A prototype for the first 3D-printed, sensor-operated prosthetic arm for toddlers has been developed by engineers at the University of Lincoln.
The next stage of the project is to test the prototype design on toddlers.
The lightweight device designed for toddlers under two-years-old has soft grip fingers. It uses an armband fitted with sensors to detect electrical signals naturally conducted by muscles.
This enables the toddler to grip and pick up objects in much the same way as they would with a natural arm.
SIMPA Toddler Prosthetic Arm. Photo: University of Lincoln
Muscle-stimulated prostheses are routinely used by adults. This new device is the first of its kind to translate the same technology into dimensions suitable for a toddler.
Producing prosthesis for children under two can be expensive and has also been considered as problematic as a child’s fast growth rates mean the devices would need to be frequently replaced.
The 3D printing element of the new small device is more cost effective as the SIMPA (Soft-Grasp Infant Myoelectric Prosthetic Arm) is cheaper to produce than conventional prosthesis. It can also be custom made to the individual child’s required size without the need for traditional plaster casting techniques.
The early fitting of a functional myoelectric device has also been shown to reduce the risk of the high rejection rates seen with existing prosthetics for children.
Dr Khaled Goher, Senior Lecturer in the School of Engineering at the University of Lincoln and the lead engineer on the project, said: “Many traditional active prosthetics are unsuitable for toddlers as they are very time consuming to construct and heavy.
“Our proposed system would utilise a seven-channel paediatric armband with motion sensors allowing infants to benefit from and become familiar with active prosthetics, with evidence showing that the earlier the exposure, the more likely for the prosthetics to be accepted and used throughout life.
“So far, the device has been tested for grasp force and effectiveness using a range of everyday objects including toys, bottles and building blocks but the next stage of the project is to test the prototype design on toddlers.
Dr Goher added: “We are planning to use algorithm training which would utilise games to engage with the toddlers and attune the system to the ‘grab’ signals from the armband.”
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