StrokeMARSNCT07016295
Monitoring Arm Recovery After Stroke (MARS)
An observational study of Stroke, run by King's College London at 1 site in United Kingdom.
Trial summary
People who have a stroke often find it hard to do the things they did before. This can be caused by problems with arm movement. One in five people do not get any arm movement back after a stroke. Arm movements can be measured accurately in a laboratory, but it is very expensive and not easy to do in hospital. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Stroke
- What is being tested?
- Biomechanical analysis of arm movement and Pose estimation of arm movement
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 30 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 28 Jul 2025to 30 Apr 2027
- Phase
- Observational
- 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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: 18 stroke survivors 8 Healthy age-matched controls
Who may be able to join
- History of stroke
- Arm impairment evidenced by Fugl-Meyer Upper Limb Assessment between 9-60/66.
Who cannot join
- Severe cognitive impairment preventing ability to consent to treatment and understand and follow research protocol
- Severe language deficit preventing ability to consent to treatment and understand and follow research protocol
- Shoulder pain >3/10 on visual analog scale
- Unable to maintain independent sitting balance without a high back support.
- Wheelchair users that are unable to transfer with assistance of 1 to lab chair or whose wheelchair backrest cannot colapse.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site, 1 recruiting
- Recruiting
Centre for Human and Applied Physiological Sciences
London, SE1 1UL
Ulrike Hammerbeck, PhD, +44 (0) 207 848 888 x6292, ulrike.hammerbeck@kcl.ac.uk
Irene di Giulio, PhD
About this study
Official title: Developing an Accessible, Cost-Effective Motion Analysis Tool for Arm Movement After Stroke
People who have a stroke often find it hard to do the things they did before. This can be caused by problems with arm movement. One in five people do not get any arm movement back after a stroke.
Arm movements can be measured accurately in a laboratory, but it is very expensive and not easy to do in hospital. That means it is hard to tell if the arm is recovering to move like it did before the stroke or adapting to perform tasks in other ways.
Read more
To tell if a treatment is working, the investigators are making a phone app to record arm movement, using the camera. The recordings will be turned into data showing movement difficulties and sent to hospital records for clinicians. Clinicians will see if movement changes, to help choose the best treatment.
The investigators are looking for twelve stroke survivors to help test this app.
- The session will be at King's College London, on Guy's Campus.
- It will run for 2-3 hours.
- Participants will wear a vest or tight-fitting clothes.
- The investigators will place non-invasive markers on the participants arm.
- The investigators will video simple movements such as drinking from a cup.
- The investigators will also measure the same simple movements using the laboratory cameras.
This will show us if our app can measure arm movement as well as laboratory tests. If they do, the investigators will know the app is accurate.
In future this technology can improve recovery by correcting stroke survivors when they perform home exercises.
Read the detailed description
Upper limb recovery after stroke remains poor and 20% of stroke survivors do not recover arm movement. To improve outcome and advance insights to recovery mechanisms, an international collaboration has proposed a standardised set of outcome measures, including movement kinematics. Kinematics are moresensitive to change than clinical measures and can differentiate whether recovery is achieved by compensating to impairment or true recovery. However, kinematic assessments are not performed in clinical practice as 3-D motion capture requires expensive equipment and expertise for set-up and analysis.
The investigators therefore aim to develop a low-cost tool to measure kinematics. Open-source Artificial Intelligence models can detect positions and orientations on video and are called pose estimation models. The objectives will be to deploy and test these models in stroke survivors. The investigators will invite 12 stroke survivors with mild to moderate upper limb impairment and compare the accuracy of the models to gold-standard kinematic analysis when performing a variety of upper limb tasks. The investigators will optimise the models in case of any discrepancies. The investigators will develop a front-end smartphone app to instruct, record and provide feedback of arm movement performance to clinicians and stroke survivors. The investigators will develop the software back-end performing analysis of recorded movements and integrating these findings into electronic healthcare records for longitudinal performance tracking.
This accessible technology will provide clinicians kinematic analyses. Kinematics can guide treatment modifications and progression to improve upper limb movement.
- Conditions
- Stroke
- Being tested
- Biomechanical analysis of arm movement, Pose estimation of arm movement
- Keywords
- biomechanics, pose estimation models, upper limb
- Medical subject headings
- Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Biomechanical analysis of arm movementBehavioural
Marker based kinematic analysis
Pose estimation of arm movementBehavioural
Marker free kinematic analysis
| Study group | Role | What they receive |
|---|---|---|
| Stroke survivors | Not described Receives: Behavioral: Biomechanical analysis of arm movement; Behavioral: Pose estimation of arm movement | |
| Healthy age-matched controls | Not described Receives: Behavioral: Biomechanical analysis of arm movement; Behavioral: Pose estimation of arm movement |
What is being measured
The primary outcome is the main question the study is designed to answer.
Pose estimation model accuracy
Agreement between pose estimation and biomechanics measurements
Measured: During intervention
Secondary outcomes (5)
Fugl-Meyer Upper limb Assessment
Measured: baseline, before intervention
Motricity Index
Strength
Measured: baseline, before intervention
Cancellation OCS
neglect
Measured: baseline, before intervention
Box and block
dexterity
Measured: during the intervention
ARAT-2
Measured: during the intervention
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Jun 2025
- Study start28 Jul 2025
- Primary completion30 Sep 2026 (estimated)
- Study completion30 Apr 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for StrokeStudies of the same condition, open and under way.
- More trials run by King's College LondonThe 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
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- King's College London
- Sponsor type
- University, hospital or other
- Collaborators
- King's College Hospital NHS Trust
- Responsible party
- Sponsor
- Investigators
- Vasa Curcin, PhD, Study chair, King's College London
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07016295
- Sponsor's protocol ID
- LRS/RGO-24/25-47508
- Acronym
- MARS
- Status last verified
- May 2025
- First submitted
- 30 May 2025
- Last updated
- 11 Aug 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: The main data includes videos of participants which are impossible to anonymise. Therefore it is not appropriate for sharing.
Study at a glance
From the registry record, last updated by the sponsor on 11 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Developing an Accessible, Cost-Effective Motion Analysis Tool for Arm Movement After Stroke
- ClinicalTrials.gov ID
- NCT07016295
- Acronym / sponsor ID
- MARS / LRS/RGO-24/25-47508
- Conditions
- Stroke
- Keywords
- biomechanics, pose estimation models, upper limb
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- King's College LondonUniversity, hospital or other
- Collaborators
- King's College Hospital NHS Trust
- Study start
- 28 Jul 2025 (actual)
- Primary completion
- 30 Sep 2026 (estimated)
- Study completion
- 30 Apr 2027 (estimated)
- First posted
- 11 Jun 2025 (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.
People who have a stroke often find it hard to do the things they did before. This can be caused by problems with arm movement. One in five people do not get any arm movement back after a stroke.
Arm movements can be measured accurately in a laboratory, but it is very expensive and not easy to do in hospital. That means it is hard to tell if the arm is recovering to move like it did before the stroke or adapting to perform tasks in other ways.
To tell if a treatment is working, the investigators are making a phone app to record arm movement, using the camera. The recordings will be turned into data showing movement difficulties and sent to hospital records for clinicians. Clinicians will see if movement changes, to help choose the best treatment.
The investigators are looking for twelve stroke survivors to help test this app.
- The session will be at King's College London, on Guy's Campus.
- It will run for 2-3 hours.
- Participants will wear a vest or tight-fitting clothes.
- The investigators will place non-invasive markers on the participants arm.
- The investigators will video simple movements such as drinking from a cup.
- The investigators will also measure the same simple movements using the laboratory cameras.
This will show us if our app can measure arm movement as well as laboratory tests. If they do, the investigators will know the app is accurate.
In future this technology can improve recovery by correcting stroke survivors when they perform home exercises.
Detailed description
Upper limb recovery after stroke remains poor and 20% of stroke survivors do not recover arm movement. To improve outcome and advance insights to recovery mechanisms, an international collaboration has proposed a standardised set of outcome measures, including movement kinematics. Kinematics are moresensitive to change than clinical measures and can differentiate whether recovery is achieved by compensating to impairment or true recovery. However, kinematic assessments are not performed in clinical practice as 3-D motion capture requires expensive equipment and expertise for set-up and analysis.
The investigators therefore aim to develop a low-cost tool to measure kinematics. Open-source Artificial Intelligence models can detect positions and orientations on video and are called pose estimation models. The objectives will be to deploy and test these models in stroke survivors. The investigators will invite 12 stroke survivors with mild to moderate upper limb impairment and compare the accuracy of the models to gold-standard kinematic analysis when performing a variety of upper limb tasks. The investigators will optimise the models in case of any discrepancies. The investigators will develop a front-end smartphone app to instruct, record and provide feedback of arm movement performance to clinicians and stroke survivors. The investigators will develop the software back-end performing analysis of recorded movements and integrating these findings into electronic healthcare records for longitudinal performance tracking.
This accessible technology will provide clinicians kinematic analyses. Kinematics can guide treatment modifications and progression to improve upper limb movement.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Stroke survivors | – | Behavioral: Biomechanical analysis of arm movement, Behavioral: Pose estimation of arm movement |
| Healthy age-matched controls | – | Behavioral: Biomechanical analysis of arm movement, Behavioral: Pose estimation of arm movement |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- 18 stroke survivors 8 Healthy age-matched controls
Key inclusion criteria (2 listed)
- History of stroke
- Arm impairment evidenced by Fugl-Meyer Upper Limb Assessment between 9-60/66.
Key exclusion criteria (5 listed)
- Severe cognitive impairment preventing ability to consent to treatment and understand and follow research protocol
- Severe language deficit preventing ability to consent to treatment and understand and follow research protocol
- Shoulder pain >3/10 on visual analog scale
- Unable to maintain independent sitting balance without a high back support.
- Wheelchair users that are unable to transfer with assistance of 1 to lab chair or whose wheelchair backrest cannot colapse.
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 |
|---|---|---|
| Biomechanical analysis of arm movementMarker based kinematic analysis | Behavioural | Healthy age-matched controls, Stroke survivors |
| Pose estimation of arm movementMarker free kinematic analysis | Behavioural | Healthy age-matched controls, Stroke survivors |
Primary outcome
Pose estimation model accuracy
Time frame: During intervention
Agreement between pose estimation and biomechanics measurements
5 secondary outcomes
Fugl-Meyer Upper limb Assessment
Time frame: baseline, before intervention
Motricity Index
Time frame: baseline, before intervention
Cancellation OCS
Time frame: baseline, before intervention
Box and block
Time frame: during the intervention
ARAT-2
Time frame: during the intervention
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 11 Aug 2025.
- Individual participant dataSharing planned: No. The main data includes videos of participants which are impossible to anonymise. Therefore it is not appropriate for sharing.
Related trials for Stroke
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ELATE Study: Evaluating Large-vessel Acute Thrombectomy in Extended Time Window
Acute Ichemic Stroke
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Web-Based Tele-Rehabilitation Using Action Observation and Mirror Therapy for Subacute Stroke: A Randomized Controlled Trial
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Early Motor-Cognitive Integrative Training on Cognitive and Motor Performance in Patients With Aneurysmal Subarachnoid Hemorrhage
Subarachnoid Aneurysm Hemorrhage
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Selective Intra-Arterial Hypothermia After Endovascular Treatment for Acute Basilar Artery Occlusion
Acute Ischemic Stroke, Basilar Artery Occlusion
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.
Vasa Curcin, PhD study chair
King's College London
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Stroke, run by King's College London at 1 site in United Kingdom.
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 2 inclusion and 5 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: looking for participants now, as of the sponsor's last update on 11 Aug 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 Kingdom. 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?
Contact Ulrike Hammerbeck, PhD (+44 (0) 20 7888 6292, ulrike.hammerbeck@kcl.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pose estimation model accuracy (time frame: During intervention). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 11 Aug 2025.