Autism Spectrum Disorder (ASD
Conditions
Keywords
Autism Spectrum Disorder, ASD, sleep, movement disorders
Brief summary
Children with autism spectrum disorder (ASD) often show motor abnormalities and sleep disturbances that affect behavior, learning, and family quality of life. Emerging technologies such as wearable devices and markerless systems provide accessible tools for gait and sleep assessment, with actigraphy recommended for long-term monitoring in natural settings. Evidence also suggests links between sleep problems and sensory processing differences. This project, aims to integrate these approaches in a clinical-translational framework.
Detailed description
This study aims to better understand how children with autism spectrum disorder (ASD) move and sleep in their everyday lives, and how these aspects may be connected to their overall development and well-being. Children with ASD often experience differences in motor skills, such as walking and coordination, as well as sleep difficulties, which can affect their behavior, learning, and family life. To address these challenges, the study uses innovative and non-invasive technologies, including wearable devices (such as wrist sensors and smart insoles) and video-based systems that can analyze movement without the need for markers or complex laboratory setups. These tools allow researchers to monitor children in more natural environments, such as at home, over several days. The project combines three main components: continuous monitoring of daily activity through wearable sensors, detailed gait analysis in a clinical setting, and sleep evaluation using both wearable devices and home-based sleep recordings. By integrating these data, the study seeks to identify patterns in movement and sleep, and to explore how they relate to sensory processing differences often seen in children with ASD. The ultimate goal is to develop more personalized and accessible approaches to assessment and care, helping clinicians and families better understand each child's needs and support their development through targeted interventions.
Interventions
DEVICEplacement of a wearable wrist sensor
The project integrates three complementary modules on the same participant: (A) monitoring with wearable sensors (primary objective), (B) laboratory-based gait analysis, and (C) sleep assessment using home video-EEG polysomnography (PSG). The reference wearable instrumentation follows the technical protocols established by the Politecnico di Milano, which already include the use of the AX6 device and F-Scan GO insoles among the wearable devices available within the research program.
Sponsors
IRCCS San Raffaele Roma
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Intervention model description
This study examines motor activity and sleep patterns in children and adolescents with autism spectrum disorder (ASD) using a multimodal, non-invasive approach. It includes: (A) continuous monitoring with wearable sensors, (B) laboratory gait analysis, and (C) home video-EEG polysomnography (PSG), with a control group. Participants aged 2-18 years complete a standardized protocol. At baseline, clinical data are collected, wearable devices (AX6 wrist sensor and F-Scan GO insoles) are applied, and gait is assessed using both marker-based and AI markerless systems. Sensory processing is evaluated with the Sensory Profile 2. Over a 7-day home phase, devices record daily activity and sleep-wake patterns. Sleep is also assessed with 1-2 nights of home PSG, allowing comparison with wearable data. At follow-up, devices are returned, data are checked, and caregiver feedback is collected. The study evaluates feasibility and explores links between movement, sleep, and sensory processing.
Eligibility
Sex/Gender
ALL
Age
2 Years to 18 Years
Healthy volunteers
Yes
Inclusion criteria
* Diagnosis of autism spectrum disorder (ASD) according to DSM-5 criteria * Age between 2 and 18 years * Ability to walk independently * Willingness to wear a wearable device (wrist sensor) continuously for 7 days and pedobarographic insoles for reproducible gait monitoring * Willingness to undergo one night of home polysomnography with video-EEG/polygraphy during the wearable monitoring period * Informed consent signed by both parents/legal guardian; assent from the minor when applicable
Exclusion criteria
* Skin contraindications to the wristband/fixation systems (known material allergies, active wrist dermatitis, or skin lesions preventing prolonged use) * Severe motor impairments * Recent orthopedic surgery (\<6 months) * Use of orthoses or assistive devices during walking * Severe behavioral disorder making device use impracticable despite acclimatization strategies
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility and adherence to continuous use of a wearable sensor in children with autism spectrum disorder (ASD) | 7 days | This objective aims to assess the feasibility and adherence to continuous use of a wearable sensor in children with autism spectrum disorder (ASD), evaluating tolerability, compliance, and data quality in real-life conditions over a 7-day monitoring period. Feasibility is primarily defined as the proportion of participants completing the protocol with valid data, while adherence is assessed through wear time, data completeness, and caregiver-reported acceptability. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Gait Pattern | during the enrollment period with wearable sensor | To characterize gait patterns in children and adolescents with autism spectrum disorder |
| ASD subgroups | during the enrollment period using the wearable sensor | To identify potential phenotypic subgroups within the ASD population (e.g., different gait patterns according to age or phenotypic severity) |
| Daily activity and sleep quality | during the enrollment period using a wearable sensor | To investigate the relationship between sleep quality, daily motor activity (daytime activity, fragmentation/variability), and sensory processing. |
Countries
Italy
Outcome results
None listed