StrokeNCT05076565
Wearable Airbag Technology to Mitigate Falls in Individuals With High Fall Risk
A study testing Airbag Belt Fall Protection System in people with Stroke and Parkinson Disease, run by Shirley Ryan AbilityLab at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 85 yearsHealthy volunteers can take part
- Conditions the study is for
- Stroke, Parkinson Disease, Lower Limb Amputation Knee
- What is being tested?
- Airbag Belt Fall Protection System
- Type of treatment
- Medical device
- How many people
- 200 participants
- Where
- 1 siteUnited States
- Study dates
- 14 Jan 2018to 14 Dec 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 85 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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:
- 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:
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- 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
- 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.
Who cannot join
- 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
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- 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
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the 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:
- 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.
- 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.
- Conditions
- Stroke, Parkinson Disease, Lower Limb Amputation Knee, Fall Injury, Fall Patients, Falling
- Being tested
- Airbag Belt Fall Protection System
- Medical subject headings
- Stroke, Parkinson Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Airbag Belt Fall Protection SystemDevice
Both versions of Airbags features different number of IMU sensors. Participant's will be randomly assigned one of the two versions. The algorithms developed in this project will help the researcher to identify the optimal performance (sensitivity and specificity values for detecting falls). Based on this information the research team will be able to choose a version for home/community deployment portion of the study. Based on the performance of the airbags in detecting true positives (falls) and true negatives (non-falls) accurately one of the airbags will be used in community deployment phase of the study.
What is being measured
The primary outcome is the main question the study is designed to answer.
Pre-fall classification performance
Derivation(s) from a confusion matrix
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Oct 2021
- Study start14 Jan 2018
- Primary completion14 Dec 2026 (estimated)
- Study completion14 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for StrokeStudies of the same condition, open and under way.
- More trials run by Shirley Ryan AbilityLabThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Device feasibility
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- This device feasibility enrollment number of 200 is a larger sample in order to create a machine learning algorithm
- Masking
- None (open label)
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shirley Ryan AbilityLab
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Arun Jayaraman, PT, PhD, Shirley Ryan AbilityLab
- Investigators
- Arun Jayaraman, PT, PhD, Principal investigator, Shirley Ryan AbilityLab
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05076565
- Sponsor's protocol ID
- STU00209246
- Status last verified
- Dec 2025
- First submitted
- 11 Jun 2021
- Last updated
- 29 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 35715823
Study at a glance
From the registry record, last updated by the sponsor on 29 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Wearable Airbag Technology to Mitigate Falls in Individuals With High Fall Risk
- ClinicalTrials.gov ID
- NCT05076565
- Acronym / sponsor ID
- STU00209246
- Conditions
- Stroke, Parkinson Disease, Lower Limb Amputation Knee, Fall Injury, Fall Patients, Falling
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Shirley Ryan AbilityLabUniversity, hospital or other
- Study start
- 14 Jan 2018 (actual)
- Primary completion
- 14 Dec 2026 (estimated)
- Study completion
- 14 Dec 2026 (estimated)
- First posted
- 13 Oct 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- 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.
- 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.
Study design
- Primary purpose
- Device feasibility
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Model description
- This device feasibility enrollment number of 200 is a larger sample in order to create a machine learning algorithm
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (24 listed)
- 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:
- 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.
Key exclusion criteria (10 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Airbag Belt Fall Protection SystemBoth versions of Airbags features different number of IMU sensors. Participant's will be randomly assigned one of the two versions. The algorithms developed in this project will help the researcher to identify the optimal performance (sensitivity and specificity values for detecting falls). Based on this information the research team will be able to choose a version for home/community deployment portion of the study. Based on the performance of the airbags in detecting true positives (falls) and true negatives (non-falls) accurately one of the airbags will be used in community deployment phase of the study. | Device | – |
Primary outcome
Pre-fall classification performance
Time frame: 1 year
Derivation(s) from a confusion matrix
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Dec 2025.
- Derived from this study: PubMed 35715823Botonis 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Arun Jayaraman, PT, PhD principal investigator
Shirley Ryan AbilityLab
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Airbag Belt Fall Protection System in people with Stroke and Parkinson Disease, run by Shirley Ryan AbilityLab at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 24 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 29 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pre-fall classification performance (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05076565, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 29 Dec 2025; AzTrials last refreshed its copy on 7 Nov 2026.