Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
Drug Dosing: Geriatric Patients01:15

Drug Dosing: Geriatric Patients

Elderly individuals encompass a diverse population with varying degrees of age-related physiological changes. Defining the elderly presents challenges, as the geriatric population is often arbitrarily categorized as individuals older than 65. However, many individuals in this group lead active and healthy lives, with an increasing number surpassing 85 years and falling into the older elderly category. Physiological changes associated with aging impact performance capacity and homeostatic...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Can Large Language Models Reduce the Cost of Extracting Data from Electronic Health Records for Research?

medRxiv : the preprint server for health sciences·2026
Same author

Longitudinal monitoring of twenty homes reveals spatiotemporal dynamics which require new models of discomfort and thermostat use.

Scientific reports·2026
Same author

The temporal dynamics of the association between daily physical activity and life satisfaction.

Annals of behavioral medicine : a publication of the Society of Behavioral Medicine·2025
Same author

A dynamic Bayesian network approach to modeling engagement and walking behavior: insights from a yearlong micro-randomized trial (<i>Heartsteps II</i>).

Health psychology and behavioral medicine·2025
Same author

Dynamic Modeling and System Identification of User Engagement in mHealth Interventions using a Bayesian Approach for Missing Data Imputation.

Control engineering practice·2025
Same author

Adapting the Technology Acceptance Model to Examine the Use of Information Communication Technologies and Loneliness Among Low-Income, Older Asian Americans: Cross-Sectional Survey Analysis.

JMIR aging·2025

Related Experiment Video

Updated: Jun 18, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

The exploration & forensic analysis of computer usage data in the elderly.

William J Hatt1, Edward A Vanbaak, Holly B Jimison

  • 1Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR 97239-3098, USA. hattb@ohsu.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
Summary

In-home computer monitoring offers cost-effective early detection of cognitive decline in the elderly. This study analyzes computer usage data, removing non-user activity for accurate cognitive ability assessments.

More Related Videos

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
10:13

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

Published on: February 14, 2014

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

Related Experiment Videos

Last Updated: Jun 18, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
10:13

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

Published on: February 14, 2014

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

Area of Science:

  • Gerontology
  • Computer Science
  • Cognitive Science

Background:

  • Early detection of cognitive impairment in the elderly is crucial for timely intervention.
  • In-home computer monitoring presents a potential method for cost-effective cognitive assessment.
  • Existing computer usage data requires validation before clinical application.

Purpose of the Study:

  • To conduct a forensic analysis of computer usage data collected for cognitive decline studies.
  • To identify and remove non-user-generated activities from computer monitoring data.
  • To ensure the reliability of computer usage data for assessing cognitive abilities in the elderly.

Main Methods:

  • Forensic analysis of computer usage logs.
  • Development and application of methods to isolate user-generated activities.
  • Filtering of system processes and automated tasks from raw data.

Main Results:

  • Successfully identified and isolated non-user-generated activities, such as software updates and background processes.
  • Quantified the proportion of non-user-generated data within the collected computer usage logs.
  • Established a refined dataset of user-generated computer activity.

Conclusions:

  • Computer monitoring data requires rigorous pre-processing to exclude non-user activities for accurate cognitive assessment.
  • This forensic approach enhances the validity of using in-home computer monitoring for detecting cognitive impairment.
  • Semi-automated systems analyzing cleaned computer usage data show promise for cost-effective elderly cognitive health monitoring.