Evidence map›Paper›PMID 37300003›Full record

ArticleSensors (Basel, Switzerland)2023

Application of Foot Hallux Contact Force Signal for Assistive Hand Fine Control.

Jianwei Cui, Bingyan Yan, Han Du, Yucheng Shang, Liyan Tong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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
–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

0 citing papers in PubMed.

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

5 authors.

Jianwei CuiSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Bingyan YanSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Han DuSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Yucheng ShangSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0002-7335-1587
Liyan TongSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.

Funding

National Natural Science Foundation of China 61873063
6 · The paper itself

Abstract

Accurate recognition of disabled persons' behavioral intentions is the key to reconstructing hand function. Their intentions can be understood to some extent by electromyography (EMG), electroencephalogram (EEG), and arm movements, but they are not reliable enough to be generally accepted. In this paper, characteristics of foot contact force signals are investigated, and a method of expressing grasping intentions based on hallux (big toe) touch sense is proposed. First, force signals acquisition methods and devices are investigated and designed. By analyzing characteristics of signals in different areas of the foot, the hallux is selected. The peak number and other characteristic parameters are used to characterize signals, which can significantly express grasping intentions. Second, considering complex and fine tasks of the assistive hand, a posture control method is proposed. Based on this, many human-in-the-loop experiments are conducted using human-computer interaction methods. The results showed that people with hand disabilities could accurately express their grasping intentions through their toes, and could accurately grasp objects of different sizes, shapes, and hardness using their feet. The accuracy of the action completion for single-handed and double-handed disabled individuals was 99% and 98%, respectively. This proves that the method of using toe tactile sensation for assisting disabled individuals in hand control can help them complete daily fine motor activities. The method is easily acceptable in terms of reliability, unobtrusiveness, and aesthetics.

Indexed as

HalluxPersons with DisabilitiesElectromyographyHandHand StrengthHumansReproducibility of ResultsUpper Extremityassistive handcontact force signalscontinuous fine actions’ controlhuman–robot interactionposture controlupper limb assistive robotswearable sensors

Identifiers

PMID37300003
PMCPMC10256067

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.