Evidence map›Paper›PMID 38486906›Full record

ArticleWearable technologies2022

Adaptive estimation of continuous gait phase based on capacitive sensors.

Dongfang Xu, Zhitong Zhang, Simona Crea, Nicola Vitiello, Qining Wang

Abstract read
In one paragraph

Article in Wearable technologies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

5 authors.

Dongfang XuDepartment of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China.
Zhitong ZhangDepartment of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China.
Simona CreaBioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.ORCID https://orcid.org/0000-0001-9833-4401
Nicola VitielloBioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Qining WangDepartment of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China.ORCID https://orcid.org/0000-0003-3484-4810

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Continuous gait phase plays an important role in robotic prosthesis control. In this paper, we have conducted the offline adaptive estimation (at different speeds and on different ramps) of continuous gait phase of robotic transtibial prosthesis based on the adaptive oscillators. We have used the capacitive sensing method to record the deformation of the muscles. Two transtibial amputees joined in this study. Based on the strain signals of the prosthetic foot and the capacitive signals of the residual limb, the maximum and minimum of estimation errors are 0.80 rad and 0.054 rad, respectively, and their corresponding ratios in one gait cycle are 1.27% and 0.86%, respectively. This paper proposes an effective method to estimate the continuous gait phase based on the capacitive signals of the residual muscles, which provides a basis for the continuous control of robotic transtibial prosthesis.

Indexed as

capacitive sensorscontinuous gait phaserobotic transtibial prosthesis

Identifiers

PMID38486906
PMCPMC10936350

What OpenQuestion holds

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LicenceCC BY
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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.