Actigraphy features for predicting mobility disability in older adults

Physiological Measurement

Volumn 37, Issue 10, 2016, Pages 1813-1833

  Kheirkhahan, Matin ^a,m   Tudor Locke, Catrine ^b   Axtell, Robert ^c   Buman, Matthew P ^d   Fielding, Roger A ^e   Glynn, Nancy W ^f   Guralnik, Jack M ^g   King, Abby C ^h   White, Daniel K ⁱ   Miller, Michael E ^j   Siddique, Juned ^k   Brubaker, Peter ^l   Rejeski, W Jack ^l   Ranshous, Stephen ^m   Pahor, Marco ^a   Ranka, Sanjay ^m   Manini, Todd M ^a  

^a UNIVERSITY OF FLORIDA   (United States)

^b UNIVERSITY OF MASSACHUSETTS   (United States)

^c SOUTHERN CONNECTICUT STATE UNIVERSITY   (United States)

^d ARIZONA STATE UNIVERSITY   (United States)

^e TUFTS UNIVERSITY   (United States)

^f UNIVERSITY OF PITTSBURGH GRADUATE SCHOOL OF PUBLIC HEALTH   (United States)

^g UNIVERSITY OF MARYLAND SCHOOL OF MEDICINE   (United States)

^h STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

ⁱ BOSTON UNIVERSITY   (United States)

^j WAKE FOREST SCHOOL OF MEDICINE   (United States)

^k NORTHWESTERN UNIVERSITY   (United States)

^l WAKE FOREST UNIVERSITY   (United States)

^m University of Florida   (United States)

more..

Author keywords

aging; data mining; disability; machine learning; physical activity; sedentary

Indexed keywords

ACCELEROMETERS; ARTIFICIAL INTELLIGENCE; DATA MINING; FEATURE EXTRACTION; LEARNING SYSTEMS; MEAN SQUARE ERROR; PATIENT MONITORING; WALKING AIDS;

ACTIGRAPHY; ANALYSIS PROCESS; DISABILITY; FREE LIVINGS; GENERAL MODEL; LIVING CONDITIONS; OLDER ADULTS; PHYSICAL ACTIVITY; SEDENTARY; WALKING SPEED;

FORECASTING;

EID: 84989885275     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/37/10/1813     Document Type: Article

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