Quality of
Principal Investigators: Rory A. Cooper, PhD; Takeo Kanade,
PhD
Co-Investigators: Dan Ding, PhD; Chris Atkeson, PhD; Dan Siewiorek, PhD; Martiel Herbert,
PhD, Katherine Seelman, PhD
2006-2011
Quality of Life Technology Engineering Research
Center Web site: www.QOLT.org
We
envision intelligent systems, ranging from individual devices to comprehensive environments, that will monitor and communicate with a person and
understand his/her needs and task goals. The systems compensate for or
replace diminished capabilities, as required, while adapting to the changing
situation so that tasks are performed safely, reliably and graciously. A
person’s level of function is complex, comprised of multiple determinants that
have effects at many levels and involve various dimensions. These Quality of
Life Technology (QoLT) systems will especially impact
those with partial loss of perception, cognition, and fine and large motor
skills. Examples may include a future wheel chair that functions as a smart personal
mobility and manipulation device.. Knowing the
abilities of the rider, it would provide appropriate types and degrees of
physical, navigational, and cognitive assistance to augment the rider’s own
mobility and manipulation capabilities, rather than being merely a
power-assisted vehicle. A virtual coach would learn and know the
person’s daily activities, family and friends, log his/her experiences, and
relate them to current situations so that it provides reminders for taking
medications, helps to recognize people, and aids communication with other
people through multiple interfaces such as an “e-watch”. An assisted-living
environment, referred to as the “active home,” operating in a skilled care
or nursing home would continuously monitor residents’ activities and behaviors
in order to provide information to staff and reassurance to family. A smart
public transportation system, detecting that a fragile person is near a bus
stop or waiting for Paratransit, would minimize the
time for her to wait in cold weather. Technology research efforts towards the DriveCap system are focused on accurate,
low-cost, real-time measurement of capability metrics. The logical extension is
direct feedback on driver capability. This will allow drivers to better
self-regulate driving behaviors and become aware of shifts in capability. QoLT systems need to work daily in unstructured dynamic
environments. They must work naturally with people; be neither overpowering nor
overwhelming, but rather enable people to do what they want to do whenever and
wherever possible. QoLT systems must be safe and
reliable, and users must be able to trust that their privacy is protected and
modesty respected.