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| ID | Type | Description | Link |
|---|---|---|---|
| RC 2024-2026 to E. Biffi | Other Grant/Funding Number | Italian Ministry of Health |
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| Name | Class |
|---|---|
| Politecnico di Milano | OTHER |
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What is the purpose of this study? This study wants to learn how the physiological signals and movement data can help researchers understand and predict how children with neuromotor impairments engage with rehabilitation.
Who can take part? 40 participants between 5 and 17 years old will take part. Half of them will be children with neurotypical development (control). The other half will be children with neuromotor impairments.
What will happen in the study? Children within the control group will take part in 1 rehabilitation session, while those with neuromotor impairments will take part in 2 to 3 rehabilitation sessions as part of the treatment plan already provided by their referring physicians.
During each session, researchers will collect: (i) physiological signals like heart activity (ECG), heart rate variability (HRV), and electrodermal activity (EDA); (ii) movement data; (iii) exergames scores and motor performance data; (iv) questionnaires filled out by therapists to understand how engaged the participant is.
Children will use one of two technology-assisted rehabilitation systems during their sessions: either the Lokomat (robotic exoskeleton that supports children with impairments in walking) or the GRAIL system (a treadmill system with motion tracking and extended reality).
Why is this study important? Researchers will use the data to understand and predict how each child responds to therapy and engage with it. These analyses will help therapists adjust rehabilitation settings in real-time, offering more personalized and effective care for children with neuromotor impairments.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Neuromotor impaired |
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| Control |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Inapplicable | Other | Inapplicable |
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| Measure | Description | Time Frame |
|---|---|---|
| Pediatric Rehabilitation Intervention Measure of Engagement - Observation (PRIME-O) | This validated self-reported questionnaire is intended to capture observable indicators of patient and therapist engagement in therapy sessions. It is composed of 10 items, divided into 3 sections. Section A (4 items) groups items exclusively related to the patient engagement evaluation, Section B (4 items) lists items exclusively devoted to therapists, Section C (2 items) contains items that evaluate the interaction between patient and therapist. Each item is proposed on a 5-points Likert scale, with minimum value 0 and maximum value 4. Higher values stand for higher engagement levels. | Baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Service Provider-Rated Measure of Client Engagement (PRIME-SP) | This measure is intended to capture the therapist's observation of patient engagement. PRIME-SP is a validated self-reported questionnaire that is composed of three main parts: Part A, where the therapist can perform an overall evaluation of patient engagement according to a 5-point Likert scale (from 0 to 4, with higher values corresponding to positive engagement); Part B, where the therapist can perform a domain-dependent (affective, cognitive, behavioral domains) evaluation of patient engagement according to a 5-point Likert scale (from 0 to 4, with higher values corresponding to positive engagement); Part C, where the therapist can take free notes about factors and circumstances that he/she believes may have affected patient engagement in the session. |
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Inclusion Criteria:
Exclusion Criteria:
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Potentially eligible participants will be selected from clinical databases of IRCCS Medea.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Scientific Institute IRCCS E.Medea | Bosisio Parini | LC | 23842 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39702317 | Background | Costantini S, Falivene A, Chiappini M, Malerba G, Dei C, Bellazzecca S, Storm FA, Andreoni G, Ambrosini E, Biffi E. Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation. J Neuroeng Rehabil. 2024 Dec 19;21(1):215. doi: 10.1186/s12984-024-01519-2. | |
| 21674389 | Background |
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The results obtained at the end of this clinical trial will be presented at national and international conferences and submitted to peer-reviewed international journals. The raw data of the study will be published among the supplementary materials of scientific articles and/or uploaded to Zenodo, a multidisciplinary repository, managed by CERN in Geneva, which allows researchers to share and preserve research results in any size and form. Depositing data in ZENODO guarantees their compliance with the FAIR principles.
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| Baseline |
| Self-Assessment Manikin (SAM) | The Self-Assessment Manikin is a self-reported questionnaire that evaluates the emotional valence, arousal, and dominance of the subject in relation to a specific context. It is composed of 3 items, namely valence, arousal, and dominance, to which the therapist has to answer according to its feelings regarding the participant's emotional state. Each item is measured through a 9-point Likert scale, from 1 to 9, where:
| Baseline |
| Positive Affect and Negative Affect Scale (PANAS) | PANAS is a self-reported questionnaire that is used to assess the positive and negative affective states. It is composed of two distinct scales: Positive Affect (PA) and Negative Affect (NA), with 20 items in total. Each item is structured with a 5-point Likert scale, from 1 to 5. The items are the following: interested, distressed, excited, upset, strong, guilty, scared, hostile, enthusiastic, proud, irritable, alert, ashamed, inspired, nervous, determined, attentive, jittery, active, and afraid. For each item, higher values on the Likert scale represent higher agreement with that specific word describing different feelings and emotions. Higer values for the items interested, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive, active represent higher levels of affective engagement; conversely, higher values for the items distressed, upset, guilty, scared, hostile, irritable, ashamed, nervous, jittery, afraid represent lower levels of affective engagement. | Baseline |
| Heart Rate (HR) | It measures the number of heartbeats per minute. It is computed as the average number of R-peaks that occur within a minute. A moderately elevated HR may indicate physical or emotional engagement. Extremely high or low values might reflect discomfort or disengagement. A slightly increased HR, compared to rest condition, is generally interpreted as a positive sign of engagement during active tasks. | Baseline |
| Root Mean Square of Successive Differences (RMSSD) | RMSSD is a measure of heart rate variability (HRV) that reflects short-term variations in the time between heartbeats. It is calculated as the square root of the mean squared differences between successive RR intervals (e.g., intervals between successive R-peaks). RMSSD is commonly associated with parasympathetic (rest-and-digest) activity. Higher RMSSD values are typically interpreted as positive, as they indicate a more regulated autonomic state and lower distress, potentially supporting better engagement. | Baseline |
| Low Frequency power of Heart Rate Variability (HRV LF) | HRV LF refers to the power of HRV in the low frequency range (typically 0.04-0.15 Hz). It is calculated using spectral analysis of RR intervals. Moderate LF values with respect to rest condition may suggest adaptive physiological arousal, but excessively high LF can reflect distress or discomfort. | Baseline |
| High Frequency power of Heart Rate Variability (HRV HF) | HRV HF is the high-frequency component of HRV (0.15-0.4 Hz), associated with parasympathetic nervous system activity and respiratory influences. It is calculated using spectral analysis of RR intervals. In the context of rehabilitation, higher HF values typically indicate calm, focused engagement and are thus seen as positive when participants are actively involved without distress. | Baseline |
| Average Skin Conductance Level (AvSCL) | AvSCL is the average level of the tonic (slow-changing) component of skin conductance over time. It reflects general autonomic arousal. It is calculated from electrodermal activity (EDA) after separating the tonic and phasic components as the mean value over time of the tonic component. Moderately higher AvSCL values suggest increased physiological arousal, which is typically positive if not excessive, as it indicates increased engagement into therapy. | Baseline |
| Non-Specific Skin Conductance Responses (NSSCR) | NSSCR represents the frequency of phasic skin conductance responses (rapid changes of skin conductance level, SCR) per minute. It is calculated by counting the number of over-threshold SCR peaks. A higher NSSCR generally indicates greater arousal and cognitive engagement and is considered a positive marker when aligned with task demands. | Baseline |
| Low Frequency power of Skin Conductance Response (SCR LF) | SCR LF measures the power of the skin conductance phasic signal in the low frequency band (0.045-0.15 Hz), focusing on slow oscillations in the phasic component. It is obtained using spectral analysis after SCR decomposition. An increased SCR LF may indicate sustained physiological activation and is generally interpreted as a positive indicator of cognitive and emotional engagement. | Baseline |
| Walk Cadence | Walk Cadence is the number of steps a person takes per minute. It is calculated using inertial sensors placed on L5. Higher cadence typically reflects greater motor activation and is considered a positive outcome, especially when aligned with therapeutic goals. | Baseline |
| Step Time | Step time is the average time taken to complete one step. It is calculated as the time between heel strikes of alternating feet. Lower step times (faster stepping) can reflect better motor coordination and task engagement. A decrease in step time, if associated with smooth and safe gait, is considered a positive sign of engagement and motor activation. | Baseline |
| Exergame score | The exergame score represents the participant's performance level in gamified motor rehabilitation exercises. It is calculated from metrics such as task accuracy, reaction time, and completion rate, depending on the game design. Higher scores generally indicate better motor performance and sustained attention and are also interpreted as a positive measure of both physical and cognitive engagement during the session. A unique normalized scale across different exergames is not available. | Baseline |
| Koenig A, Omlin X, Zimmerli L, Sapa M, Krewer C, Bolliger M, Muller F, Riener R. Psychological state estimation from physiological recordings during robot-assisted gait rehabilitation. J Rehabil Res Dev. 2011;48(4):367-85. doi: 10.1682/jrrd.2010.03.0044. |
| 29149163 | Background | Graffigna G, Barello S, Riva G, Castelnuovo G, Corbo M, Coppola L, Daverio G, Fauci A, Iannone P, Ricciardi W, Bosio AC; CCIPE Working Group. [Recommandation for patient engagement promotion in care and cure for chronic conditions.]. Recenti Prog Med. 2017 Nov;108(11):455-475. doi: 10.1701/2812.28441. Italian. |
| 31700676 | Background | Flynn R, Walton S, Scott SD. Engaging children and families in pediatric Health Research: a scoping review. Res Involv Engagem. 2019 Nov 4;5:32. doi: 10.1186/s40900-019-0168-9. eCollection 2019. |
| 31163093 | Background | Bray L, Appleton V, Sharpe A. The information needs of children having clinical procedures in hospital: Will it hurt? Will I feel scared? What can I do to stay calm? Child Care Health Dev. 2019 Sep;45(5):737-743. doi: 10.1111/cch.12692. Epub 2019 Jul 18. |