Cargando…
USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS
It is desirable to assess older adults’ health status from their routine activities, identify tipping points based on quantitative metrics, and evaluate the potential risks. Such assessments based on infrequently measured, traditional physical performance instruments fall short of sensitivity as wel...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6841103/ http://dx.doi.org/10.1093/geroni/igz038.2220 |
_version_ | 1783467803572961280 |
---|---|
author | Liu, Jian Heasley, Beverly Crist, Janice D Shea, kimberly D Plank, Lorraine M Martin Phillips, Linda R Peterson, Rachel L |
author_facet | Liu, Jian Heasley, Beverly Crist, Janice D Shea, kimberly D Plank, Lorraine M Martin Phillips, Linda R Peterson, Rachel L |
author_sort | Liu, Jian |
collection | PubMed |
description | It is desirable to assess older adults’ health status from their routine activities, identify tipping points based on quantitative metrics, and evaluate the potential risks. Such assessments based on infrequently measured, traditional physical performance instruments fall short of sensitivity as well as reliability. In this research, we investigate multiple types of data collected continuously from older adults wearing fitness watches, which are equipped with various wearable wireless sensors. We develop a methodology to fuse the information from multivariate data streams and define a new synthesized metric to detect significant physiological transitions that lead to tipping points. Both sensitivity- and robustness-analysis are conducted to evaluate the risks of miss-detection and false alarm. The detection results are cross-validated by the self-reported data from daily diaries and questionnaires. |
format | Online Article Text |
id | pubmed-6841103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68411032019-11-15 USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS Liu, Jian Heasley, Beverly Crist, Janice D Shea, kimberly D Plank, Lorraine M Martin Phillips, Linda R Peterson, Rachel L Innov Aging Session 3120 (Symposium) It is desirable to assess older adults’ health status from their routine activities, identify tipping points based on quantitative metrics, and evaluate the potential risks. Such assessments based on infrequently measured, traditional physical performance instruments fall short of sensitivity as well as reliability. In this research, we investigate multiple types of data collected continuously from older adults wearing fitness watches, which are equipped with various wearable wireless sensors. We develop a methodology to fuse the information from multivariate data streams and define a new synthesized metric to detect significant physiological transitions that lead to tipping points. Both sensitivity- and robustness-analysis are conducted to evaluate the risks of miss-detection and false alarm. The detection results are cross-validated by the self-reported data from daily diaries and questionnaires. Oxford University Press 2019-11-08 /pmc/articles/PMC6841103/ http://dx.doi.org/10.1093/geroni/igz038.2220 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Session 3120 (Symposium) Liu, Jian Heasley, Beverly Crist, Janice D Shea, kimberly D Plank, Lorraine M Martin Phillips, Linda R Peterson, Rachel L USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS |
title | USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS |
title_full | USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS |
title_fullStr | USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS |
title_full_unstemmed | USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS |
title_short | USING HEALTH INFORMATION FROM AFFORDABLE WEARABLE DEVICES FOR PREDICTING IMPENDING TIPPING POINTS |
title_sort | using health information from affordable wearable devices for predicting impending tipping points |
topic | Session 3120 (Symposium) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6841103/ http://dx.doi.org/10.1093/geroni/igz038.2220 |
work_keys_str_mv | AT liujian usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints AT heasleybeverly usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints AT cristjaniced usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints AT sheakimberlyd usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints AT planklorrainemmartin usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints AT phillipslindar usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints AT petersonrachell usinghealthinformationfromaffordablewearabledevicesforpredictingimpendingtippingpoints |