Cerebral Palsy (CP)NCT06090383
Feasibility and Discriminant Validity of Monitoring Movement Behavior of Adolescents With Cerebral Palsy
An observational study of Cerebral Palsy (CP), run by Copenhagen University Hospital, Rigshospitalet at 1 site in Denmark.
Trial summary
A new artificial intelligence network has been developed to monitor real-world daytime and nighttime movement behavior of adolescents with cerebral palsy (CP). The network uses seven wearable sensors to recognize lying, sitting, and standing, as well as walking and movements of both arms and legs. Read more about this study
- Who is it for?
- Ages 15 to 25 years
- Conditions the study is for
- Cerebral Palsy (CP)
- How many people
- 25 participants
- Where
- 1 siteDenmark
- Study dates
- 16 Oct 2023to 31 Dec 2025
- 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 15 to 25 years
- All sexes
- Child, Adult
Study population: Primary care clinic and community sample
Who may be able to join
- Clinical diagnosis of Cerebral Palsy at GMFCS-E\&R levels I-V and typically developed without neurological impairment.
- Age range: 15-25 years
- Capable of providing informed consent or have a legal guardian who can provide consent on their behalf.
Who cannot join
- Adolescents without the capacity to provide informed consent when another young adult with the capacity can provide the same or similar data.
- Adolescents who have undergone musculoskeletal surgery or injury and have not resumed their normal movement behavior.
- Presence of skin wounds in areas where sensors are to be attached.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Denmark1 site, 1 recruiting
- Recruiting
University Hospital Copenhagen, Rigshospitalet
Copenhagen, 2100
Ivana Bardino Novosel, PhD. student, +4527328961, ivana.novosel@sund.ku.dk
Jakob Lorentzen, 31521131, j.lorentzen@sund.ku.dk
About this study
Official title: Wearable and Deep Learning-Based Recognition of Real-World Movement Behavior of Adolescents With Cerebral Palsy: Feasibility and Discriminant Validity Study
A new artificial intelligence network has been developed to monitor real-world daytime and nighttime movement behavior of adolescents with cerebral palsy (CP). The network uses seven wearable sensors to recognize lying, sitting, and standing, as well as walking and movements of both arms and legs. This information can be useful for healthcare professionals to understand and influence change in movement behavior, leading to benefits for the health of adolescents with cerebral palsy. This study aims to examine the acceptability and technical dependability of monitoring the movement behavior of adolescents with cerebral palsy for 72 hours using wearable sensors. Additionally, the study aims to evaluate the network's ability to discriminate between control and individuals with CP, different subgroups of individuals with CP, as well as the incidence of sleep disturbance in the entire cohort.
Read the detailed description
Cerebral palsy (CP) is a non-progressive disorder resulting from injuries or abnormalities in fetal or early infant brain development. According to registries from European countries, the condition affects 2-3 out of every 1000 live births. An individual with CP typically presents with motor development disorders that cause abnormal patterns of movement and posture due to impaired coordination of movements and muscle tone regulation. People with cerebral palsy can also have various other problems, including sensory and cognitive problems and sleep disturbances. These symptoms result in limitations in activity level and societal participation throughout the individual's life. Adolescents and even children as young as seven may experience a decline in motor ability, leading to changes in their movement behavior. Healthcare professionals rely on various observations and measurements performed in clinical and hospital settings to assess and treat individuals with CP. However, there is some uncertainty about whether these assessments truly reflect real-life movement behaviors, as using an impaired extremity in everyday life frequently deviates from its motor capacity. There is an absence of robust tools that capture daytime and nighttime movement behavior in real-world settings rather than in clinical or controlled environments. Hemiparesis is the most common marker of CP, making asymmetrical deficits a target for intensive interventions such as physical and occupational therapy. Yet, no clinical tools are available that document asymmetrical differences in the real world in children and adolescents with CP. An objective method to measure real-world movement patterns would allow therapists to identify individuals who need a more comprehensive evaluation and to target interventions and other management strategies more precisely. This would help children and adolescents with CP gain motor skills to maximize independence. Further, objectively observing individuals with CP in their daily lives is essential to gain insights into functional decline. It has been observed that children and adolescents with CP are more likely to experience sleep-related difficulties such as difficulty initiating sleep, frequent nocturnal awakenings, discomfort while in bed, and early morning awakenings. As sleep quality plays a vital role in health-related quality of life, it is crucial to have objective methods to evaluate and monitor potential sleep problems in a real-world context.
A deep-learning convolutional neural network has been modeled to recognize postures lying, sitting, and standing the activity of walking, and movements of the right and left extremities. The network uses accelerometer and gyroscope data from 7 wearable sensors. Testing of the network´s performance found that it surpasses human annotators in accurately classifying the movement behavior of healthy and typically developed adults. These findings are currently under review and have yet to be published. The present protocol details the methodology for assessing the feasibility of real-world movement behavior monitoring and the discriminant validity of the network in adolescents with CP and controls.
The feasibility evaluation examines the technology used, e.g., potential data loss and the credibility of data output, as well as user acceptance, e.g., sensor wear time and adverse events. The networks' discriminant ability will be assessed by the network's ability to differentiate between controls and CP severity, e.g., scores on the Gross Motor Functional Classification Scale - Expanded and revised (GMFCS-E\&R), different types of CP, differently affected body parts of the participating adolescents with CP, as well as individuals who have and have not sleep problems in the entire cohort.
- Conditions
- Cerebral Palsy (CP)
- Keywords
- Real-world, Movement Behavior, Adolescents, Cerebral Palsy, Wearables, Feasibility, Validity
- Medical subject headings
- Cerebral Palsy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Adolescents with CP and typically developed adolescents. | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Gross Motor Functional Classification Scale - Expanded and revised (GMFCS-E&R)
The GMFCS-E\&R is a classification system comprising five levels that aims to describe the gross motor function of children and adolescents with CP. This system considers five age bands; in this case, we use the 12-18-year-old age band. Individuals with CP are classified as level I when capable of walking without limitations, while those with non-ambulatory functions are classified as levels IV and V
Measured: Day one
Jenkins Sleep Evaluation Questionnaire (JSEQ) - Danish version
The JSEQ evaluates the frequency and intensity of sleep difficulties in the past month. The questions pertain to difficulty falling asleep, frequent awakenings during the night, trouble remaining asleep, and subjective feelings of fatigue and sleepiness despite a typical night's rest. Respondents rate their experiences using a Likert-type scale, with the following response alternatives: not at all (1), 1 to 3 days (2), 4 to 7 days (3), 8 to 14 days (4), 15 to 21 days (5), and 22 to 28 days (6).
Measured: Day one
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Oct 2023
- Study start16 Oct 2023
- Primary completion31 Dec 2025 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for Cerebral Palsy (CP)Studies of the same condition, open and under way.
- More trials run by Copenhagen University Hospital, RigshospitaletThe 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
- Prospective
- Enrolment
- 25 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Copenhagen University Hospital, Rigshospitalet
- Sponsor type
- University, hospital or other
- Collaborators
- University of Copenhagen
- Responsible party
- Principal investigator, Jan Christensen, Copenhagen University Hospital, Rigshospitalet
- Investigators
- Jakob Lorentzen, Prof., Principal investigator, University of Copenhagen, Department of Neuroscience
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06090383
- Sponsor's protocol ID
- Sensor-H-22032100
- Status last verified
- Jun 2025
- First submitted
- 9 Oct 2023
- Last updated
- 22 Jun 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Upon reasonable request
Publications
Wimalasundera N, Stevenson VL. Cerebral palsy. Pract Neurol. 2016 Jun;16(3):184-94. doi: 10.1136/practneurol-2015-001184. Epub 2016 Feb 2.
PubMed 26837375Hanna SE, Rosenbaum PL, Bartlett DJ, Palisano RJ, Walter SD, Avery L, Russell DJ. Stability and decline in gross motor function among children and youth with cerebral palsy aged 2 to 21 years. Dev Med Child Neurol. 2009 Apr;51(4):295-302. doi: 10.1111/j.1469-8749.2008.03196.x.
PubMed 19391185Hulst RY, Gorter JW, Obeid J, Voorman JM, van Rijssen IM, Gerritsen A, Visser-Meily JMA, Pillen S, Verschuren O. Accelerometer-measured physical activity, sedentary behavior, and sleep in children with cerebral palsy and their adherence to the 24-hour activity guidelines. Dev Med Child Neurol. 2023 Mar;65(3):393-405. doi: 10.1111/dmcn.15338. Epub 2022 Jul 14.
PubMed 35833425Palisano RJ, Rosenbaum P, Bartlett D, Livingston MH. Content validity of the expanded and revised Gross Motor Function Classification System. Dev Med Child Neurol. 2008 Oct;50(10):744-50. doi: 10.1111/j.1469-8749.2008.03089.x.
PubMed 18834387
Study at a glance
From the registry record, last updated by the sponsor on 22 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Wearable and Deep Learning-Based Recognition of Real-World Movement Behavior of Adolescents With Cerebral Palsy: Feasibility and Discriminant Validity Study
- ClinicalTrials.gov ID
- NCT06090383
- Acronym / sponsor ID
- Sensor-H-22032100
- Conditions
- Cerebral Palsy (CP)
- Keywords
- Real-world, Movement Behavior, Adolescents, Cerebral Palsy, Wearables, Feasibility, Validity
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 25 participants (estimated)
- Lead sponsor
- Copenhagen University Hospital, RigshospitaletUniversity, hospital or other
- Collaborators
- University of Copenhagen
- Study start
- 16 Oct 2023 (actual)
- Primary completion
- 31 Dec 2025 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 19 Oct 2023 (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.
A new artificial intelligence network has been developed to monitor real-world daytime and nighttime movement behavior of adolescents with cerebral palsy (CP). The network uses seven wearable sensors to recognize lying, sitting, and standing, as well as walking and movements of both arms and legs. This information can be useful for healthcare professionals to understand and influence change in movement behavior, leading to benefits for the health of adolescents with cerebral palsy. This study aims to examine the acceptability and technical dependability of monitoring the movement behavior of adolescents with cerebral palsy for 72 hours using wearable sensors. Additionally, the study aims to evaluate the network's ability to discriminate between control and individuals with CP, different subgroups of individuals with CP, as well as the incidence of sleep disturbance in the entire cohort.
Detailed description
Cerebral palsy (CP) is a non-progressive disorder resulting from injuries or abnormalities in fetal or early infant brain development. According to registries from European countries, the condition affects 2-3 out of every 1000 live births. An individual with CP typically presents with motor development disorders that cause abnormal patterns of movement and posture due to impaired coordination of movements and muscle tone regulation. People with cerebral palsy can also have various other problems, including sensory and cognitive problems and sleep disturbances. These symptoms result in limitations in activity level and societal participation throughout the individual's life. Adolescents and even children as young as seven may experience a decline in motor ability, leading to changes in their movement behavior. Healthcare professionals rely on various observations and measurements performed in clinical and hospital settings to assess and treat individuals with CP. However, there is some uncertainty about whether these assessments truly reflect real-life movement behaviors, as using an impaired extremity in everyday life frequently deviates from its motor capacity. There is an absence of robust tools that capture daytime and nighttime movement behavior in real-world settings rather than in clinical or controlled environments. Hemiparesis is the most common marker of CP, making asymmetrical deficits a target for intensive interventions such as physical and occupational therapy. Yet, no clinical tools are available that document asymmetrical differences in the real world in children and adolescents with CP. An objective method to measure real-world movement patterns would allow therapists to identify individuals who need a more comprehensive evaluation and to target interventions and other management strategies more precisely. This would help children and adolescents with CP gain motor skills to maximize independence. Further, objectively observing individuals with CP in their daily lives is essential to gain insights into functional decline. It has been observed that children and adolescents with CP are more likely to experience sleep-related difficulties such as difficulty initiating sleep, frequent nocturnal awakenings, discomfort while in bed, and early morning awakenings. As sleep quality plays a vital role in health-related quality of life, it is crucial to have objective methods to evaluate and monitor potential sleep problems in a real-world context.
A deep-learning convolutional neural network has been modeled to recognize postures lying, sitting, and standing the activity of walking, and movements of the right and left extremities. The network uses accelerometer and gyroscope data from 7 wearable sensors. Testing of the network´s performance found that it surpasses human annotators in accurately classifying the movement behavior of healthy and typically developed adults. These findings are currently under review and have yet to be published. The present protocol details the methodology for assessing the feasibility of real-world movement behavior monitoring and the discriminant validity of the network in adolescents with CP and controls.
The feasibility evaluation examines the technology used, e.g., potential data loss and the credibility of data output, as well as user acceptance, e.g., sensor wear time and adverse events. The networks' discriminant ability will be assessed by the network's ability to differentiate between controls and CP severity, e.g., scores on the Gross Motor Functional Classification Scale - Expanded and revised (GMFCS-E\&R), different types of CP, differently affected body parts of the participating adolescents with CP, as well as individuals who have and have not sleep problems in the entire cohort.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Adolescents with CP and typically developed adolescents. | – | – |
Who may qualify
- Ages
- 15 to 25 years
- Sex
- All
- Age groups
- Child, Adult
- Study population
- Primary care clinic and community sample
Key inclusion criteria (3 listed)
- Clinical diagnosis of Cerebral Palsy at GMFCS-E\&R levels I-V and typically developed without neurological impairment.
- Age range: 15-25 years
- Capable of providing informed consent or have a legal guardian who can provide consent on their behalf.
Key exclusion criteria (3 listed)
- Adolescents without the capacity to provide informed consent when another young adult with the capacity can provide the same or similar data.
- Adolescents who have undergone musculoskeletal surgery or injury and have not resumed their normal movement behavior.
- Presence of skin wounds in areas where sensors are to be attached.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Gross Motor Functional Classification Scale - Expanded and revised (GMFCS-E&R)
Time frame: Day one
The GMFCS-E\&R is a classification system comprising five levels that aims to describe the gross motor function of children and adolescents with CP. This system considers five age bands; in this case, we use the 12-18-year-old age band. Individuals with CP are classified as level I when capable of walking without limitations, while those with non-ambulatory functions are classified as levels IV and V
Jenkins Sleep Evaluation Questionnaire (JSEQ) - Danish version
Time frame: Day one
The JSEQ evaluates the frequency and intensity of sleep difficulties in the past month. The questions pertain to difficulty falling asleep, frequent awakenings during the night, trouble remaining asleep, and subjective feelings of fatigue and sleepiness despite a typical night's rest. Respondents rate their experiences using a Likert-type scale, with the following response alternatives: not at all (1), 1 to 3 days (2), 4 to 7 days (3), 8 to 14 days (4), 15 to 21 days (5), and 22 to 28 days (6).
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 22 Jun 2025.
- Background: PubMed 26837375Wimalasundera N, Stevenson VL. Cerebral palsy. Pract Neurol. 2016 Jun;16(3):184-94. doi: 10.1136/practneurol-2015-001184. Epub 2016 Feb 2.
- Background: PubMed 19391185Hanna SE, Rosenbaum PL, Bartlett DJ, Palisano RJ, Walter SD, Avery L, Russell DJ. Stability and decline in gross motor function among children and youth with cerebral palsy aged 2 to 21 years. Dev Med Child Neurol. 2009 Apr;51(4):295-302. doi: 10.1111/j.1469-8749.2008.03196.x.
- Background: PubMed 35833425Hulst RY, Gorter JW, Obeid J, Voorman JM, van Rijssen IM, Gerritsen A, Visser-Meily JMA, Pillen S, Verschuren O. Accelerometer-measured physical activity, sedentary behavior, and sleep in children with cerebral palsy and their adherence to the 24-hour activity guidelines. Dev Med Child Neurol. 2023 Mar;65(3):393-405. doi: 10.1111/dmcn.15338. Epub 2022 Jul 14.
- Background: PubMed 18834387Palisano RJ, Rosenbaum P, Bartlett D, Livingston MH. Content validity of the expanded and revised Gross Motor Function Classification System. Dev Med Child Neurol. 2008 Oct;50(10):744-50. doi: 10.1111/j.1469-8749.2008.03089.x.
- Individual participant dataSharing planned: Undecided. Upon reasonable request
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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.
Jakob Lorentzen, Prof. principal investigator
University of Copenhagen, Department of Neuroscience
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 Cerebral Palsy (CP), run by Copenhagen University Hospital, Rigshospitalet at 1 site in Denmark.
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 3 inclusion and 3 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 22 Jun 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 Denmark. 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 Ivana Bardino Novosel, Ph.d. student (+4527328961, ivana.novosel@sund.ku.dk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Gross Motor Functional Classification Scale - Expanded and revised (GMFCS-E&R) (time frame: Day one). The study lists 2 primary outcomes in all. 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 NCT06090383, which also lists 4 linked publications.
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 22 Jun 2025.