between 0-1.
The higher the score the more overlap there is between the expert and the algorithm.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
Consistency of FOG detection with AID-FOG compared between two free-living assessments
Zeitfenster: T0= test day 1: free-living gait (5 hours) and T1= test day 2: free-living gait (5 hours)
|
The agreement in FOG detection (%TF, F1-score) between the AID-FOG algorithm and the gold-standard human annotations will be compared between the two free-living test days.
|
T0= test day 1: free-living gait (5 hours) and T1= test day 2: free-living gait (5 hours)
|
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The number of false detections of FOG episodes during free-living
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The absolute sum of false detections made by the algorithm.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
Comparing AID-FOG with subjective FOG
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The FOG outcomes obtained with AID-FOG will be correlated to the total score of the New Freezing of Gait Questionnaire (NFOGQ) and Patient Reported Outcomes of FOG (PRO).
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
Performance of automated FOG detection during free-living mobility
Zeitfenster: 1 week of free-living mobility with IMU
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The FOG outcomes obtained with AID-FOG offline will be calculated from multiple days of free-living mobility IMU data.
These outcomes will be correlated to FOG severity as determined during the observed walking tasks of the project and self-reported FOG severity.
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1 week of free-living mobility with IMU
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Andere Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
AID-FOG version 2.0 (percentage TF)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0. This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach. Percentage of time spent with FOG in relation to total task duration (= %TF) will be established by manual annotations of video footage by an experienced assessor (=gold-standard reference) and by the automated AID-FOG algorithm v2.0 applied post-hoc (i.e. offline) to IMU data collected during the same walking tasks. This will be calculated for standardized walking tasks on which the AID-FOG algorithm has been trained, standardized walking tasks on which the AID-FOG algorithm was not trained, and a free-living walking condition on which the AID-FOG algorithm was not trained. |
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (F1-score)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
Same as percentage TF, but now for the F1-score (rather than percent TF).
F1 scores range between 0 and 1, the higher the score the better.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (Number of FOG episodes)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
Same as percentage TF, but now for the absolute number of FOG episodes.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (FOG manifestations)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
The performance of the AID-FOG algorithm v2.0 to discriminate between the FOG manifestations.
Freezing of gait (FOG) manifests in multiple forms, including akinetic and kinetic subtypes, which may be associated with trembling or occur without it.
This study investigates the performance of AID-FOG in discriminating between these manifestations, using expert annotations as the reference standard.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (OFF/ON medication)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
Comparing performance of AID-FOG v2.0 to detect freezing in OFF and ON medication states.
The FOG outcomes as obtained by the human expert and the offline AID-FOG algorithm v2.0 will be calculated for both the OFF and ON medication states.
These scores will be compared to evaluate the change in algorithm performance depending on medication status.
The FOG outcomes will be the percentage TF which ranges between 0-100 percent.
The higher the percentage the more freezing the patient has.
But also the F1-score which ranges between 0-1.
The higher the score the more overlap there is between the expert and the algorithm.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (consistency of detection during two free-living assessments)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
Consistency of FOG detection with AID-FOG v2.0 compared between two free-living assessments.
The agreement in FOG detection (%TF, F1-score) between the AID-FOG algorithm v2.0 and the gold-standard human annotations will be compared between the two free-living test days.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (number of false positives)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
The number of false detections (AID-FOG v2.0) of FOG episodes during free-living
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG version 2.0 (subjective FOG)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The data obtained in the study will be used to train the AID-FOG algorithm v1.0.
This trained AID-FOG algorithm v2.0 will be evaluated using the same listed outcome measures, using a leave-one-subject-out approach.
Comparing AID-FOG v2.0 with subjective FOG.
The FOG outcomes obtained with AID-FOG v2.0 will be correlated to the total score of the New Freezing of Gait Questionnaire (NFOGQ) and Patient Reported Outcomes of FOG (PRO).
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (percentage TF)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
Percentage of time spent with FOG in relation to total task duration (= %TF) will be established by manual annotations of video footage by an experienced assessor (=gold-standard reference) and by the automated AID-FOG online to IMU data collected during the same walking tasks.
This will be calculated for standardized walking tasks on which the AID-FOG algorithm has been trained, standardized walking tasks on which the AID-FOG algorithm was not trained, and a free-living walking condition on which the AID-FOG algorithm was not trained.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (F1-score)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
Same as percentage TF, but now for the F1-score (rather than percent TF).
F1 scores range between 0 and 1, the higher the score the better.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (number of FOG episodes)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
Same as percentage TF, but now for the absolute number of FOG episodes.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (FOG manifestations)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
The performance of the AID-FOG online algorithm to discriminate between the FOG manifestations.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (OFF/ON medication)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
The FOG outcomes as obtained by the human expert and the offline AID-FOG online algorithm will be calculated for both the OFF and ON medication states.
These scores will be compared to evaluate the change in algorithm performance depending on medication status.
The FOG outcomes will be the percentage TF which ranges between 0-100 percent.
The higher the percentage the more freezing the patient has.
But also the F1-score which ranges between 0-1.
The higher the score the more overlap there is between the expert and the algorithm.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (agreement of the detection between two free-living test days)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
The agreement in FOG detection (%TF, F1-score) between the AID-FOG online algorithm and the gold-standard human annotations will be compared between the two free-living test days.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (number false positives)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
The absolute sum of false detections made by the online algorithm.
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
|
AID-FOG online (subjective FOG)
Zeitfenster: T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
The AID-FOG algorithm will be modified for real-time FOG detection.
Performance of this AID-FOG online algorithm will be compared with AID-FOG offline versions, using the same listed outcomes.
Comparing AID-FOG online with subjective FOG.
The FOG outcomes obtained with AID-FOG online will be correlated to the total score of the New Freezing of Gait Questionnaire (NFOGQ) and Patient Reported Outcomes of FOG (PRO).
|
T0=test day 1: free-living gait assessment (5 hours), T1=test day 2: free-living gait (5 hours) and T2= test day 3: standardized gait (4 hours)
|
Mitarbeiter und Ermittler
Publikationen und hilfreiche Links
Allgemeine Veröffentlichungen
- Yang PK, Filtjens B, Ginis P, Goris M, Nieuwboer A, Gilat M, Slaets P, Vanrumste B. Freezing of gait assessment with inertial measurement units and deep learning: effect of tasks, medication states, and stops. J Neuroeng Rehabil. 2024 Feb 13;21(1):24. doi: 10.1186/s12984-024-01320-1.
- Yang PK, Filtjens B, Ginis P, Goris M, Nieuwboer A, Gilat M, Slaets P, Vanrumste B. Automatic Detection and Assessment of Freezing of Gait Manifestations. IEEE Trans Neural Syst Rehabil Eng. 2024;32:2699-2708. doi: 10.1109/TNSRE.2024.3431208. Epub 2024 Jul 31.
Nützliche Links
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn (Tatsächlich)
Primärer Abschluss (Geschätzt)
Studienabschluss (Geschätzt)
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Tatsächlich)
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Zusätzliche relevante MeSH-Bedingungen
Andere Studien-ID-Nummern
- S70220
- MJFF-024628 (Andere Zuschuss-/Finanzierungsnummer: Micheal J. Fox)
Plan für individuelle Teilnehmerdaten (IPD)
Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?
Beschreibung des IPD-Plans
Arzneimittel- und Geräteinformationen, Studienunterlagen
Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt
Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt
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