Evidence map›Paper›PMID 38676166›Full record

ArticleSensors (Basel, Switzerland)2024

Choice of Piezoelectric Element over Accelerometer for an Energy-Autonomous Shoe-Based System.

Niharika Gogoi, Yuanjia Zhu, Jens Kirchner, Georg Fischer

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 46% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 2 countries.

Niharika GogoiDepartment of Computer Science, Durham University, Upper Mountjoy Campus, Stockton Road, Durham DH13LE, UK.ORCID 0000-0002-6589-0820
Yuanjia ZhuInstitute of Technical Electronics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
Jens KirchnerInstitute of Technical Electronics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.ORCID 0000-0002-8623-9551
Georg FischerInstitute of Technical Electronics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.ORCID 0000-0002-4033-2005
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEDortmund University of Applied Sciences and Arts · DE

Funding

Deutsche Forschungsgemeinschaft grk2495
6 · The paper itself

Abstract

Shoe-based wearable sensor systems are a growing research area in health monitoring, disease diagnosis, rehabilitation, and sports training. These systems-equipped with one or more sensors, either of the same or different types-capture information related to foot movement or pressure maps beneath the foot. This captured information offers an overview of the subject's overall movement, known as the human gait. Beyond sensing, these systems also provide a platform for hosting ambient energy harvesters. They hold the potential to harvest energy from foot movements and operate related low-power devices sustainably. This article proposes two types of strategies (Strategy 1 and Strategy 2) for an energy-autonomous shoe-based system. Strategy 1 uses an accelerometer as a sensor for gait acquisition, which reflects the classical choice. Strategy 2 uses a piezoelectric element for the same, which opens up a new perspective in its implementation. In both strategies, the piezoelectric elements are used to harvest energy from foot activities and operate the system. The article presents a fair comparison between both strategies in terms of power consumption, accuracy, and the extent to which piezoelectric energy harvesters can contribute to overall power management. Moreover, Strategy 2, which uses piezoelectric elements for simultaneous sensing and energy harvesting, is a power-optimized method for an energy-autonomous shoe system.

Indexed as

accelerometeractivity recognitiongaitpiezoelectricstep-count

Identifiers

PMID38676166
PMCPMC11055156
OpenAlexW4394836152

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.