ACCESS: An Adaptive Contactless Capacitive Electrostatic Sensing System
10:30-12:30 Thursday, 13 July 2017, ITE 325, UMBC
Technological miniaturization and low-power systems have precipitated an explosive growth in capability and adoption of wearable sensors. These kinds of sensors can be applied to many medical and rehabilitative applications, including as an assistive interface. The overarching theme of this thesis is the development of fabric capacitor sensor arrays as a holistic, wearable, touchless sensing solution. These fabric sensors are lightweight, flexible, and can therefore be integrated into items of everyday use. Further, the capacitive sensing hardware is low-power, unobtrusive, and maintainable.
Additionally, gesture-recognition is expanded in this work to touchless capacitor sensor arrays through the ideation, development, and evaluation of an adaptive signal processing algorithm. The algorithm comprises a hierarchy of data reduction techniques that enable real-time processing on a low-power embedded microcontroller. Using a set of adaptive techniques, the system allows for recognition of gestures of different sizes and rotations as well as gestures with noisy or jittery motions. These adaptations enable a set of mobility that encompasses a large portion of people with upper extremity mobility impairments.
The system is developed as an assistive device, with application to environmental control as a Smart-Home controller.The research is conducted with advisement from medical professionals and private consultants, and evaluated in clinical trials by individuals with upper-extremity mobility impairment.
Committee: Drs. Nilanjan Banerjee (Chair), Ryan Robucci (Co-Chair), Chintan Patel, Sandy McCombe-Waller (University of Maryland Medical School), Susan Fager (Madonna Rehabilitation Hospital)