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Is the Wii's Motion Controller Any Good?

By Matt Peckham

PC World

December 9, 2008

Just how good is the Wii's motion controller, really? A group of researchers at Rice University intend to find out. Armed with a National Science Foundation grant, professors Marcia O'Malley and Michael Byrne will spend the next thee years measuring motions as simple as slapping around a paddleball to as sophisticated as maneuvering a fighter jet.

What'll they test against? Something called a Vicon motion capture system. The press release doesn't specify which one, but probably something like the Vicon MX, which uses cameras in conjunction with a controlling hardware module and software to achieve high resolution motion capture. Some perspective: Vicon's been involved in everything from "transforming Ray Winstone in Beowulf, to creating the Transformers, right through to the work on The Golden Compass" according to Nick Bolton, chief executive at Oxford Metrics, of which Vicon is a subsidiary.

Back to the Rice study: "We're already grabbing motion data from the Wiimote," said O'Malley, "so soon we'll be able to measure a range of motion and then turn it into a mathematical model."

That mathematical model will help gauge the effectiveness of robotics to improve motor skills. Say you're having trouble with your golf swing. You could practice until you trial-and-error your way to a solution, or you could just slip on a robotic sleeve that uses comparative performance data to physically notify you where the hitch is in your swing.

Will the Wii's motion controller stand up to the Vicon system? Probably not dollar for dollar, but O'Malley has perfectly understandable reasons for picking Nintendo's multimillions wonder: "Using the Wii will be a great way to recruit subjects," he says. "We can say, 'Hey, kids, come play some games!'"

http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0812569

Award Abstract #0812569
RI-Small: Cognitive Modeling of Human Motor Skill Acquisition

NSF Org:
IIS
Division of Information & Intelligent Systems

Initial Amendment Date:
August 5, 2008

Latest Amendment Date:
August 5, 2008

Award Number:
0812569

Award Instrument:
Continuing grant

Program Manager:
Douglas H. Fisher
IIS Division of Information & Intelligent Systems
CSE Directorate for Computer & Information Science & Engineering

Start Date:
August 1, 2008

Expires:
July 31, 2009 (Estimated)

Awarded Amount to Date:
$112781

Investigator(s):
Marcia O'Malley omalleym@rice.edu (Principal Investigator)
Michael Byrne (Co-Principal Investigator)

Sponsor:
William Marsh Rice University
6100 MAIN ST
HOUSTON, TX 77005 713/348-4820

NSF Program(s):
ROBUST INTELLIGENCE

Field Application(s):
0116000 Human Subjects

Program Reference Code(s):
HPCC, 9215, 7495

Program Element Code(s):
7495

ABSTRACT

Theoretical psychology has not, until recently, been in position to have much to say about how humans learn in dynamic, multidegree-of-freedom manual control domains. While applied concerns have led to successful training programs for manual control tasks (e.g., most people learn to steer automobiles in reasonable time), we currently lack the ability to predict how well people will do in these domains or how rapidly they will learn. This limits our ability to train people in these domains, where we presently rely on expensive one-on-one tutoring or similar intensive methods.

The project studies human performance and acquisition of sensorimotor tasks in real and virtual environments. Human motion data and performance of various skills by high performers and low performers, who exhibit linear performance gains, will be analyzed and compared to data for subjects who rapidly acquire skill and exhibit nonlinear performance gains. This data will inform the development of more accurate models of sensorimotor skill acquisition that can be expressed in ACT-R, and doing this should lead to improved understanding of training methods in human motor learning domains.