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This is an observational study that intends to compare falls or fall-risk related alarms derived from a three-dimensional sensor system with the clinical reality definded by attending nurses.
Three dimensional sensor technology (3DS) is available for fall detection and fall prevention (e.g. unwanted getting up in persons with risks for frequent falls) in several institutions in Europe and Switzerland. 3DS are capable to analyze completely anonymized data and alert nurses towards a dangerous (fall) or potentially dangerous (getting out of bed) event during day- and nighttime. Multi-sensor technology has been applied to assess activities of daily living in persons cognitive problems living at home. To our knowledge, 3DS technology has not been examined as part of a structured clinical protocol. In addition, the combination of two digital technologies (3DS and a server based software) as an integrative platform could help to develop algorithms to analyze complex human activities such as using a toilet. Automated analyses of such complex activities have the potential to support nursing staff in the future.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Three dimensional sensor system designed for fall detection (Fearless) | Device | Detection of falls in nursing home residents and acute geriatric hospital patiients |
| Measure | Description | Time Frame |
|---|---|---|
| Falls detection rate | Number of falls detected by the system compared to falls detected by nursing staff members | Through study completion, an average of 6 months |
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| Measure | Description | Time Frame |
|---|---|---|
| Assessment of toileting | 3d sensor system data will be used to develop an algorithm for a complex activity such as using a toilet. The senors results will be compared with a Nurse led 12 step observation protocol. Parts of the activity model include: (1) enter the room, (2) go to the toilet, (3) take off clothes, (4) sit on the toilet, (5) clean oneself, (6) stand up, (7) get dressed, (8) flush the toilet, (9) go to the sink, (10) wash hands, (11) dry hands, (12) leave the room, as well as emergencies. |
Inclusion criteria Informed consent given by person or caregiver Patients admitted
Exclusion Criteria:
For Falls assessment by 3D sensors:
• Based on the multifactorial risk for falls there are no exclusion criteria for falls assessment
For the development of toileting algorithm:
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Due to the observationa design, we will have no control group. All persons admitted to the rooms equipped with this novel technology are asked to participate.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Thomas Münzer, MD | Contact | +41712438880 | thomas.muenzer@geriatrie-sg.ch |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Geriatrische Klinik | Recruiting | Sankt Gallen | Canton of St. Gallen | 9000 | Switzerland |
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| ID | Term |
|---|---|
| D000073496 | Frailty |
| D003704 | Dementia |
| D014549 | Urinary Incontinence |
| D004688 | Encopresis |
| ID | Term |
|---|---|
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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| Through study completion, an average of 6 months |
| D009422 | Nervous System Diseases |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D014555 | Urination Disorders |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
| D059411 | Lower Urinary Tract Symptoms |
| D020924 | Urological Manifestations |
| D012816 | Signs and Symptoms |
| D012817 | Signs and Symptoms, Digestive |
| D001526 | Behavioral Symptoms |
| D001519 | Behavior |
| D019960 | Elimination Disorders |