- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06947889
Biofeedback Based System to Enhance Robotic Assisted Gait Training in Children With Cerebral Palsy (AID2GAIT)
AID2GAIT: Biofeedback Based System to Enhance Robotic Assisted Gait Training in Children With Cerebral Palsy
The AID2GAIT project aims to develop a biofeedback system with the aim of improving the outcomes of robot-assisted gait training (RAGT) in pediatric patients with cerebral palsy. The physiological signals of children during RAGT therapy sessions, acquired through non-invasive technologies, will be analyzed. These technologies specifically are:
- wearable technology (smartwatch), from which the HRV (Heart Rate Variability) signal will be measured;
- infrared thermography, from which the temperature in salient facial regions will be obtained;
- fNIRS (functional near-infrared spectroscopy), from which information on brain activity and its changes over time will be obtained.
Information on the kinematics of the exoskeleton used during RAGT will be extracted.
The RAGT will be performed using the Lokomat orthosis (Hocoma), the most widely used exoskeleton in rehabilitation that facilitates a bilaterally symmetrical gait, as the individual actively tries to advance each limb during walking, combined with a patented dynamic body weight support system.
Study Overview
Status
Intervention / Treatment
Detailed Description
The entire RAGT treatment will consist of 12 sessions of robotic gait rehabilitation administered over 4 weeks.
The protocol consists of a block paradigm: children will be asked to actively move during the robotic training for the first 30 seconds, followed by a rest period of 30 seconds. The paradigm will be provided in 10 blocks for a total duration of 30 minutes. During each single session, infrared (IR) thermal video, smartwatch signals (HRV- heart rate variability) and the kinematic output of the robot will be recorded. During the first (T1) and the last session of the RAGT (T12), fNIRS will also be recorded together with the assessment of motor skills, revealed by clinical scales. The assessment of fNIRS and clinical scales will be useful to understand the global efficacy of the treatment. Before the start of the experimental trials, parents will be extensively informed about the purpose and protocol of the study and will sign an informed consent form.
For each session, the assessment of the psychophysiological state of the patients will be based on the estimation of the state of physiological parameters, such as heart rate variability (HRV), recorded by a smartwatch and on the assessment of the emotional state of the child by means of an infrared thermal imaging system. The information on the state of the child and the robot will be assessed in real time and will constitute the input data for a machine learning-based model capable of classifying the level of patient engagement. Based on this information, the physiotherapist, who assists the child during the training sessions, will be able to intervene and modify the parameters of the exoskeleton (e.g. push force, body weight support, treadmill speed, range of motion and hip and knee offset). Furthermore, the effectiveness of the entire treatment will be assessed through the administration of clinical tools commonly used in clinical practice and by the assessment of brain activation by means of a non-invasive and portable neuroimaging technique, the fNIRS. These assessments will be conducted by comparing the first and the last training session.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Daniela Cardone, Dr
- Phone Number: +39 085 453 7260
- Email: daniela.cardone@unich.it
Study Contact Backup
- Name: Teresa Paolucci, Prof.
- Phone Number: +3908713551
- Email: teresa.paolucci@unich.it
Study Locations
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FG
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San Giovanni Rotondo, FG, Italy, 71013
- Recruiting
- Fondazione Centri di Riabilitazione Padre Pio Onlus - Gli Angeli di Padre Pio
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Contact:
- Maria T. Gatta, Dr.
- Email: dsangeli@centripadrepio.it
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
Children with cerebral palsy aged 3 to 18 years who have a GMFCS level from I to V, with the ability to express discomfort or pain and understanding simple instructions
Exclusion Criteria:
- Medical problems that could interfere with training and restrictions on the use of the robotic device;
- severe lower limb conditions: muscle contractures, instability or subluxation of the hip;
- recent botulinum toxin A injections to the lower limbs;
- uncontrolled seizures;
- open skin disorders and vascular disorders of the lower limbs.
- Contraindications to gait rehabilitation treatment with Lokomat (e.g. weight <10 kg, non-consolidated fractures, cognitive deficits limiting communication).
- Contractures of fixed joints that limit the range of motion of the orthoses
- Inability to properly adjust the harness and/or orthoses
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Analysis of variations in the motor skills of patients from T0 (1st RAGT) to T2 (12th RAGT), assessed by GMFM88 clinical scale
Time Frame: One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
Assessment by Gross Motor Function Measure (GMFM-88): it measure changes in GMF with intervention through 88 items. The scoring range is from 0 to 3 with higher scores meaning a better outcome. The clinical scale is administered before RAGT#1 (i.e. T0) and after RAGT#12 (i.e. T2). |
One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
|
Analysis of variations in the motor skills of patients from T0 (1st RAGT) to T2 (12th RAGT), assessed by MAS clinical scale
Time Frame: One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
Assessment by Modified Ashworth Scale (MAS): The test is performed by extending the patients limb's first from a position of maximal possible flexion to maximal possible extension. The scoring range is from 0 to 4 with lower scores meaning a better outcome. The clinical scale is administered before RAGT#1 (i.e. T0) and after RAGT#12 (i.e. T2). |
One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
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Analysis of variations in the motor skills of patients from T0 (1st RAGT) to T2 (12th RAGT), assessed by WeeFIM clinical scale
Time Frame: One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
Assessment by Functional Independence Measure for Children (WeeFIM): it measures the need for assistance and the severity of disability. Scores range from 0 to 4, with lower scores indicating higher levels of disability. The clinical scale is administered before RAGT#1 (i.e. T0) and after RAGT#12 (i.e. T2). |
One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
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Analysis of variations in the motor skills of patients from T0 (1st RAGT) to T2 (12th RAGT), assessed by PEDSQL clinical scale
Time Frame: One month (4 weeks) from the beginning of the 1st RAGT (T0)
|
Assessment by Pediatric Quality of Life Inventory (PedsQL): modular approach to measuring health-related quality of life. The items of the four Scales (Physical Functioning, Emotional Functioning, Social Functioning, and School Functioning) are grouped together. The scoring range is from 0 to 4 with lower scores meaning a better outcome. The clinical scale is administered before RAGT#1 (i.e. T0) and after RAGT#12 (i.e. T2). |
One month (4 weeks) from the beginning of the 1st RAGT (T0)
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Measurement of heart rate variability of patients
Time Frame: Two years from the beginning
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During RAGT #1(i.e T0), RAGT#6 (i.e. T1), RAGT#12 (i.e. T2) heart rate variability (HRV) measurement will be performed by a smartwatch. The HRV signal will be monitored and metrics such as mean, standard deviation, root mean square, power spectral density will be extracted in time windows of 30 seconds. The above mentioned parameters are correlated with autonomous nervous system activity and will be used as input data for a AI based model able to classify the patient's engagement level during RAGT. |
Two years from the beginning
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Measurement of fNIRS of patients
Time Frame: Two years from the beginning
|
During RAGT #1(i.e T0), RAGT#6 (i.e. T1), RAGT#12 (i.e. T2) functional near infrared spectroscopy measurement will be performed by a fNIRS cap. fNIRS allows to measure oxy- and deoxyhemoglobin oscillations in the frontal, prefrontal and motor cortex areas. Given the ecological nature of the experiment, a GLM-based algorithm will be applied to automatically identify the onset and duration of cortical activations. The canonical GLM metrics (beta-values and t-statistics) indicative of brain activity will be evaluated in time windows of 30 seconds and averaged across all good channels. The above mentioned parameters are correlated with central nervous system activity and will be used as input data for a AI based model able to classify the patient's engagement level during RAGT and to assess neural plasticity in patients. |
Two years from the beginning
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Measurement of infrared imaging of patients
Time Frame: Two years from the beginning
|
During RAGT #1(i.e T0), RAGT#6 (i.e. T1), RAGT#12 (i.e. T2) infrared imaging (IRI) measurement will be acquired by an infrared camera. The thermal signals in salient areas of the face (nose tip, nostrils, corrugator, chin, and perioral area) will be monitored (tempertures in °C), and metrics such as mean, standard deviation, kurtosis, skewness and LF ([0.04-0.15] Hz), HF ([0.15-0.4] Hz), and LF/HF components will be extracted in time windows of 30 seconds. The above mentioned parameters are correlated with autonomous nervous system activity and will be used as input data for a AI based model able to classify the patient's engagement level during RAGT. |
Two years from the beginning
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Measurement of exoskeleton kinematics
Time Frame: Two years from the beginning
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During RAGT #1(i.e T0), RAGT#6 (i.e. T1), RAGT#12 (i.e. T2) the torques relative to both knees and both hips will be acquired (in Nm). Metrics such as mean, standard deviation will be extracted in time inetrvals of 30 seconds. The above mentioned parameters are correlated with the participation level and with the activity of the patient during RAGT and will be used as input data for a AI based model able to classify the patient's engagement level during RAGT. |
Two years from the beginning
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Daniela Cardone, Dr, G. d'Annunzio University
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- D53D23021770001
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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