Evidence map›Paper›PMID 33937345›Full record

ReviewFrontiers in robotics and AI2021

Safety Assessment of Rehabilitation Robots: A Review Identifying Safety Skills and Current Knowledge Gaps.

Jule Bessler, Gerdienke B Prange-Lasonder, Leendert Schaake, José F Saenz, Catherine Bidard, Irene Fassi, Marcello Valori, Aske Bach Lassen, Jaap H Buurke

Abstract readReview
In one paragraph

Review in Frontiers in robotics and AI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Application of Artificial Intelligence in Physical Rehabilitation of Patients Admitted to the Intensive Care Unit: A Scoping Review.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review.Archives of public health = Archives belges de sante publique · 2023
    Article
  19. Article
  20. Review
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

9 authors.

Jule BesslerRoessingh Research and Development, Enschede, Netherlands.
Gerdienke B Prange-LasonderRoessingh Research and Development, Enschede, Netherlands.
Leendert SchaakeRoessingh Research and Development, Enschede, Netherlands.
José F SaenzFraunhofer Institute for Factory Operation and Automation, Magdeburg, Germany.
Catherine BidardInteractive Robotics Laboratory, CEA LIST, Palaiseau, France.
Irene FassiNational Research Council of Italy, Milan, Italy.
Marcello ValoriNational Research Council of Italy, Milan, Italy.
Aske Bach LassenDepartment of Robot Technology, Danish Technological Institute, Odense, Denmark.
Jaap H BuurkeRoessingh Research and Development, Enschede, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The assessment of rehabilitation robot safety is a vital aspect of the development process, which is often experienced as difficult. There are gaps in best practices and knowledge to ensure safe usage of rehabilitation robots. Currently, safety is commonly assessed by monitoring adverse events occurrence. The aim of this article is to explore how safety of rehabilitation robots can be assessed early in the development phase, before they are used with patients. We are suggesting a uniform approach for safety validation of robots closely interacting with humans, based on safety skills and validation protocols. Safety skills are an abstract representation of the ability of a robot to reduce a specific risk or deal with a specific hazard. They can be implemented in various ways, depending on the application requirements, which enables the use of a single safety skill across a wide range of applications and domains. Safety validation protocols have been developed that correspond to these skills and consider domain-specific conditions. This gives robot users and developers concise testing procedures to prove the mechanical safety of their robotic system, even when the applications are in domains with a lack of standards and best practices such as the healthcare domain. Based on knowledge about adverse events occurring in rehabilitation robot use, we identified multi-directional excessive forces on the soft tissue level and musculoskeletal level as most relevant hazards for rehabilitation robots and related them to four safety skills, providing a concrete starting point for safety assessment of rehabilitation robots. We further identified a number of gaps which need to be addressed in the future to pave the way for more comprehensive guidelines for rehabilitation robot safety assessments. Predominantly, besides new developments of safety by design features, there is a strong need for reliable measurement methods as well as acceptable limit values for human-robot interaction forces both on skin and joint level.

Indexed as

development phasehazardsmechanical safetyphysical human-robot interactionregulationrehabilitation robotssafety assessmentstandardization

Identifiers

PMID33937345
PMCPMC8080797

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.