LabVIEW Student Design Competition
Smart Glove for First Responder Communication
University: Boston University
Team Member(s): Luke Anderson, Anna Evans, Patrick Henson, Jonathan Kwan, Angelo Luo
Faculty Advisors: Mark Horenstein, Babak Kia, Alan Pisano
Email Address: lukea@bu.edu, anevans@bu.edu, phenson@bu.edu, jkwan@bu.edu, aylou@bu.edu
Title: Smart Glove for First Responder Communication - GloveSense
Description:
A strong need exists for a non-verbal gesture device for use by military and emergency personnel. A lack of a reliable communication system places these workers in unnecessary danger. Our device, GloveSense, provides a communication system that is not reliant on visual or audio paths. The goal was to create an electronic communication system, through the use of hand signals, to silently transmit signals over mid-range distances, such as inside buildings and through walls.
Products:
The Challenge:
Our project was to create a device capable of recognizing and wirelessly transmitting hand gestures, using National Instruments provided hardware and software. The device had several main requirements in its design: capablility of detecting fine movement, an ergonomic design, a defined library of gestures, directed transmission, and a large transmission range.
The Solution:
Our project was divided into two main parts: a glove tied to the Data Acquisition Board, and a glove utilizing the LabVIEW Embedded Module. The first design was a proof of concept utilizing a glove connected directly to a PC. Upon completion, we received a Luminary Micro Evaluation Board and the LabVIEW Embedded Module. The board was attached to a supplementary board of our design to facilitate reading in data, powering auxiliary components, and utilizing a vibration motor to alert users of new messages. The software separates fingerand hand motion into two different algorithms. Measurements of finger positions are quantized and compared to a pre-computed library of gestures. The most likely gestures from this comparison are then compared in their motion components. Each axis of motion is compared using the cross correlation algorithm and the most likely gesture is returned. The gesture name is sent over the ZigBee protocol to the recipient selected.
Features:
The LabVIEW environment was helpful in its prebuilt utilities. The prototype stage was made much with the use of prebuilt modules. For example, the cross correlation module was already implemented in LabVIEW and did not need to be written. LabVIEW also helped to abstract the software away from the constraints of the hardware. In changing to a different microprocessor, only the hardware I/O connections would need to be rewired. This convenience made serial communication with the ZigBee modulestrivial, as the software simply supplied a port number to the Serial I/O modules.
Media:
BU ECE Day Presentation
GloveSense Demonstration Video

LabVIEW VI Hierarchy
Hey there,
Thank you so much for your project submission into the NI LabVIEW Student Design Competition. It's great to see your enthusiasm for NI LabVIEW! Make sure you share your project URL (https://decibel.ni.com/content/docs/DOC-16361) with your peers so you can collect votes via "likes" for your project and win. Collecting the most "likes" gives you the opportunity to win cash prizes for your project submission. I'm curious to know, what's your favorite part about using LabVIEW and how did you hear about the competition?
Good Luck, Liz in Austin, TX.
Hello Liz,
I think our teams favorite part about LabVIEW are all the available libraries. These prebuilt VIs saved the team a lot of time by allowing us to focus on the actual problem being investigated. A quick scaffolding of an idea can be created in LabVIEW with relative ease due to this characteristic of the software. The team was notified of the competition through our NI contact, Lesley Yu. Thank you for the opportunity to work with National Instruments and we look forward to the competition.
Thanks
-Team GloveSense