Accidental Falls, Gait, Unsteady
Conditions
Brief summary
In this observational study, a motion monitoring system including body-worn sensors, communication portals, data capture system, and algorithms will be tested with geriatric patients in Garrison Geriatric Education and Care Center (Lubbock, TX). The study is part of a long-term effort to improve the quality of life and safety of geriatric patients by using autonomous systems that can alert care givers of mobility issues and falls.
Detailed description
Medical monitoring systems have become an important area of research and development due to the possibility of allowing improved quality of life and care while reducing overall medical costs. Significance of the study: The study is significant because it will allow researchers to understand the efficacy of the autonomous sensor system used with actual residents of a geriatric care center. This study is one of the first attempts to monitor movements of geriatric residents as they go about their activities of daily living. This type of system has the potential to improve the quality of life and safety of geriatric patients. Goals: The development of autonomous patient monitoring technologies that will eventually improve the quality of life and safety of patients in geriatric care facilities and other environments. Determine the performance and usability of the wearable sensor system in a geriatric care facility with actual residents going about their daily lives. Specific Aims: 1. Determine performance of motion data collect ion system for monitoring geriatric residents as they go about their daily life in a geriatric center 2. Determine tolerability of wearing sensors by geriatric residents 3. Understand how medical staff interacts with monitored residents and the sensor devices 4. Determine if the sensor system's algorithms can identify falls Objectives: 1. Analyze the motion data generated by the system to determine system performance. The list of performance metrics will include: (a) system up-time, (b) continuity of data collection (c) sensor device failure rate, (d) sensor device battery life (e) simultaneous collection of data when multiple monitored residents are in the same localized area. 2. Assess the tolerability of wearing the devices over the course of a day using a survey administered to residents. 3. Assess the usability of the sensor system using a survey administered to care givers. 4. Compare events flagged as falls by system algorithms with the fall log produced by Garrison staff, cross-verified against personal fall logs, to determine the ability of the system to detect falls.
Interventions
DEVICESmart Slipper
The shoe measures foot pressure and motion allowing gait to be quantified.
DEVICEBelt-Clip Sensor
The sensor measures acceleration of the body allowing falls to be detected.
Sponsors
Texas Tech University
Texas Tech University Health Sciences Center
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
45 Years to 85 Years
Healthy volunteers
Yes
Inclusion criteria
1. At least 30 day resident of Garrison. 2. Deemed mentally competent by primary care provider to make decisions regarding their daily shoe wear. 3. A resident prone to falls is eligible. 4. Willing to wear shoes and offer high level of compliance to study 5. Able to provide informed consent 6. Able to complete survey 7. Age range: 45-85 yrs
Exclusion criteria
1\. Unwilling to participate 2. Not mentally competent to provide informed consent \-
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Detection of Fall Incidences | 6 months | Participants will be monitored for falls. The detection of fall events as determined by the sensors will be compared to the fall log kept by Garrison Geriatric Center. |
Countries
United States
Outcome results
None listed