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A New Paradigm of Technology-Enabled ‘Vital Signs’ for Early Detection of Health Change for Older Adults

A Sinclair School of Nursing, b Electrical and Computer Engineering, c Department of Health Management and Informatics and d Curtis W.

Anatomy of Inpatient Falls: Examining Fall Events Captured by Depth-Sensor Technology

Patient falls remain a significant and persistent health problem, despite years of intensive efforts by hospitals to prevent them. Each year in the United States, between 700,000 and 1,100,000.

Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing

Marilyn Rantz PhD, RN, FAAN a, *, Lorraine J. Phillips RN, PhD, FAAN a , Colleen Galambos PhD, MSW, ACSW, LCSW-C b , Kari Lane RN, PhD a , Gregory L. Alexander RN, PhD, FAAN a , Laurel Despins RN,

Enhanced registered nurse care coordination with sensor technology: Impact on length of stay and cost in aging in place housing

A University of Missouri, School of Social Work, Columbia, Missouri, USA; b University of Missouri Electrical and Computer Engineering Department, Columbia, Missouri, USA; c University of Missouri

Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment

1Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO 65211 USA 2Cerner Corporation, Kansas City, MO 64117 USA 3Sinclair School of Nursing, University of

Evaluation of Sensor Technology to Detect Fall Risk and Prevent Falls in Acute Care

Patricia Potter, RN, PhD; Kelly Allen, BSN, RN, BA; Eileen Costantinou, MSN, RN-BC; William Dean Klinkenberg, PhD; Jill Malen, APRN, BC, MS, NS, ANP; Traci Norris, DPT, GCS; Elizabeth O’Connor,

Management of dementia and depression utilizing in-home passive sensor data