As mentioned above, the senior project this year is just one of a number of ways in which WSU will help ALS patients. Prof. David Bakken (WSU ’85) will help to start these efforts. He realizes that we need to build up very carefully because if we do it too fast then this could greatly slow down the students’ technological progress and/or take his valuable time which could much more profitably be spent on other ways to benefit WSUTG.
The team is looking for a few computer science students for spring 2014. They would support the team by porting the system to new devices, misc. testing, etc. The team is also looking for a mechanical engineering student or two for hands-on work and learning TBD. Recruiting for this will be done in November.
In the longer term, there will be one or more senior projects in future years helping move this technology forward. We hope to get other departments involved, for example Computer Engineering (digital hardware), Mechanical Engineering (for more analog hardware and devices such as actuators and motors), business (market analysis), and others. As an example, some researchers are tasked with building low-cost smart wheelchairs that can are easy for spinal cord patients to use and can be steered by brain waves only. The researchers are also making wheelchairs much more aware of their surroundings. Such a system could possibly use the eye tracking technology developed by WSU as an alternate to brain waves, or to supplement that interface. Additionally, the technology for making wheelchairs more aware of their environment could very likely benefit a lot from Prof. Cook’s home monitoring technologies (described below), either generically or as they are extended with a profile for ALS patients.
All efforts described here will coordinate closely with Team Gleason, which is headquartered in New Orleans. They are well aware of this project, and the WSU team has already interacted with its chief technologist, ALS patient Eric Valor (who can now only communicate by blinking) via email and videoconference.
A WSU Team Gleason student club will be formed. This will allow students from majors outside of EECS to be involved. But, crucially, it will also allow EECS students to get involved well before their senior year. This will help a lot on development issues, but also provide much more long-term continuity and institutional memory than if the development efforts were a new crop of seniors each year who work for a school year then are done.
Getting WSU club status won’t be possible until August 2014. However, until then the club will - [s1] be hosted in EECS. Governance will be set up for approving purchases from the club’s funds. Until then, all purchases will be approved by both Prof. Bakken and Prof. Arslan Ay.
Caveat: WSUTG can’t start anything on getting this project going until January. It simply has too much to do between then and now. But by early February recruiting will begin in earnest.
All software implementations and hardware designs will be released open source and free for others to use. The team also plans on starting an international open source community around this, most likely starting some time in 2015.
While the technology from WSU will be free, a company may charge for the systems they build with the WSU technology. None of the WSU professors or students plan to make any money off of this, but letting others do so is crucial to enable the technology to be widely available and thus have the broadest possible impact. We also anticipate that systems will be available, especially in the first few years, from Team Gleason, possibly at no charge above the hardware costs (or even free), and/or possibly by other non-profit organizations.
It is also possible that the WSU club would take the lead in distributing the fruits of its labor. This could not begin until about early 2015. It would likely require the hiring of a half-time student at least, and possibly a few full-time workers, funds allowing.
Prof. Diane Cook is a computer scientist whose expertise includes artificial intelligence and machine learning. She heads the CASAS smart home project. CASAS is a world leader in monitoring elderly patients to learn patterns and determine when they need help. This has received huge funding from NIH, NSF, and others, because it can help keep elderly patients out of assisted living for months or even years, which is a huge cost savings. So far the CASAS lab has developed learning profiles for Alzheimers and Parkinsons patients, and it hopes to add ALS patients in the next year or two once a research grant is secured.