Healthy ControlsNCT06733077
Development of Digital Services for Parkinson's Disease
A study testing gait with cueing wearable device and neuro-ocular performance in people with Healthy Controls and Parkinson's Disease, run by University of Exeter at 1 site in United Kingdom.
Trial summary
In this project, ocular motor, pupil and gait data in people with Parkinson's disease (PD) will be collected in order to develop machine learning models for the diagnosis and monitoring of PD. With this, the investigators aim to advance the state of the art in PD diagnosis and monitoring. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Healthy Controls, Parkinson's Disease
- What is being tested?
- gait with cueing wearable device and neuro-ocular performance
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 80 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 20 Dec 2024to 1 Apr 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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
None listed.
Who cannot join
- Any physical or mental condition affecting ability to safely participate in this level of activity and capacity to understand testing as demonstrated by ability to safely follow commands and pass the PARQ by the research team.
- Cognitive impairment affecting ability to safely participate and follow instructions
- Any injury or disorder that may affect balance (other than Parkinson's or referring primary condition)
- Any skin conditions or broken skin in the calf and behind knee area
- Deep brain stimulation or pacemaker implants or other implant that may interfere with the measurement system
- Medications likely to affect eye sight or use of virtual reality sytstem
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- Healthy participants
- Any physical or mental condition affecting ability to safely participate in this level of activity and capacity to understand testing as demonstrated by ability to safely follow commands and pass the PARQ by the research team.
- Cognitive impairment affecting ability to safely participate and follow instructions
- Any injury or disorder that may affect balance (other than Parkinson's or referring primary condition)
- Any skin conditions or broken skin in the calf and behind knee area
- Deep brain stimulation or pacemaker implants or other implants that may interfere with the measurement system
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
University of Exeter
Exeter, EX1 2LU
Helen Dawes, 00441392402969, h.dawes@exeter.ac.uk
About this study
Official title: Development of Digital Diagnostics and Intervention Services for Parkinson's Disease
In this project, ocular motor, pupil and gait data in people with Parkinson's disease (PD) will be collected in order to develop machine learning models for the diagnosis and monitoring of PD. With this, the investigators aim to advance the state of the art in PD diagnosis and monitoring. By integrating the principles of machine learning with high-quality sensor data, more accurate and earlier diagnosis could potentially be achieved. Ocular motor and pupil data will be collected with the standard clinical examination and with neos, a medical device approved for objective ocular motor and pupil measurement. Gait will be collected using an IMU sensor and GaitQ senti, a consumer device that allows for an objective and continuous remote gait monitoring.
Read the detailed description
Parkinson's disease (PD) is one of the most common neurodegenerative diseases worldwide, affecting 1% of the population older than 65.
Currently, PD diagnosis is based on history, clinical assessments, and neurological examination.
The most widely used criteria for diagnosis are the Movement Disorder Society (MDS) criteria and instrument (i.e. The MDS-UPDRS). Further information may be gained from people's subjective description of their symptoms and/or via some short walking tests, such as 3-meter Timed Up and Go (TUG) performed as a snapshot in the clinic. However, people's symptoms vary through and between days and subjective descriptions rely on their memory and observations at home. These recollections can be unreliable or lack enough detail (particularly when the person has cognitive impairment). Therefore, current PD diagnosis criteria are highly dependent on the person and on the diagnosing physician. This subjectivity may lead to a variability in the diagnosis. Furthermore, these clinical assessments are unable to accurately track disease progression over time, making it difficult to provide personalized care. Additionally, manual examinations lack precise measurement instruments, resulting in a low precision of observed measurements and the inability to detect early-stage, subclinical signs. An objective diagnosis based on quantitative data rather than subjective interpretation of clinical findings is important. Therefore, an early and accurate diagnosis of PD, as well as accurate disease progression monitoring, are still important challenges in PD.
Several oculo-visual abnormalities have been described in PD. Studies report an abnormal ocular motor function in 75-87.5% of people with PD. These dysfunctions may precede or follow motor symptoms and thus, the evaluation of ocular motor function may provide valuable information regarding early disease detection or disease progression. The most commonly reported ocular motor dysfunctions are impairments in saccades, smooth pursuit, and vergence.
Gait impairments are among the most common and disabling symptoms of PD. Gait impairments include freezing of gait (FOG), an inability to initiate or maintain normal walking patterns, often resulting in a stochastic stop/start gait, and festinating gait (FSG), which is a shortening of stride length with elevated step frequency, resulting in fast, shuffling steps. Both FOG and FSG contribute to an increased risk of falls (and fall-related injuries) in people with PD relative to the wider elderly population. Objective, and continuous remote gait monitoring would be highly important in people with PD, to objectively track gait impairments in real-time, and potentially contribute to objectively track disease progression, which may lead to personalized care for individuals with PD.
In this project, ocular motor, pupil and gait data in people with Parkinson's disease (PD) will be collected in order to develop machine learning models for the diagnosis and monitoring of PD. With this, the investigators aim to advance the state of the art in PD diagnosis and monitoring. By integrating the principles of machine learning with high-quality sensor data, more accurate and earlier diagnosis could potentially be achieved. Ocular motor and pupil data will be collected with the standard clinical examination and with neos, a medical device approved for objective ocular motor and pupil measurement. Gait will be collected using an IMU sensor and GaitQ senti, a consumer device that allows for an objective and continuous remote gait monitoring.
The primary objective of this project is to collect ocular motor, pupil and gait data from people with PD in order to develop and compare machine learning models for diagnosing and monitoring PD.
Secondary objectives are:
Correlate ocular motor, pupil and gait parameters with several clinical parameters, including the MDS-UPDRS.
Collect real-world evidence (RWE) data regarding health economics parameters to address the individual and combined properties, effects, and/or impacts of the deployed health technologies.
By analysing the data collected, we also aim to contribute to the scientific understanding of PD, potentially uncovering new insights into disease patterns, progression, and response to treatments.
- Conditions
- Healthy Controls, Parkinson's Disease
- Being tested
- gait with cueing wearable device and neuro-ocular performance
- Keywords
- gaitQ, long-term movement condition, digital healthcare, MachineMD
- Medical subject headings
- Parkinson Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
gait with cueing wearable device and neuro-ocular performanceDevice
Participants will be invited to participate in the following sequential phases. Participants can participate in Phases as selected. Control participants will not be invited to Phase 4.
Phase 1. Lab testing [2 hours] Validation study of digital technology measures MachineMD and gaitQ to criterion metric of UPDRS.
Phase 2. home/community testing [2 weeks daily] Determine feasibility of daily measuring in the home of gaitQ to determine usability, acceptability, and day to day variability of measurement metrics and to determine concurrent validation of home metric to lab metrics to determine, reliability, concurrent validity of change, minimal detectable change and criterion validation to lab-based measures.
Phase 3. Lab retesting [2 hours] see Phase 1
Phase 4. Home/community intervention [2 weeks] Determine the potential for effect of the gaitQ vibration intervention from a 2-week exposure in the home.
| Study group | Role | What they receive |
|---|---|---|
| Feasibility of using the MachineMD and gaitQ devices | Experimental | To complete gaitQ and MachineMD digital feasibility assessment and intervention service development Receives: Device: gait with cueing wearable device and neuro-ocular performance |
What is being measured
The primary outcome is the main question the study is designed to answer.
Step length
Step length (measured in meters) during the gait tasks (TUG, 5 sit to stand, 15-m walk, 5-min walk).
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Step rate
Step rate (measured in steps per minute) will be measured during the gait tasks (TUG, 5 sit to stand, 15-m walk, 5-min walk).
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Step length symmetry index
Step length symmetry index will be calculated using the following equation:
[((R - L)/0.5 × (R + L)) × 100], where R: right leg, L: left leg
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Walking speed
Walking speed (meters per second) will be measured during the gait activities (TUG, 5 sit to stand, 15-m walk, 5-min walk).
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Timed Up and Go test
The time (in seconds) to complete the Timed Up and Go task will be recorded.
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Five times Sit to Stand
The time (in seconds) a person needs to stand up from a standard height chair and sit back down five times.
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
15-m Walk
The time (in seconds) needed to cover 15 meters in straight line walking
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
5-min Walk
The distance a participant walks in 5 minutes (measured in meters and can round to the nearest decimal place).
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Safety of the gaitQ device
Safety of the gaitQ device will be assessed by recording the adverse events (expected and unexpected).
Measured: From lab visit 1 to the end of the intervention (up to 6 weeks).
Usability of the gaitQ device
Usability of the gaitQ device will be assessed through successful establishment of a system usability scale target >68 and through the number of therapy support sessions required.
Measured: From lab visit 1 to the end of the intervention (up to 6 weeks).
Ocular motor and pupil function - Standard manual test
Ocular motor and pupil function scores derived from gaze (left, centre, right), ocular alignment, pupilary function, saccades (horizontal, vertical), smooth pursuit, visual field screening, and convergence.
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Ocular motor and pupil function - Neos device
Ocular motor and pupil function scores derived from gaze (left, centre, right), ocular alignment, pupilary function, saccades (horizontal, vertical), smooth pursuit, visual field screening, and convergence.
Measured: From lab visit 1 to lab visit 2 (up to 3 weeks).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Dec 2024
- Study start20 Dec 2024
- Primary completion1 Apr 2026 (estimated)
- Study completion1 Apr 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Healthy ControlsStudies of the same condition, open and under way.
- 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
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- Feasibility study (before and after)
- Masking
- None (open label)
- Enrolment
- 80 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Exeter
- Sponsor type
- University, hospital or other
- Collaborators
- University of Zurich, University Hospital, Zürich, machineMD AG, GaitQ company
- Responsible party
- Sponsor
- Investigators
- Helen Dawes, PhD, Principal investigator, University of Exeter
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06733077
- Sponsor's protocol ID
- 2023-24-18
- Other IDs
- 10086932
- Status last verified
- Jan 2025
- First submitted
- 20 Nov 2024
- Last updated
- 3 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 3 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of Digital Diagnostics and Intervention Services for Parkinson's Disease
- ClinicalTrials.gov ID
- NCT06733077
- Acronym / sponsor ID
- 2023-24-18
- Conditions
- Healthy Controls, Parkinson's Disease
- Keywords
- gaitQ, long-term movement condition, digital healthcare, MachineMD
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 80 participants (estimated)
- Lead sponsor
- University of ExeterUniversity, hospital or other
- Collaborators
- University of Zurich, University Hospital, Zürich, machineMD AG, GaitQ company
- Study start
- 20 Dec 2024 (actual)
- Primary completion
- 1 Apr 2026 (estimated)
- Study completion
- 1 Apr 2026 (estimated)
- First posted
- 13 Dec 2024 (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.
In this project, ocular motor, pupil and gait data in people with Parkinson's disease (PD) will be collected in order to develop machine learning models for the diagnosis and monitoring of PD. With this, the investigators aim to advance the state of the art in PD diagnosis and monitoring. By integrating the principles of machine learning with high-quality sensor data, more accurate and earlier diagnosis could potentially be achieved. Ocular motor and pupil data will be collected with the standard clinical examination and with neos, a medical device approved for objective ocular motor and pupil measurement. Gait will be collected using an IMU sensor and GaitQ senti, a consumer device that allows for an objective and continuous remote gait monitoring.
Detailed description
Parkinson's disease (PD) is one of the most common neurodegenerative diseases worldwide, affecting 1% of the population older than 65.
Currently, PD diagnosis is based on history, clinical assessments, and neurological examination.
The most widely used criteria for diagnosis are the Movement Disorder Society (MDS) criteria and instrument (i.e. The MDS-UPDRS). Further information may be gained from people's subjective description of their symptoms and/or via some short walking tests, such as 3-meter Timed Up and Go (TUG) performed as a snapshot in the clinic. However, people's symptoms vary through and between days and subjective descriptions rely on their memory and observations at home. These recollections can be unreliable or lack enough detail (particularly when the person has cognitive impairment). Therefore, current PD diagnosis criteria are highly dependent on the person and on the diagnosing physician. This subjectivity may lead to a variability in the diagnosis. Furthermore, these clinical assessments are unable to accurately track disease progression over time, making it difficult to provide personalized care. Additionally, manual examinations lack precise measurement instruments, resulting in a low precision of observed measurements and the inability to detect early-stage, subclinical signs. An objective diagnosis based on quantitative data rather than subjective interpretation of clinical findings is important. Therefore, an early and accurate diagnosis of PD, as well as accurate disease progression monitoring, are still important challenges in PD.
Several oculo-visual abnormalities have been described in PD. Studies report an abnormal ocular motor function in 75-87.5% of people with PD. These dysfunctions may precede or follow motor symptoms and thus, the evaluation of ocular motor function may provide valuable information regarding early disease detection or disease progression. The most commonly reported ocular motor dysfunctions are impairments in saccades, smooth pursuit, and vergence.
Gait impairments are among the most common and disabling symptoms of PD. Gait impairments include freezing of gait (FOG), an inability to initiate or maintain normal walking patterns, often resulting in a stochastic stop/start gait, and festinating gait (FSG), which is a shortening of stride length with elevated step frequency, resulting in fast, shuffling steps. Both FOG and FSG contribute to an increased risk of falls (and fall-related injuries) in people with PD relative to the wider elderly population. Objective, and continuous remote gait monitoring would be highly important in people with PD, to objectively track gait impairments in real-time, and potentially contribute to objectively track disease progression, which may lead to personalized care for individuals with PD.
In this project, ocular motor, pupil and gait data in people with Parkinson's disease (PD) will be collected in order to develop machine learning models for the diagnosis and monitoring of PD. With this, the investigators aim to advance the state of the art in PD diagnosis and monitoring. By integrating the principles of machine learning with high-quality sensor data, more accurate and earlier diagnosis could potentially be achieved. Ocular motor and pupil data will be collected with the standard clinical examination and with neos, a medical device approved for objective ocular motor and pupil measurement. Gait will be collected using an IMU sensor and GaitQ senti, a consumer device that allows for an objective and continuous remote gait monitoring.
The primary objective of this project is to collect ocular motor, pupil and gait data from people with PD in order to develop and compare machine learning models for diagnosing and monitoring PD.
Secondary objectives are:
Correlate ocular motor, pupil and gait parameters with several clinical parameters, including the MDS-UPDRS.
Collect real-world evidence (RWE) data regarding health economics parameters to address the individual and combined properties, effects, and/or impacts of the deployed health technologies.
By analysing the data collected, we also aim to contribute to the scientific understanding of PD, potentially uncovering new insights into disease patterns, progression, and response to treatments.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- Feasibility study (before and after)
| Arm | Type | Receives |
|---|---|---|
| Feasibility of using the MachineMD and gaitQ devices | Experimental | Device: gait with cueing wearable device and neuro-ocular performanceTo complete gaitQ and MachineMD digital feasibility assessment and intervention service development |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (0 listed)
Key exclusion criteria (12 listed)
- Any physical or mental condition affecting ability to safely participate in this level of activity and capacity to understand testing as demonstrated by ability to safely follow commands and pass the PARQ by the research team.
- Cognitive impairment affecting ability to safely participate and follow instructions
- Any injury or disorder that may affect balance (other than Parkinson's or referring primary condition)
- Any skin conditions or broken skin in the calf and behind knee area
- Deep brain stimulation or pacemaker implants or other implant that may interfere with the measurement system
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 |
|---|---|---|
| gait with cueing wearable device and neuro-ocular performanceParticipants will be invited to participate in the following sequential phases. Participants can participate in Phases as selected. Control participants will not be invited to Phase 4. Phase 1. Lab testing [2 hours] Validation study of digital technology measures MachineMD and gaitQ to criterion metric of UPDRS. Phase 2. home/community testing [2 weeks daily] Determine feasibility of daily measuring in the home of gaitQ to determine usability, acceptability, and day to day variability of measurement metrics and to determine concurrent validation of home metric to lab metrics to determine, reliability, concurrent validity of change, minimal detectable change and criterion validation to lab-based measures. Phase 3. Lab retesting [2 hours] see Phase 1 Phase 4. Home/community intervention [2 weeks] Determine the potential for effect of the gaitQ vibration intervention from a 2-week exposure in the home. | Device | Feasibility of using the MachineMD and gaitQ devices |
Primary outcome
Step length
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
Step length (measured in meters) during the gait tasks (TUG, 5 sit to stand, 15-m walk, 5-min walk).
Step rate
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
Step rate (measured in steps per minute) will be measured during the gait tasks (TUG, 5 sit to stand, 15-m walk, 5-min walk).
Step length symmetry index
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
Step length symmetry index will be calculated using the following equation: [((R - L)/0.5 × (R + L)) × 100], where R: right leg, L: left leg
Walking speed
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
Walking speed (meters per second) will be measured during the gait activities (TUG, 5 sit to stand, 15-m walk, 5-min walk).
Timed Up and Go test
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
The time (in seconds) to complete the Timed Up and Go task will be recorded.
Five times Sit to Stand
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
The time (in seconds) a person needs to stand up from a standard height chair and sit back down five times.
15-m Walk
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
The time (in seconds) needed to cover 15 meters in straight line walking
5-min Walk
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
The distance a participant walks in 5 minutes (measured in meters and can round to the nearest decimal place).
Safety of the gaitQ device
Time frame: From lab visit 1 to the end of the intervention (up to 6 weeks).
Safety of the gaitQ device will be assessed by recording the adverse events (expected and unexpected).
Usability of the gaitQ device
Time frame: From lab visit 1 to the end of the intervention (up to 6 weeks).
Usability of the gaitQ device will be assessed through successful establishment of a system usability scale target >68 and through the number of therapy support sessions required.
Ocular motor and pupil function - Standard manual test
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
Ocular motor and pupil function scores derived from gaze (left, centre, right), ocular alignment, pupilary function, saccades (horizontal, vertical), smooth pursuit, visual field screening, and convergence.
Ocular motor and pupil function - Neos device
Time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).
Ocular motor and pupil function scores derived from gaze (left, centre, right), ocular alignment, pupilary function, saccades (horizontal, vertical), smooth pursuit, visual field screening, and convergence.
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 3 Feb 2025.
- 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.
Helen Dawes, PhD principal investigator
University of Exeter
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing gait with cueing wearable device and neuro-ocular performance in people with Healthy Controls and Parkinson's Disease, run by University of Exeter 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 0 inclusion and 12 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 3 Feb 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 Pavlos Evangelidis, PhD (00447866138722, p.evangelidis@exeter.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Step length (time frame: From lab visit 1 to lab visit 2 (up to 3 weeks).). The study lists 12 primary outcomes in all. 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 3 Feb 2025.