Some people who need to access switchable software are unable to use existing switches such as buttons or joysticks but can still make an intentional arm or leg movement.
Handshake is a system that uses a programmable smart-watch to detect intentional limb motion. When this motion is detected, a radio signal is sent to a receiver unit that sends a switch signal to an attached switch-enabled device such as an AAC unit. The receiver unit is built by modifying another off-the-shelf device.
Initial testing took place at a specialist college with the intended user group with encouraging results. Feedback from this testing is being used to improve the system prior to further testing at other specialist colleges.
The sensitivity of the system can be adjusted without having to touch the smart-watch. Having an adjustable sensitivity means that a range of motions can be detected, from faint motion to powerful punching movements.
This project improves on a prototype that was presented at Communication Matters in 2020[1][2]. This prototype was built using the BBC micro:bit[3]. By re-implementing the system using robust off-the-shelf devices we are now in a position to safely introduce the technology to the intended user group for long-term use. Using commercially available devices enables wide-scale uptake of the system.
Details on how to create the system will be made open-source which allows others to replicate the switch at minimal cost.
It is anticipated that different testers may require different algorithms implemented on the smart-watch to enable reliable detection of their own unique motion. As these algorithms are identified and implemented, details will be made open-source to benefit the AAC and research communities.
Ethical approval was obtained from Lancaster University to carry out user-studies for this project.
An unlisted video showing the system can be seen at: https://youtu.be/m8qva4VpN1U
REFERENCES
1. M Oppenheim, 2020, “Using the BBC micro:bit as AAC – Three Solutions”, The Journal of Communication Matters, vol. 34, no. 3, pp. 13-15.
2. M Oppenheim & F McIntyre, F 2020, “HandShake – Using Hand Motion Recognition to Enable Communication”, The Journal of Communication Matters, vol. 34, no. 1, pp. 19-21.
3. M Oppenheim, 2021, “Devices Aid Speech for People with Disabilities”, Circuit Cellar – The Magazine For Computer Applications, vol. 1, no. 372, pp. 30-37. <https://circuitcellar.com/article-materials-and-resources/july-issue-372-circuit-cellar/>
