TY - JOUR
T1 - Unobtrusive monitoring of computer interactions to detect cognitive status in elders
AU - Jimison, Holly
AU - Pavel, Misha
AU - McKanna, James
AU - Pavel, Jesse
N1 - Funding Information:
Manuscript received December 22, 2003; revised April 5, 2004 and July 7, 2004. This work was supported in part by a grant from the Intel Corporation and in cooperation with Spry Learning, Inc. H. B. Jimison is with the Department of Medical Informatics, Oregon Health and Science University, Portland, OR 97230 USA (e-mail: jimisonh@ohsu.edu). M. Pavel and J. McKanna are with the Biomedical Engineering Department, Oregon Health and Science University, Portland, OR 97239 USA (e-mail: pavel@bme.ogi.edu; jmckanna@bme.ogi.edu). J. Pavel is with Electrika, Inc., Islip Terrace, NY 11752 USA (e-mail: jpavel@alum.mit.edu). Digital Object Identifier 10.1109/TITB.2004.835539
PY - 2004/9
Y1 - 2004/9
N2 - The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.
AB - The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.
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U2 - 10.1109/TITB.2004.835539
DO - 10.1109/TITB.2004.835539
M3 - Article
C2 - 15484429
AN - SCOPUS:4644230001
SN - 2168-2194
VL - 8
SP - 248
EP - 252
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 3
ER -