Inpatient Stroke Recovery Using Sensors

This observational study is looking at how wireless wearable sensors can help us understand stroke recovery. Researchers want to see if these sensors can continuously track and measure how people recover during their inpatient stay after a stroke. The study will compare data from people who have had a stroke with data from healthy individuals. The goal is to see if these sensors can accurately measure things like movement, speech, and swallowing, and help doctors understand how well someone is recovering. You could be eligible if you've had a stroke and are 18 or older, or if you are a healthy adult without significant health problems. The study aims to estimate clinical scores at discharge from inpatient stay.

Study design
This is an observational study planning to enroll 400 participants. It will compare individuals who have had a stroke with healthy controls.
What's involved
You would wear wireless wearable sensors that capture biometric and movement-based data. This monitoring would occur continuously during your inpatient stay, which averages 22 days.
Compensation
Not stated in the trial record.
Follow-up
The primary endpoint is measured at discharge from inpatient stay, which averages 22 days.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT04219670

Inpatient Stroke Recovery Using Sensors

Recruiting
Not specifiedAges 18+Observational
Shirley Ryan AbilityLab
~400 participants
Updated 2025-12-29 on ClinicalTrials.gov
What's tested:Wearable sensors

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Discharge clinical scores estimation
Measured over Discharge from inpatient stay. Average length of stay is 22 days.
Stroke

NCT04219670

Where you'd take part

This study runs at 1 site. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.

  • Shirley Ryan AbilityLab

    Chicago, Illinoisstudy coordinator listed

    Recruiting

Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.

  • Arun Jayaraman, PT, PhD · PRINCIPAL_INVESTIGATOR · Study Principal Investigator

Opens a ready-to-send draft in your own email app — review before sending.

Want this trial checked against your situation?

Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.

Check eligibility for this trial ~2 min · HIPAA-protected · delete anytime
Eligibility criteria

Inclusion

Patient group
Individuals diagnosed with stroke admitted to the Shirley Ryan AbilityLab (inpatient), or individuals in the community who had a stroke (chronic)
Age 18 or older
Able and willing to give written consent and comply with study procedures
Healthy control group
Individuals without any known significant health problem (healthy controls)
Age 18 or older
Able and willing to give written consent and comply with study procedures

Exclusion

Patient group
Neurological degenerative pathologies as co-morbidities (such as multiple sclerosis, Alzheimer's disease, Parkinson's disease, etc.)
Pregnant or nursing
Skin allergies or irritation; open wounds
Utilizing a powered, implanted cardiac device for monitoring or supporting heart function (i.e. pacemaker, defibrillator, or LVAD)
Healthy control group
No known history of cerebrovascular accidents or neurological degenerative pathologies (such as multiple sclerosis, Alzheimer's disease, Parkinson's disease, etc.)
Pregnant or nursing
Skin allergies or irritation; open wounds
Utilizing a powered, implanted cardiac device for monitoring or supporting heart function (i.e. pacemaker, defibrillator, or LVAD)
  • Discharge clinical scores estimationDischarge from inpatient stay. Average length of stay is 22 days.

    Error between clinical scores estimated from machine learning algorithms trained on sensor data from the Admission time-point, and true scores assessed at the discharge from the hospital.