A 2-D motion detection model for low-cost embedded reconfigurable I/O devices.

Area of Science:

• Engineering
• Computer Science
• Biomedical Engineering

Background:

• Developing accessible assistive technologies is crucial for individuals with kinetic challenges.
• Existing motion detection systems can be costly and lack adaptability.
• Embedded systems offer potential for low-cost, specialized hardware solutions.

Purpose of the Study:

• To develop a low-cost, reconfigurable embedded apparatus for two-dimensional (2-D) motion detection.
• To create a system adaptable to the specific needs of kinetically challenged individuals.
• To demonstrate the system's capability in detecting complex motions and its application in text processing.

Main Methods:

• Direct mapping of a 2-D motion detection model to reconfigurable hardware.
• Implementation of adjustable detection thresholds and delays for user-specific adaptation.
• Development of a motion detection model utilizing a vocabulary of simple motions.
• System training protocols tailored to individual user requirements.

Main Results:

• Successful development of an efficient, low-cost, reconfigurable hardware implementation for 2-D motion detection.
• Demonstrated ability of the hardware to adapt to individual user needs by altering detection parameters.
• Validation of the model's capability to detect complex motions through a combination of simple motions.
• Presentation of experimental results and integrated applications, including text processing.

Conclusions:

• The developed reconfigurable embedded apparatus provides an effective and affordable solution for 2-D motion detection.
• The system's adaptability makes it particularly beneficial for individuals with kinetic challenges.
• The model's approach to complex motion detection and user-specific training shows promise for broader applications.