Evidence map›Paper›PMID 27170900›Full record

ArticleIEEE journal of translational engineering in health and medicine2015

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

Marjorie Skubic, Rainer Dane Guevara, Marilyn Rantz

Registry-linked trialAbstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05379504 (Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology), which is not on this map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05379504 nacompletednot on this mapstarted 2022, after this paper: background citation

Reducing COVID-19 Related Disability in Rural Community-Dwelling Older Adults Using Smart Technology

TypeinterventionalSponsorUniversity of Missouri-ColumbiaRan2022 to 2024Enrolled58ConditionsQuality of Life, Disabilities MultipleArmsStandard Health Education, Self Management
3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing.Journal of the American Medical Directors Association · 2017
    Trial
  4. Article
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  8. An Algorithm for Activity Recognition and Assessment of Adults Poststroke.The American journal of occupational therapy : official publication of the American Occupational Therapy Association · 2024
    Article
  9. Article
  10. Piloting Smart Home Sensors to Detect Overnight Respiratory and Withdrawal Symptoms in Adults Prescribed Opioids.Pain management nursing : official journal of the American Society of Pain Management Nurses · 2023
    Article
  11. Article
  12. Article
  13. Family informatics.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Marjorie Skubic
Rainer Dane Guevara
Marilyn Rantz

Funding

Intelligent Sensor System for Early Illness Alerts in Senior HousingR01NR014255 · NINR · UNIVERSITY OF MISSOURI-COLUMBIA · PI RANTZ, MARILYN J · 2013 to 2015
$1.7M
Technology to Automatically Detect Early Signs of Illness in Senior HousingR21NR011197 · NINR · UNIVERSITY OF MISSOURI-COLUMBIA · PI RANTZ, MARILYN J · 2009 to 2010
$405k
NINR NIH HHS R01 NR014255NINR NIH HHS R21 NR011197
6 · The paper itself

Abstract

We present an example of unobtrusive, continuous monitoring in the home for the purpose of assessing early health changes. Sensors embedded in the environment capture behavior and activity patterns. Changes in patterns are detected as potential signs of changing health. We first present results of a preliminary study investigating 22 features extracted from in-home sensor data. A 1-D alert algorithm was then implemented to generate health alerts to clinicians in a senior housing facility. Clinicians analyze each alert and provide a rating on the clinical relevance. These ratings are then used as ground truth for training and testing classifiers. Here, we present the methodology for four classification approaches that fuse multisensor data. Results are shown using embedded sensor data and health alert ratings collected on 21 seniors over nine months. The best results show similar performance for two techniques, where one approach uses only domain knowledge and the second uses supervised learning for training. Finally, we propose a health change detection model based on these results and clinical expertise. The system of in-home sensors and algorithms for automated health alerts provides a method for detecting health problems very early so that early treatment is possible. This method of passive in-home sensing alleviates compliance issues.

Indexed as

Behavioral bio-markerseldercare monitoringhealth alertsin-home sensing

Identifiers

PMID27170900
PMCPMC4848095

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.