Evidence map›Paper›PMID 33803791›Full record

ArticleSensors (Basel, Switzerland)2021

Human Body Parts Proximity Measurement Using Distributed Tactile Robotic Skin.

Jan Klimaszewski, Michał Władziński

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Jan KlimaszewskiWarsaw University of Technology, Faculty of Mechatronics, Institute of Automatic Control and Robotics, A. Boboli 8 St., 02-525 Warsaw, Poland.ORCID 0000-0002-0028-0968
Michał WładzińskiWarsaw University of Technology, Faculty of Mechatronics, Institute of Metrology and Biomedical Engineering, A. Boboli 8 St., 02-525 Warsaw, Poland.ORCID 0000-0002-6986-251X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Safety in human-machine cooperation is the current challenge in robotics. Safe human-robot interaction requires the development of sensors that detect human presence in the robot's workspace. Detection of this presence should occur before the physical collision of the robot with the human. Human to robot proximity detection should be very fast, allowing machine elements deceleration to velocities safe for human-machine collision. The paper presents a new, low-cost design of distributed robotic skin, which allows real-time measurements of the human body parts proximity. The main advantages of the proposed solution are low cost of its implementation based on comb electrodes matrix and real-time operation due to fast and simple electronic design. The main contribution is the new idea of measuring the distance to human body parts by measuring the operating frequency of a rectangular signal generator, which depends on the capacity of the open capacitor. This capacitor is formed between the comb electrodes matrix and a reference plate located next to the matrix. The capacitance of the open capacitor changes if a human body part is in vicinity. The application of the developed device can be very wide. For example, in the field of cooperative robots, it can lead to the improvement of human-machine interfaces and increased safety of human-machine cooperation. The proposed construction can help to meet the increasing requirements for cooperative robots.

Indexed as

RoboticsHuman BodyHumansTouchdistributed sensorelectronic skinflexible electronicsgraphene nanoplateletsproximity sensorreal-timerobotic skintactile sensor

Identifiers

PMID33803791
PMCPMC8003171

What OpenQuestion holds

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Registered trials

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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.