An alternative human interface enabling the handicapped with severe motor disabilities to control an assistive system is presented. Since this interface relies on the biosignals originating from the contraction of muscles on the face during particular movements, even individuals with a paralyzed limb can use it with ease. For real-world application, a dedicated hardware module employing a general-purpose DSP was implemented and its validity tested on an electrically powered wheelchair. Furthermore, an additional attempt to reduce error rates to a minimum for stable operation was also made based on the entropy information inherent in the signals during the classification phase. In the experiments in which 11 subjects participated, it was found most of them could control the target system at their own will, and thus the proposed interface could be considered a potential alternative for the interaction of the severely handicapped with electronic systems.

This paper proposes a human interface where a novel input method is used to substitute conventional input devices. It overcomes the deficiencies of physical devices, as it is based on image processing techniques. The proposed interface is composed of three parts: extraction of a person's handshape from a digitized image, detection of its fingertip, and interpretation by a software application. First, images of a pointing hand are digitized to obtain a sequence of monochrome frames. In each frame the hand is isolated from the background by means of gray-level slicing; with threshold values calculated dynamically by the combination of movement detection and histogram analysis. The advantage of this approach is that the system adapts itself to any user and compensates any changes in the illumination, while in conventional methods the threshold values are previously defined or markers have to be attached to the hand in order to give reference points. Second, once the hand is isolated, fingertip coordinates are extracted by scanning the image. Third, the coordinates are inputted to an application interface. Overall, as the algorithms are simple and only monochrome images are used, the amount of processing is kept low, making this system suitable to real-time processing without needing expensive hardware.