Using Consumer-grade Wearable Devices for Fall Risk Evaluation and Alerts
- Conditions
- Mass Screening
- Interventions
- Behavioral: risk of fall
- Registration Number
- NCT06508892
- Lead Sponsor
- University of Michigan
- Brief Summary
Creation and use of a smartphone application for older adults to assess the participants' risk of fall. Phase 1: Compare the accuracy and validity of accelerometer and gyroscopic data from a smartphone and gold-standard, wearable sensors gathered during balance and gait activities. Phase 2: Develop a model that integrates wearable sensor data and individual characteristics, such as age, medical conditions, exercises, previous falls, fear of falls, along with gait and balance outcome measurements, to evaluate fall risk in older adults. Phase 3: Integrate the computational model in the design of a mobile app for wearable devices for older adults to self-administer fall risk assessments and provide individualized risk of fall information.
- Detailed Description
Falls are prevalent among older adults and can cause serious problems. Falls in older adults can cause serious injuries that negatively impact their quality of life and can be life-threatening. Evaluating an individual's risk of fall is, typically, an important first step in preventing falls. Fall risk is commonly evaluated through clinical measurement scales, such as the Tinetti Performance Oriented Mobility Assessment (POMA) and Berg Balance Scale (BBS). Physical measurements using instruments, such as inertial measurement units (IMUs; accelerometers and gyroscopes) and force plates, can also be employed to evaluate an individual's fall risk. However, both clinical and instrumented measures are often only collected in clinical or research settings, thus making them less accessible to older adults and their care providers. Additionally, fall risk can only be evaluated infrequently, which can be a problem as health and environmental changes in the life of an older adult can necessitate more frequent measurement of fall risk. The research team proposes consumer-grade wearable devices (e.g. smartphones and watches) to fill the gap in current fall risk assessment. This approach has great potential as quick, simple, timely, and frequent measures of fall risk can help to reduce fall risk in older adults. The proposed research investigates older adults' gait and balance to identify potential links between wearable sensor measurements and fall risk. The types and granularity of data on physical activities that can be collected by consumer-grade wearable devices are more limited than using research-grade measurement. The investigators plan to use research-grade sensors to validate measures of gait and balance via consumer-grade wearable devices. Signal processing algorithms will be employed to extract the critical patterns from wearable device measurements that could be used for regular fall risk monitoring. A machine-learning computational model will also be developed to correlate the wearable data to clinical scales. This data will be used to design and build a mobile app for older adults to self-administer the fall risk test at home. The application design will be informed by factors such as one's physical environment, health condition, fear of falls, etc. and the goal is to develop an integrated system that offers fall risk assessment and provides alerts for older adults.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 100
- 65 years or older
- have had a fall in the six months
- have been diagnosed with neurological conditions such as multiple sclerosis, Parkinson's disease, traumatic brain injury, Alzheimer's disease, or have had a stroke in the last year
- have orthopedic or cardiopulmonary conditions and/or surgeries in the past year
- have physical limitations that would make it difficult or uncomfortable for individuals to perform the experimental tasks.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Comparison of acceleration and 3D rotation during balance and movement risk of fall Can consumer-grade sensors used in mobile phones provide an accurate and valid measure of balance and gait when compared to gold standard research-grade sensors? A computational model for risk of fall will be developed.
- Primary Outcome Measures
Name Time Method 3D rotation 60 seconds to 6 minutes Vertical, medial-lateral, and anterior-posterior rotation
3D acceleration 60 seconds to 6 minutes Vertical, medial-lateral, and anterior-posterior acceleration
- Secondary Outcome Measures
Name Time Method Timed Up and Go (TUG) 5 minutes Assess mobility, balance, walking ability and risk of fall. Less than or equal to 10 seconds: normal; 11-30 seconds: good mobility, can go outside alone, mobile without a gait assistive device; greater than 30 seconds: problems, cannot go outside alone, requires a gait assistive device.
Montreal Cognitive Assessment (MoCA) 15 minutes Detect cognitive involvement, Scores greater than 26 indicates normal cognition; scores less than 26 indicate cognitive impairment. Therefore, lower scores are a worse outcome. 18-25: Mild cognitive impairment; 10-17: Moderate cognitive impairment; Less than 10: Severe cognitive impairment.
Berg Balance Scale (BBS) 15 minutes Assess static and dynamic balance and risk of fall. 14 item scale. Lower scores indicate poorer balance and higher scores indicate better balance. Score of less than 45 out of 56 indicates that the individual may be at a greater risk of fall. Out of 56, 41-56 Independent, 21-40 walking with assistance, 0-20 wheelchair bound.
Five Times Sit to Stand (5XSTS) 5 minutes Assess functional lower extremity strength. The time it takes to complete the 5XSTS task is recorded. For community-dwelling older adults, the cut-off score is greater than or equal to 15 seconds which indicates risk of fall. Greater than or equal to 12 seconds identifies the need for further assessment for falls. Therefore, the greater the number of seconds, the greater the risk of fall.
Activities-Specific Balance Confidence (ABC) Scale 10 minutes Self-report measure of perceived balance confidence. 16 items are rated on a 0% to 100% whole number rating scale. Scores of zero represent no confidence; scores of 100 indicate complete confidence.
Total the ratings (possible range = 0-1600) and divide by 16 (number of items) to get the patient's ABC score or overall percent of balance confidence. For older adults, scores less than 67% indicate risk for falling and accurately classify people who fall 84% of the time. Greater than 80% indicates a high level of physical functioning, 50-80% indicates moderate level of physical functioning, and less than 50% indicates low level of physical functioning.6 Minute Walk Test (6MWT) 6 minutes Assess distance walked over a duration of 6 minutes, submaximal test for endurance. For community-dwelling older adults: 60-69 years old: 572 (male) and 538 (female) meters; 70-79 years old: 527 (male) and 471 (female) meters, and 80-90 years old: 417 (male) and 392 (female) meters. Therefore, the less distance walked in 6 minutes indicates that the individual has less submaximal aerobic and functional walking capacity.
Trial Locations
- Locations (1)
University of Michigan-Flint
🇺🇸Flint, Michigan, United States