Literature DB >> 33501319

Occurrence and Type of Adverse Events During the Use of Stationary Gait Robots-A Systematic Literature Review.

Jule Bessler1,2, Gerdienke B Prange-Lasonder1,3, Robert V Schulte1,2, Leendert Schaake1, Erik C Prinsen1,3, Jaap H Buurke1,2.   

Abstract

Robot-assisted gait training (RAGT) devices are used in rehabilitation to improve patients' walking function. While there are some reports on the adverse events (AEs) and associated risks in overground exoskeletons, the risks of stationary gait trainers cannot be accurately assessed. We therefore aimed to collect information on AEs occurring during the use of stationary gait robots and identify associated risks, as well as gaps and needs, for safe use of these devices. We searched both bibliographic and full-text literature databases for peer-reviewed articles describing the outcomes of stationary RAGT and specifically mentioning AEs. We then compiled information on the occurrence and types of AEs and on the quality of AE reporting. Based on this, we analyzed the risks of RAGT in stationary gait robots. We included 50 studies involving 985 subjects and found reports of AEs in 18 of those studies. Many of the AE reports were incomplete or did not include sufficient detail on different aspects, such as severity or patient characteristics, which hinders the precise counts of AE-related information. Over 169 device-related AEs experienced by between 79 and 124 patients were reported. Soft tissue-related AEs occurred most frequently and were mostly reported in end-effector-type devices. Musculoskeletal AEs had the second highest prevalence and occurred mainly in exoskeleton-type devices. We further identified physiological AEs including blood pressure changes that occurred in both exoskeleton-type and end-effector-type devices. Training in stationary gait robots can cause injuries or discomfort to the skin, underlying tissue, and musculoskeletal system, as well as unwanted blood pressure changes. The underlying risks for the most prevalent injury types include excessive pressure and shear at the interface between robot and human (cuffs/harness), as well as increased moments and forces applied to the musculoskeletal system likely caused by misalignments (between joint axes of robot and human). There is a need for more structured and complete recording and dissemination of AEs related to robotic gait training to increase knowledge on risks. With this information, appropriate mitigation strategies can and should be developed and implemented in RAGT devices to increase their safety.
Copyright © 2020 Bessler, Prange-Lasonder, Schulte, Schaake, Prinsen and Buurke.

Entities:  

Keywords:  adverse event (AE); injuries (MeSH); physical human-robot interaction (pHRI); rehabilitation robotics; robot-assisted gait training; safety; stationary gait robots

Year:  2020        PMID: 33501319      PMCID: PMC7805916          DOI: 10.3389/frobt.2020.557606

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  64 in total

1.  Evaluation of robotic-assisted locomotor training outcomes at a rehabilitation centre in Singapore.

Authors:  L F Chin; W S Lim; K H Kong
Journal:  Singapore Med J       Date:  2010-09       Impact factor: 1.858

2.  Effects of locomotion training with assistance of a robot-driven gait orthosis in hemiparetic patients after stroke: a randomized controlled pilot study.

Authors:  Britta Husemann; Friedemann Müller; Carmen Krewer; Silke Heller; Eberhardt Koenig
Journal:  Stroke       Date:  2007-01-04       Impact factor: 7.914

3.  Spatiotemporal gait characteristic changes with gait training using the hybrid assistive limb for chronic stroke patients.

Authors:  Hiroki Tanaka; Manabu Nankaku; Toru Nishikawa; Takuya Hosoe; Honami Yonezawa; Hiroki Mori; Takayuki Kikuchi; Hidehisa Nishi; Yasushi Takagi; Susumu Miyamoto; Ryosuke Ikeguchi; Shuichi Matsuda
Journal:  Gait Posture       Date:  2019-05-03       Impact factor: 2.840

4.  A Comparison of Locomotor Therapy Interventions: Partial-Body Weight-Supported Treadmill, Lokomat, and G-EO Training in People With Traumatic Brain Injury.

Authors:  Alberto Esquenazi; Stella Lee; Amanda Wikoff; Andrew Packel; Theresa Toczylowski; John Feeley
Journal:  PM R       Date:  2017-01-16       Impact factor: 2.298

5.  Who may benefit from robotic-assisted gait training? A randomized clinical trial in patients with subacute stroke.

Authors:  Giovanni Morone; Maura Bragoni; Marco Iosa; Domenico De Angelis; Vincenzo Venturiero; Paola Coiro; Luca Pratesi; Stefano Paolucci
Journal:  Neurorehabil Neural Repair       Date:  2011-03-26       Impact factor: 3.919

Review 6.  Skin response to mechanical stress: adaptation rather than breakdown--a review of the literature.

Authors:  J E Sanders; B S Goldstein; D F Leotta
Journal:  J Rehabil Res Dev       Date:  1995-10

7.  Combined transcranial direct current stimulation and robot-assisted gait training in patients with chronic stroke: a preliminary comparison.

Authors:  Christian Geroin; Alessandro Picelli; Daniele Munari; Andreas Waldner; Christopher Tomelleri; Nicola Smania
Journal:  Clin Rehabil       Date:  2011-03-14       Impact factor: 3.477

8.  Case Report: Description of two fractures during the use of a powered exoskeleton.

Authors:  F H M van Herpen; R B van Dijsseldonk; H Rijken; N L W Keijsers; J W K Louwerens; I J W van Nes
Journal:  Spinal Cord Ser Cases       Date:  2019-12-11

Review 9.  Risk management and regulations for lower limb medical exoskeletons: a review.

Authors:  Yongtian He; David Eguren; Trieu Phat Luu; Jose L Contreras-Vidal
Journal:  Med Devices (Auckl)       Date:  2017-05-09

10.  Characterizing the comfort limits of forces applied to the shoulders, thigh and shank to inform exosuit design.

Authors:  Matthew B Yandell; David M Ziemnicki; Kirsty A McDonald; Karl E Zelik
Journal:  PLoS One       Date:  2020-02-12       Impact factor: 3.240

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  5 in total

1.  Safety and Feasibility of a Novel Exoskeleton for Locomotor Rehabilitation of Subjects With Spinal Cord Injury: A Prospective, Multi-Center, and Cross-Over Clinical Trial.

Authors:  Sijing Chen; Zhanbin Wang; Yongqiang Li; Jiashuai Tang; Xue Wang; Liping Huang; Zhuangwei Fang; Tao Xu; Jiang Xu; Feng Guo; Yizhao Wang; Jianjun Long; Xiaodong Wang; Fang Liu; Jianfeng Luo; Yulong Wang; Xiaolin Huang; Zishan Jia; Mei Shuai; Jianan Li
Journal:  Front Neurorobot       Date:  2022-05-12       Impact factor: 3.493

Review 2.  Safety Assessment of Rehabilitation Robots: A Review Identifying Safety Skills and Current Knowledge Gaps.

Authors:  Jule Bessler; Gerdienke B Prange-Lasonder; Leendert Schaake; José F Saenz; Catherine Bidard; Irene Fassi; Marcello Valori; Aske Bach Lassen; Jaap H Buurke
Journal:  Front Robot AI       Date:  2021-03-22

3.  Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator.

Authors:  Jule Bessler-Etten; Leendert Schaake; Gerdienke B Prange-Lasonder; Jaap H Buurke
Journal:  J Neuroeng Rehabil       Date:  2022-01-29       Impact factor: 4.262

Review 4.  Effectiveness of Platform-Based Robot-Assisted Rehabilitation for Musculoskeletal or Neurologic Injuries: A Systematic Review.

Authors:  Anil Babu Payedimarri; Matteo Ratti; Riccardo Rescinito; Kris Vanhaecht; Massimiliano Panella
Journal:  Bioengineering (Basel)       Date:  2022-03-22

5.  Therapeutic Effects of a Newly Developed 3D Magnetic Finger Rehabilitation Device in Subacute Stroke Patients: A Pilot Study.

Authors:  Sung-Hoon Kim; Dong-Min Ji; Chan-Yong Kim; Sung-Bok Choi; Min-Cheol Joo; Min-Su Kim
Journal:  Brain Sci       Date:  2022-01-14
  5 in total

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