Sensor-based technology offers a potentially cheap, small-scale, unobtrusive, and data rich capture environment. Harnessing data capture whilst children interact seamlessly with play objects and toys, will enable large-scale data insight into the active behaviour of children, allowing clear comparisons with neurotypical groups. Data comparison can be modelled on diagnostic manual descriptions, and would enhance pathology descriptions. Smart systems can provide diagnostic evidence that can be compiled for children with disabilities and be appropriately compared to neuro-typical baseline data. Borderline diagnosis and confusion can be avoided, as collected data can then be used in addition to observable report. This data elicits new information about the way children with Autism and associated developmental disorders interact with their environment on a micro-level. Children with Autism when using smart objects show slow movement, where deceleration during grasping reaching and placing activities takes longer than neurotypical peers, the amplitude of reach speed is at its peak higher than typical peers, maximum acceleration through space is slower, and the time taken to reach speed peak is higher such that speed and accuracy can account for 76% of all variance between children with Autism and typical peers. Children with Autism therefore experience qualitative differences in the way they navigate their own body and interact with objects within their own environment. Stereotyped or repetitive motor movements, hyper- or hypo-reactivity to sensory input, and unusual interests in sensory aspects of objects, remain central to Autism diagnosis. Atypical sensory and physical behaviour is estimated in 92% of children with ASD and 67% of children with SEND equating to one million affected school children. Diagnosis and clinical interaction of children with possible autism currently relies on the use of subjective observational inventories (SOIs) such as ADOS, whilst engaging children in unfamiliar surroundings, against the backdrop of dwindling resources. Autism assessment referrals across KSS have doubled within the last five years. Covid-19 has further delayed pathways. Innovation has not kept pace in assisting clinical teams with low cost, fast and unobtrusive pathways to shorten waiting times. As clinical interactions with younger children nearly always utilise toys to improve engagement, this Smart Toy solution enables automated data capture-otherwise lost-by embedding sensors (e.g. RIFD, IMU Bluetooth) in toys. Accurate data capture during object interaction has potential to significantly reduce assessment time-a recognised problem highlighted in the NHS Long term plan.

"Tangiball" is a new low-cost smart toy that is highly reliable and sensitive that has the potential to significantly reduce the timing of the diagnostic process in young children with possible Autism. The "Tangiball" records user speed and accuracy of movement, which aligns with variability between neuro-typical children and children with Autism. The present exploratory group intervention study (intervention, interview, focus group, and questionnaire) will map out and investigate clinical interaction through the use of sensors that can tell the investigators how children are interacting with objects, and how this diverges from neurotypical children. The project aims to establish the "Tangiball" as an acceptable tool for clinical staff, children, and parents during clinical interaction; that clinical interaction with a Smart Toy enables useful data to be gathered that can support the diagnostic process in young children. With few smart devices embedded into everyday clinical practice this project completes and trials an Internet of Medical Things Smart Toy for use in child development clinics, to capture child interaction with objects and assist in profiling. This can help determine appropriate pathways to care. Thirty children (n=15 with a formal diagnosis of Autism Spectrum Disorder, n=15 neurotypical children with no prior referral to a child development clinic), aged 2-5 years will be recruited over a period of 11 months via clinical teams and through schools. The intervention will run either in clinic or in children's homes. Children will play with the Smart Toy system during a 20 minute session. Children will be matched according to age, and score on the four-strand "Hands-On" assessment tool. Parents and children will complete a User Experience Questionnaire \[UE-Q\] which assesses user acceptability and experience of the Smart Toy. Sessions will be recorded using an SD card within the Smart Toy which records information on user speed and accuracy of placement of the detachable segments of the toy when placed into the main hub of the toy. Ten clinicians (comprising SALTs, Psychologists and Paediatricians) will be interviewed to explore themes around smart toy use and acceptability. Data produced will explore the acceptability and optimisation of triage using a novel, low-cost device that is highly reliable and sensitive, including physical and behaviour profiling to increase timely accurate identification of strengths and weaknesses in children in the early school-age, and pre-school population (2 to 5 years) where there is a current pressure on identification.