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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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CASAS Smart Home dataset - scripted complex activities, activity scores, and cognitive diagnosis

Authors: Cook, Diane;

CASAS Smart Home dataset - scripted complex activities, activity scores, and cognitive diagnosis

Abstract

We hypothesize cognitive impairment can be evident in everyday task performance. We also postulate that differences in task performance can be automatically detected between cognitively healthy individuals and those with dementia and mild cognitive impairment (MCI) using smart home and ubiquitous computing technologies. This dataset contains ambient sensor readings collected in the CASAS smart apartment testbed at Washington State University for 179 participants with corresponding cognitive diagnoses. Data are collected continuously from ambient sensors while participants perform 24 scripted activities. Each sensor reading is reported on a separate line and is described by fields date, time, sensor, and message. The first 8 activities are performed without cues (task step reminders), the second 8 activities are performed with cues when needed, and the last 8 activities, part of a complex day out task, are interwoven in a natural manner without cues. The task list is included in the file activitylist.txt. The file activityscores.txt provides numeric values for activities 1-8 that are based on experimenter assessment of task quality. The file also gives scores for the day out task. Finally, the file diagnosis.txt lists the diagnosis for each participant, coded as the following: 1 = dementia2 = MCI3 = middle age 45-594 = young-old 60-745 = old-old 75+6 = other medical7 = watch/at risk - follow longitudinally8 = younger adult9 = younger adult, English second language10 = diagnosis not available The sensors are categorized (and named) as: M01 - M51: PIR motion detectors (ON when detected motion starts and OFF when it stops) I01 - I10: item use sensors (PRESENT or ABSENT indicating item is on sensor or not) D01 - D019: door sensor on cabinets and doors (OPEN or CLOSE) P001 and P002: current eletricity consumption T001 - T006: ambient temperature sensors BATP and BATV: sensor battery levels The floorplan and sensor layout are provided in the file Chinook.jpg.

Citation: Please cite the following paper when using this dataset:Dawadi, P., Cook, D., & Schmitter-Edgecombe, M. (2013). Automated cognitive health assessment using smart home monitoring of complex tasks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43(6):1302-1313. doi: 10.1109/TSMC.2013.2252338

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average