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Non CE-certified status of device
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| Name | Class |
|---|---|
| Ziekenhuis Oost Limburg (ZOL) Hospital Genk, Belgium | UNKNOWN |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Single group | Other |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Auditive cueing | Device | Based on gait measurement, auditive cueing is generated automatically to check its impact on patients with Freezing Of Gait. |
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| Measure | Description | Time Frame |
|---|---|---|
| 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 |
| Measure | Description | Time Frame |
|---|---|---|
| The sensitivity of FOG detection from the measured and classified (normal walk vs FOG) gait data compared to manually scored recorded video. | Same data collection as for outcome 1. Sensitivity is calculated from the algorithm scoring vs the manual scoring. | 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. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| An Driesen, MD, Neurologist | ZOL Genk | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ziekenhuis Oost-Limburg | Genk | Limburg | 3600 | Belgium |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31509999 | Background | 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. | |
| 24957299 | Background | 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. |
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| ID | Term |
|---|---|
| D010300 | Parkinson Disease |
| ID | Term |
|---|---|
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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Same data collection as for outcome 1. Specificity is calculated from the algorithm scoring vs the manual scoring. |
| within 1 to 3 weeks after the first hospital visit |
| 29263221 | Background | 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. |
| 26454703 | Background | 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. |
| 28653213 | Background | 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. |
| 31524181 | Background | 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. |
| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |