Evidence map›Paper›PMID 35062475›Full record

ArticleSensors (Basel, Switzerland)2022

Low-Cost Force Sensors Embedded in Physical Human-Machine Interfaces: Concept, Exemplary Realization on Upper-Body Exoskeleton, and Validation.

Niclas Hoffmann, Samet Ersoysal, Gilbert Prokop, Matthias Hoefer, Robert Weidner

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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
0.6field-weighted citation impact, top 41% 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, 8 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

5 authors at 2 institutions in 2 countries.

Niclas HoffmannDepartment of Production Technologies, Institute of Mechatronics, University of Innsbruck, 6020 Innsbruck, Austria.ORCID 0000-0003-4834-4761
Samet ErsoysalDepartment of Production Technologies, Institute of Mechatronics, University of Innsbruck, 6020 Innsbruck, Austria.
Gilbert ProkopDepartment of Production Technologies, Institute of Mechatronics, University of Innsbruck, 6020 Innsbruck, Austria.
Matthias HoeferDepartment of Production Technologies, Institute of Mechatronics, University of Innsbruck, 6020 Innsbruck, Austria.
Robert WeidnerDepartment of Production Technologies, Institute of Mechatronics, University of Innsbruck, 6020 Innsbruck, Austria.ORCID 0000-0003-1286-4458
Universität Innsbruck · ATHelmut Schmidt University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In modern times, the collaboration between humans and machines increasingly rises, combining their respective benefits. The direct physical support causes interaction forces in human-machine interfaces, whereas their form determines both the effectiveness and comfort of the collaboration. However, their correct detection requires various sensor characteristics and remains challenging. Thus, this paper presents a developed low-cost sensor pad working with a silicone capsule and a piezoresistive pressure sensor. Its measurement accuracy is validated in both an isolated testing environment and a laboratory study with four test subjects (gender-balanced), and an application integrated in interfaces of an active upper-body exoskeleton. In the material-testing machine, it becomes apparent that the sensor pad generally features the capability of reliably determining normal forces on its surface until a certain threshold. This is also proven in the real application, where the measurement data of three sensor pads spatially embedded in the exoskeletal interface are compared to the data of an installed multi-axis load cell and a high-resolution flexible pressure map. Here, the consideration of three sensor pads potentially enables detection of exoskeletal support on the upper arm as well as "poor" fit conditions such as uneven pressure distributions that recommend immediate system adjustments for ergonomic improvements.

Indexed as

Exoskeleton DeviceRoboticsWearable Electronic DevicesErgonomicsHumansUpper Extremityevaluationexoskeletonforce sensorhuman–machine interactioninteraction forceslow costmetrological comparisonpressure sensorwearable robot

Identifiers

PMID35062475
PMCPMC8780276
OpenAlexW4206448449

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.