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Due to COVID-19 pandemic and new regulatory requirements
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Within this study we conduct long-term measurements on Parkinson patients using a three sensor IMU setup: one sensor is located at the wrist, one sensor at the belt/ in the pocket and one sensor is worn as a pendant. Before and after each long-term measurement phase (5 days within 6-8 weeks) we perform an UPDRS to identify changes in everyday life behaviour that correlate with UPDRS trends (especially part 3).
The aim of the study is to collect a database for the development of algorithms for the classification of everyday movement patterns of PD patients with the underlying sensor concepts. From the recorded movement data of PD patients and healthy volunteers (reference basis), characteristic features will be derived which could allow a distinction between pathological and unobtrusive non-disturbed movement patterns (e.g. on/off-state classification) and an assessment of the fall potential.
Study Timeline
The present study will be carried out in three, partly successive stages. The first two stages are measurements with the presented system during a medical examination (or afterwards) under annotation of certain motor exercises to determine the state of health of the patient or test person. In order to generate a sufficient reference database of comparable movement patterns, a series of measurements with subjects of a similar average age is carried out in parallel with the same sensor configuration and the same motor exercises. The third part of the study includes measurements in the home environment of Parkinson's patients. These measurements are used to identify the previously annotated movement patterns in the everyday life of the patient of the same previously included patient group. The individual stages of the study comprise in detail:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with Morbus Parkinson | Other |
| |
| Healthy Subjects | Other |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Body Sensor Network | Device | The "Integrated Posture and Activity NEtwork by Medit Aachen (IPANEMA)" Body Sensor Network (BSN) is a wireless sensor network with several sensor nodes. A sensor node consists of a base unit equipped with different sensor modalities: Acceleration sensor, Rotation rate sensor, Air pressure sensor, Photoplethysmography (PPG, optional), Galvanic Skin Response (GSR, optional) measurement. The sensor data is transmitted via a wireless 433/868 MHz ISM band radio link to the central radio node. From there, the data is transferred via a Bluetooth connection to a laptop or PC for processing. Three sensors are attached 1) to the wrist with a flexible Velcro strap, 2) hung around the neck on a specially designed collar and 3) worn loosely in the trouser pocket without further fixation or at the belt. The respective sensors are located in a closed, ergonomically shaped housing (size 70x40x20mm^3, approx. 35g) and have no electrically conductive contact to the skin surface of the test person. |
| Measure | Description | Time Frame |
|---|---|---|
| Disease Assessment with Wearable Movement Sensors | The Unified Parkinson's Disease Rating Scale (UPDRS) will be conducted in two consecutive clinical visits (6-12 weeks) or during an inpatient stay (5 days+). In between we conduct 5 days of long-term monitoring for each patient using a wearable movement sensor system. Outcome measures of the system (overall activity, stride time, stride variability, gait symmetry, symptom appearance, etc.) will be correlated with the UPDRS trend. | 5 days -12 weeks |
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Inclusion Criteria Patients:
Inclusion Criteria Healthy Volunteers:
Exclusion Criteria (general):
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| Name | Affiliation | Role |
|---|---|---|
| Kathrin Reetz, Prof. Dr. | Departmet of Neurology, University Clinic Aachen, Germany | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Department of Neurology, University Hospital Aachen | Aachen | North Rhine-Westphalia | 52074 | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 17667192 | Background | Dennison AC, Noorigian JV, Robinson KM, Fisman DN, Cianci HJ, Moberg P, Bunting-Perry L, Martine R, Duda J, Stern MB. Falling in Parkinson disease: identifying and prioritizing risk factors in recurrent fallers. Am J Phys Med Rehabil. 2007 Aug;86(8):621-32. doi: 10.1097/PHM.0b013e311611583. | |
| 17588236 | Background |
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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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| Pickering RM, Grimbergen YA, Rigney U, Ashburn A, Mazibrada G, Wood B, Gray P, Kerr G, Bloem BR. A meta-analysis of six prospective studies of falling in Parkinson's disease. Mov Disord. 2007 Oct 15;22(13):1892-900. doi: 10.1002/mds.21598. |
| 12023412 | Background | Wood BH, Bilclough JA, Bowron A, Walker RW. Incidence and prediction of falls in Parkinson's disease: a prospective multidisciplinary study. J Neurol Neurosurg Psychiatry. 2002 Jun;72(6):721-5. doi: 10.1136/jnnp.72.6.721. |
| 14999493 | Background | Stolze H, Klebe S, Zechlin C, Baecker C, Friege L, Deuschl G. Falls in frequent neurological diseases--prevalence, risk factors and aetiology. J Neurol. 2004 Jan;251(1):79-84. doi: 10.1007/s00415-004-0276-8. |
| 2720700 | Background | Koller WC, Glatt S, Vetere-Overfield B, Hassanein R. Falls and Parkinson's disease. Clin Neuropharmacol. 1989 Apr;12(2):98-105. doi: 10.1097/00002826-198904000-00003. |
| 10994536 | Background | Gray P, Hildebrand K. Fall risk factors in Parkinson's disease. J Neurosci Nurs. 2000 Aug;32(4):222-8. doi: 10.1097/01376517-200008000-00006. |
| 11757958 | Background | Bloem BR, Grimbergen YA, Cramer M, Willemsen M, Zwinderman AH. Prospective assessment of falls in Parkinson's disease. J Neurol. 2001 Nov;248(11):950-8. doi: 10.1007/s004150170047. |
| 23450694 | Background | Paul SS, Canning CG, Sherrington C, Lord SR, Close JC, Fung VS. Three simple clinical tests to accurately predict falls in people with Parkinson's disease. Mov Disord. 2013 May;28(5):655-62. doi: 10.1002/mds.25404. Epub 2013 Feb 28. |
| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |