NCT04274478

Brief Summary

The first goal of the study is to investigate whether an algorithm can reliably detect Freezing of Gait (FOG) in Parkinson patients based on participant gait data generated by a pressure insole. The second goal is to investigate whether Auditive Cueing (AC) based on such a detection reduces the frequency and length of FOG episodes in those participants. The study will be conducted per Good Clinical Practice principles.

Trial Health

57
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
13

participants targeted

Target at below P25 for not_applicable parkinson-disease

Timeline
Completed

Started Jun 2019

Geographic Reach
1 country

1 active site

Status
terminated

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

June 6, 2019

Completed
8 months until next milestone

First Submitted

Initial submission to the registry

February 2, 2020

Completed
16 days until next milestone

First Posted

Study publicly available on registry

February 18, 2020

Completed
1.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 11, 2021

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 11, 2021

Completed
Last Updated

February 13, 2025

Status Verified

April 1, 2021

Enrollment Period

1.8 years

First QC Date

February 2, 2020

Last Update Submit

February 12, 2025

Conditions

Parkinson Disease

Outcome Measures

Primary Outcomes (3)

  • The F1-score of FOG detection from the measured and classified (normal walk vs FOG) gait data compared to manually scored recorded video.

    The participants perform 4 walks without AC on standardized tracks while being video-recorded. During the walks, gait data is recorded and then scored (for each time point) by the algorithm into normal walk or FOG. The video recording is scored manually according to the criteria as described in reference Gilat. M. and represents the true state of walking. The F1-score is calculated from the algorithm scoring vs the manual scoring: a True Positive is true freezing which is classified by the algorithm as freezing. A True Negative is a true normal walk which is classified as a normal walk. Similarly, a False Positive is a true normal walk which is classified as FOG and a False Negative is a true FOG which is classified as a normal walk. The same 4 walks are performed both in OFF and in ON. OFF measurement is only performed when the PI has given permission to do so. ON measurement is performed 1 hour after taking their standard medication.

    8 walks are performed in 1 hospital visit within 4 weeks of enrollment. Total assessment time estimate is 2x 30 minutes.

  • The change in the number of FOG-episodes with and without AC

    The participants again perform 4 walks in OFF and in ON but now with AC. The average number of freezing episodes is calculated for each participant in OFF and in ON with and without AC. The change between the average without AC and the average with AC is calculated as well as its level of significance. These changes are computed for each walk, for each individual participant across all walks and across all participants.

    1 week after the first hospital visit (for Outcome 1).

  • The change in the total duration of FOG-episodes with and without AC

    The participants again perform 4 walks in OFF and in ON but now with AC. The average duration of freezing episodes is calculated in the same way as their number per Outcome 2.

    within 1 to 3 weeks after the first hospital visit

Secondary Outcomes (2)

  • The sensitivity of FOG detection from the measured and classified (normal walk vs FOG) gait data compared to manually scored recorded video.

    Within 4 weeks of enrollment

  • The specificity of FOG detection from the measured and classified (normal walk vs FOG) gait data compared to manually scored recorded video.

    within 1 to 3 weeks after the first hospital visit

Study Arms (1)

Single group

OTHER
Device: Auditive cueing

Interventions

Auditive cueingDEVICE

Based on gait measurement, auditive cueing is generated automatically to check its impact on patients with Freezing Of Gait.

Single group

Eligibility Criteria

Age18 Years - 100 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • must have more than 1 FOG episode/day
  • must be patient in Ziekenhuis Oost Limburg (ZOL)

You may not qualify if:

  • not able to speak Dutch
  • cannot give informed consent (mental health)

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Ziekenhuis Oost-Limburg

Genk, Limburg, 3600, Belgium

Location

Related Publications (6)

  • Naghavi N, Miller A, Wade E. Towards Real-Time Prediction of Freezing of Gait in Patients With Parkinson's Disease: Addressing the Class Imbalance Problem. Sensors (Basel). 2019 Sep 10;19(18):3898. doi: 10.3390/s19183898.

    PMID: 31509999BACKGROUND

  • Nonnekes J, Janssen AM, Mensink SH, Oude Nijhuis LB, Bloem BR, Snijders AH. Short rapid steps to provoke freezing of gait in Parkinson's disease. J Neurol. 2014 Sep;261(9):1763-7. doi: 10.1007/s00415-014-7422-8. Epub 2014 Jun 24.

    PMID: 24957299BACKGROUND

  • Barthel C, Nonnekes J, van Helvert M, Haan R, Janssen A, Delval A, Weerdesteyn V, Debu B, van Wezel R, Bloem BR, Ferraye MU. The laser shoes: A new ambulatory device to alleviate freezing of gait in Parkinson disease. Neurology. 2018 Jan 9;90(2):e164-e171. doi: 10.1212/WNL.0000000000004795. Epub 2017 Dec 20.

    PMID: 29263221BACKGROUND

  • Zach H, Janssen AM, Snijders AH, Delval A, Ferraye MU, Auff E, Weerdesteyn V, Bloem BR, Nonnekes J. Identifying freezing of gait in Parkinson's disease during freezing provoking tasks using waist-mounted accelerometry. Parkinsonism Relat Disord. 2015 Nov;21(11):1362-6. doi: 10.1016/j.parkreldis.2015.09.051. Epub 2015 Oct 1.

    PMID: 26454703BACKGROUND

  • Ginis P, Heremans E, Ferrari A, Bekkers EMJ, Canning CG, Nieuwboer A. External input for gait in people with Parkinson's disease with and without freezing of gait: One size does not fit all. J Neurol. 2017 Jul;264(7):1488-1496. doi: 10.1007/s00415-017-8552-6. Epub 2017 Jun 26.

    PMID: 28653213BACKGROUND

  • Gilat M. How to Annotate Freezing of Gait from Video: A Standardized Method Using Open-Source Software. J Parkinsons Dis. 2019;9(4):821-824. doi: 10.3233/JPD-191700.

    PMID: 31524181BACKGROUND

MeSH Terms

Conditions

Parkinson Disease

Condition Hierarchy (Ancestors)

Parkinsonian DisordersBasal Ganglia DiseasesBrain DiseasesCentral Nervous System DiseasesNervous System DiseasesMovement DisordersSynucleinopathiesNeurodegenerative Diseases

Study Officials

  • An Driesen, MD, Neurologist

    ZOL Genk

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
SUPPORTIVE CARE
Intervention Model
SINGLE GROUP
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

February 2, 2020

First Posted

February 18, 2020

Study Start

June 6, 2019

Primary Completion

April 11, 2021

Study Completion

April 11, 2021

Last Updated

February 13, 2025

Record last verified: 2021-04

Data Sharing

IPD Sharing
Will not share

Locations

BE(1)