Technology and Aging: Ubiquitous Sensing Technology for Aging Research

Advances in Information and Communication Technologies (ICT) are impacting aging research in multiple ways, ranging from analyzing large volumes of data from longitudinal studies to assessing the efficacy of assistive robots. This chapter focuses on using ubiquitous technologies for gathering behavioral data from individuals to understand how we age, assess the effectiveness of interventions, perform early diagnosis of diseases, or monitor disease progression. The ubiquity of inexpensive sensors, most notably in mobile and wearable devices, and advances in pattern recognition algorithms capable of reliably inferring activities and behavior is providing a new and powerful tool for aging research. We describe how these technologies can be used to monitor clinical variables and health outcomes in interventions for aging and illustrate their use with case studies on assessing frailty, inferring anxiety in caregivers of people with dementia and monitoring eating behaviors. We conclude by discussing some of the issues facing research in this area regarding data quality and privacy.

[1]  Jessica Beltrán-Márquez,et al.  Detecting Disruptive Vocalizations for Ambient Assisted Interventions for Dementia , 2014, IWAAL.

[2]  Ware J.E.Jr.,et al.  THE MOS 36- ITEM SHORT FORM HEALTH SURVEY (SF- 36) CONCEPTUAL FRAMEWORK AND ITEM SELECTION , 1992 .

[3]  S. Katz,et al.  STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. , 1963, JAMA.

[4]  Daniel Gatica-Perez,et al.  StressSense: detecting stress in unconstrained acoustic environments using smartphones , 2012, UbiComp.

[5]  S. Iliffe,et al.  Frailty in elderly people , 2013, The Lancet.

[6]  Denzil Ferreira,et al.  AWARE: Mobile Context Instrumentation Framework , 2015, Front. ICT.

[7]  C. Sherbourne,et al.  The MOS 36-Item Short-Form Health Survey (SF-36) , 1992 .

[8]  B. L. Beattie,et al.  Frailty in elderly people: an evolving concept. , 1994, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[9]  Luís A. Castro,et al.  Monitoring Eating Behaviors for a Nutritionist E-Assistant Using Crowdsourcing , 2018, Computer.

[10]  E. H. Goulding,et al.  Cellular Telephones Measure Activity and Lifespace in Community‐Dwelling Adults: Proof of Principle , 2011, Journal of the American Geriatrics Society.

[11]  Eric C. Larson,et al.  Accurate and privacy preserving cough sensing using a low-cost microphone , 2011, UbiComp '11.

[12]  L. Fried,et al.  Frailty in older adults: evidence for a phenotype. , 2001, The journals of gerontology. Series A, Biological sciences and medical sciences.

[13]  Luís A. Castro,et al.  Behavioral data gathering for assessing functional status and health in older adults using mobile phones , 2014, Personal and Ubiquitous Computing.

[14]  Jesús Favela,et al.  Detecting Anxiety States when Caring for People with Dementia , 2016, Methods of Information in Medicine.

[15]  Alex Pentland,et al.  Modeling the co-evolution of behaviors and social relationships using mobile phone data , 2011, MUM.

[16]  Jesús Favela,et al.  Naturalistic Enactment to Elicit and Recognize Caregiver State Anxiety , 2016, Journal of Medical Systems.