Evidence map›Paper›PMID 41613408›Full record

ArticleElectronics2014

SmartStep: A Fully Integrated, Low-Power Insole Monitor.

Nagaraj Hegde, Edward Sazonov

Abstract read
In one paragraph

Article in Electronics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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.

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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Nagaraj HegdeDepartment of Electrical and Computer Engineering, the University of Alabama, 342 HM Comer, Tuscaloosa, AL 35487, USA.
Edward SazonovDepartment of Electrical and Computer Engineering, the University of Alabama, 342 HM Comer, Tuscaloosa, AL 35487, USA.

Funding

Longitudinal Assessment of Fall RiskR21EB013183 · NIBIB · UNIVERSITY OF ALABAMA IN TUSCALOOSA · PI SAZONOV, EDWARD S · 2011 to 2012
$414k
NIBIB NIH HHS R21 EB013183
6 · The paper itself

Abstract

Shoe-mounted wearable sensors can be used in applications, such as activity monitoring, gait analysis, post-stroke rehabilitation, body weight measurements and energy expenditure studies. Such wearable sensors typically require the modification or alteration of the shoe, which is not typically feasible for large populations without the direct involvement of shoe manufacturers. This article presents an insole-based wearable sensor (SmartStep) that has its electronics fully embedded into a generic insole, which is usable with a large variety of shoes and, thus, resolves the need for shoe modification. The SmartStep is an always-on electronic device that comprises a 3D accelerometer, a 3D gyroscope and resistive pressure sensors implemented around a CC2540 system-on-chip with an 8051 processor core, Bluetooth low energy (BLE) connectivity and flash memory buffer. The SmartStep is wirelessly interfaced to an Android smart phone application with data logging and visualization capabilities. This article focuses on low-power implementation methods and on the method developed for reliable data buffering, alleviating intermittent connectivity resulting from the user leaving the vicinity of the smart phone. The conducted tests illustrate the power consumption for several possible usage scenarios and the reliability of the data retention method. The trade-off between the power consumption and supported functionality is discussed, demonstrating that SmartStep can be worn for more than two days between battery recharges. The results of the mechanical reliability test on the SmartStep indicate that the pressure sensors in the SmartStep tolerated prolonged human wear. The SmartStep system collected more than 98.5% of the sensor data, in real usage scenarios, having intermittent connectivity with the smart phone.

Indexed as

AndroidBluetooth low energyflash memory managementlow-power systemssensors

Identifiers

PMID41613408
PMCPMC12851568

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.