Clinical trial NCT05076565: Wearable Airbag Technology to Mitigate Falls in Individuals With High Fall Risk
Official title: Wearable Airbag Technology to Mitigate Falls in Individuals With High Fall Risk
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Stroke
Parkinson Disease
Lower Limb Amputation Knee
Fall Injury
Fall Patients
Falling
Lead sponsor: Shirley Ryan AbilityLab
Sponsor class: OTHER
First posted: 2021-10-13
Enrollment: 200
Sex: ALL
Minimum age (years): 18
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: This device feasibility enrollment number of 200 is a larger sample in order to create a machine learning algorithm
Primary purpose: DEVICE_FEASIBILITY

Brief summary: The purpose of this study is to evaluate the feasibility and efficacy of a smart airbag system that detects and mitigates fall-related impact in individuals with high fall risk.

Detailed description: The purpose of this study is to evaluate the feasibility and efficacy of a smart airbag system that detects and mitigates fall-related impact in individuals with high fall risk.

The specific aims of this study are:

1. To evaluate and optimize pre-fall detection algorithms and the usability of the smart airbag system for fall mitigation in individuals with high fall risk.
2. To evaluate the efficacy of the smart airbag system in mitigating real-world falls and its effect on community mobility in individuals with high fall risk.

The investigators hypothesize that a soft, smart airbag system that uses advanced machine learning algorithms can accurately detect and mitigate falls, deploying appropriately to reduce hip fractures due to falls. The investigators also expect that wearing this device will decrease fear of falling and thus increase community mobility and social interaction.

Eligibility criteria: INCLUSION AND EXCLUSION CRITERIA

All potential subjects will be evaluated by research staff in order to match them to the inclusion and exclusion criteria that has been established - see below:

Inclusion Criteria - Able bodied Subjects:

* Healthy, able-bodied subject
* Age constrained from 18-70 years old
* No injury to either upper or lower extremity or history of back pain
* English speaking.

Exlusion Criteria - Able bodied Subjects:

* Waist circumference greater than 125 cm
* Pregnant women (status determined by self-reporting)
* Co-morbidity that interferes with the study (e.g. significant arthritis or joint problems, history of back injury, neuromuscular disorders, stroke, epilepsy, etc.)
* Individuals currently on anti-coagulants.
* Inactive, physically unfit
* Severe Osteoporosis (status determined by self-reporting)
* Non-English speaking
* Cognitive deficits or visual impairments (MMSE score \<17) that would impair their ability to give informed consent or impair their ability to follow simple instructions during the experiments

Inclusion Criteria - Fall Risk Subjects:

* Ages between 18-85 years old
* Individuals diagnosed with a Stroke (\> 6 months post), Parkinson's disease, aging elderly (ages 60-85)or lower-limb amputee with at least one self-reported fall in the last six months.
* Able to sit unsupported, walk at least with an assistive device and be able to follow a three-step command.
* For individuals with Parkinson's disease, Scoring 1 or higher on questions in Section II (Activities of Daily Living) and Section III (Motor examinations) on the Unified PD Rating Scale (UPDRS), be able to walk at least with an assistive device and be able to follow a three-step command.
* Waist circumference between 90 and 125 cm
* Either homebound or community ambulators.
* Willing to carry and use a smartphone and Airbag device.
* Willing to wear the airbag system as directed by the research personnel.
* English speaking
* Able and willing to give written consent and comply with study procedures.

Exclusion Criteria - Fall Risk Subjects

* Serious cardiac conditions, any musculoskeletal disorder, or other comorbidities that would interfere with participation in this minimal risk study.
* Non-healing ulcers of a lower extremity, Renal dialysis or end-stage liver disease, Legal blindness or severe visual impairment, a history of significant psychiatric illness.
* Subjects reporting a head injury from exposure to a blast/concussion injury with one or more of the following symptoms: dizziness, vertigo, headache, migraine, oscillopsia, movement induced vertigo, imbalance.
* Individuals who use a wheelchair for mobility both outdoors and indoors.
* Waist circumference greater than 125 cm
* Non-English speaking individuals
* Severe Osteoporosis (status determined by self-reporting,medical records)
* The subject is pregnant, nursing or planning a pregnancy.
* Individuals currently on anti-coagulants.
* Cognitive deficits or visual impairments (MMSE score \< 17) that would impair their ability to give informed consent or impair their ability to follow simple instructions during the experiments

Primary outcomes:
measure: Pre-fall classification performance
timeFrame: 1 year
Secondary outcomes:
Other outcomes:
Locations:
city: Chicago
country: United States
facility: Shirley Ryan AbilityLab
state: Illinois
Study officials:
affiliation: Shirley Ryan AbilityLab
name: Arun Jayaraman, PT, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Botonis OK, Harari Y, Embry KR, Mummidisetty CK, Riopelle D, Giffhorn M, Albert MV, Heike V, Jayaraman A. Wearable airbag technology and machine learned models to mitigate falls after stroke. J Neuroeng Rehabil. 2022 Jun 17;19(1):60. doi: 10.1186/s12984-022-01040-4.