Children with for example hemiplegic cerebral palsy and spasticity in their hands are encouraged to exercise their hand movements for at least 30 minutes per day. These exercises are both long and often boring. The Magic Monster adds a layer of playfulness, which provides extra motivation to do the exercises every day by encouraging children to do hand exercises while learning to do magic tricks with the monster.
The monster consists of a phone that uses AI algorithms for calibration and self-adaptive play complexity and a cuddle toy that encases the phone.
When the Magic Monster is chosen for therapy, the physiotherapist calibrates the app together with the child and parent. This is done to adjust the toy to the individual skill level of the child. This skill level defines the sensibility of the monster. The better the child’s skills, the lower the sensibility. With a lower sensibility, the monster requires more challenging movements to perform activities. Later, when the child is using the monster at home, the app keeps track of the number of attempts the child performs the movement without success. If the number is too high, the threshold for success will be lowered, and the sensibility will be higher.
Next to automatically updating the sensibility, the monster challenges the child from time to time to increase the difficulty by asking if they want to take it to the next level. The child can decide for themselves whether or not they accept this challenge.
The Magic Monster was designed in an interactive process that included interviews to therapists, workshops with children and user testing with children with and without CP. The final prototype includes two different magic tricks and a booklet with instructions.
This project is a collaboration between knowledge institutions (AUAS, University of Utrecht, Twente University, Eindhoven University of Technology, Roessingh Rehabilitation Centre), designers and developers (Ijsfontein) product and research companies (Phillips).
- Tamara Pinos Cisneros MSc. (UT & AUAS)
- Prof. Dr. Ben Schouten (TU/e & AUAS)
- Kayleigh Schoorl MSc. (UU)
- Prof. Dr. Albert Ali Salah (UU)
- Prof. Dr. Geke Ludden (UT)
- Laura de Ruijter MSc. (Ijsfontein)
- Eddy Klappe (Ijsfontein)
- Stijn Raaijmakers (Ijsfontein)
- Dr. Boris de Ruyter (Phillips)
- Dr. Marc Nederhand (Roessingh)