Evidence map›Paper›PMID 23762189›Full record

Trial reportComputational and mathematical methods in medicine2013

Mobile personal health system for ambulatory blood pressure monitoring.

Luis J Mena, Vanessa G Felix, Rodolfo Ostos, Jesus A Gonzalez, Armando Cervantes, Armando Ochoa, Carlos Ruiz, Roberto Ramos, Gladys E Maestre

Abstract readClinical Trial
In one paragraph

Trial report in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Data Sources and Gateways: Design and Open Specification.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019
    Article
  7. The CrowdHEALTH project and the Hollistic Health Records: Collective Wisdom Driving Public Health Policies.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019
    Review
  8. Generating and Knowledge Framework: Design and Open Specification.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019
    Article
  9. Interoperability Techniques in CrowdHEALTH project: The Terminology Service.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2019
    Article
  10. "Contemporary clinical trials communications · 2019
    Article
  11. Single-Frequency Ultrasound-Based Respiration Rate Estimation with Smartphones.Computational and mathematical methods in medicine · 2018
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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

9 authors.

Luis J MenaDepartment of Computer Engineering, Polytechnic University of Sinaloa, 82199 Mazatlan, SIN, Mexico. lmena@upsin.edu.mx
Vanessa G Felix
Rodolfo Ostos
Jesus A Gonzalez
Armando Cervantes
Armando Ochoa
Carlos Ruiz
Roberto Ramos
Gladys E Maestre

Funding

Gene-Environment Interactions in Cognition in Venezuelan FamiliesR01AG036469 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CHACON, INARA, MAESTRE, GLADYS E. · 2011 to 2015
$2.7M
NIA NIH HHS R01 AG036469NIA NIH HHS R01AG036469
6 · The paper itself

Abstract

The ARVmobile v1.0 is a multiplatform mobile personal health monitor (PHM) application for ambulatory blood pressure (ABP) monitoring that has the potential to aid in the acquisition and analysis of detailed profile of ABP and heart rate (HR), improve the early detection and intervention of hypertension, and detect potential abnormal BP and HR levels for timely medical feedback. The PHM system consisted of ABP sensor to detect BP and HR signals and smartphone as receiver to collect the transmitted digital data and process them to provide immediate personalized information to the user. Android and Blackberry platforms were developed to detect and alert of potential abnormal values, offer friendly graphical user interface for elderly people, and provide feedback to professional healthcare providers via e-mail. ABP data were obtained from twenty-one healthy individuals (>51 years) to test the utility of the PHM application. The ARVmobile v1.0 was able to reliably receive and process the ABP readings from the volunteers. The preliminary results demonstrate that the ARVmobile 1.0 application could be used to perform a detailed profile of ABP and HR in an ordinary daily life environment, bedsides of estimating potential diagnostic thresholds of abnormal BP variability measured as average real variability.

Indexed as

AgedBlood PressureBlood Pressure Monitoring, AmbulatoryCell PhoneComputational BiologyDiagnosis, Computer-AssistedEquipment DesignFemaleHeart RateHumansMaleMiddle AgedMonitoring, PhysiologicSignal Processing, Computer-AssistedSoftwareTelemedicine

Identifiers

PMID23762189
PMCPMC3665224

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.