Powered orthosis and attachable power-assist device with Hydraulic Bilateral Servo System

Ohnishi, Kengo; Saitō, Yukio; Oshima, Toru; Higashihara, Takanori

doi:10.1109/embc.2013.6610134

Cited by 6 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hydraulic power transmissions have been used frequently in RAS (Takemura et al, 2005 ; Kargov et al, 2008 ; Pylatiuk et al, 2009 ; Kaminaga et al, 2010 ; Ohnishi et al, 2013 ; Bechet and Ohnishi, 2014 ; Lee, 2014 ; Smit et al, 2014b ; Polygerinos et al, 2015 ; Ouyang et al, 2016 ; Bos et al, 2020 ; Chen et al, 2020 ). In contrast to pneumatic RAS, which are usually limited to pressure control, pressure and flow can be generated and controlled at the input of hydraulic RAS.…”

Section: Methodsmentioning

confidence: 99%

“…Hydraulic cylinders are a different common approach to generate pressure and flow. Linear or rotary electromagnetic motors (Ohnishi et al, 2013 ; Bechet and Ohnishi, 2014 ; Chen et al, 2020 ) or body power (Smit et al, 2014b ; Bos et al, 2020 ) have been used to drive the piston of conventional hydraulic cylinders.…”

Section: Methodsmentioning

confidence: 99%

“…The most common types of hydraulic outputs are single- and double-acting cylinders combined with hydraulic cylinders driven by electric motors (Ohnishi et al, 2013 ; Bechet and Ohnishi, 2014 ; Bos et al, 2020 ) or pumps (Lee, 2014 ; Ouyang et al, 2016 ) in the actuation unit. Bellow actuators (Kargov et al, 2008 ; Pylatiuk et al, 2009 ), implementations of hydraulic artificial muscles (HAM) (Takemura et al, 2005 ), and soft hydraulic actuators (SHA) (Polygerinos et al, 2015 ; Chen et al, 2020 ) have been integrated into hydraulic-based RAS.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Remote Actuation Systems for Fully Wearable Assistive Devices: Requirements, Selection, and Optimization for Out-of-the-Lab Application of a Hand Exoskeleton

et al. 2021

View full text Add to dashboard Cite

Wearable robots assist individuals with sensorimotor impairment in daily life, or support industrial workers in physically demanding tasks. In such scenarios, low mass and compact design are crucial factors for device acceptance. Remote actuation systems (RAS) have emerged as a popular approach in wearable robots to reduce perceived weight and increase usability. Different RAS have been presented in the literature to accommodate for a wide range of applications and related design requirements. The push toward use of wearable robotics in out-of-the-lab applications in clinics, home environments, or industry created a shift in requirements for RAS. In this context, high durability, ergonomics, and simple maintenance gain in importance. However, these are only rarely considered and evaluated in research publications, despite being drivers for device abandonment by end-users. In this paper, we summarize existing approaches of RAS for wearable assistive technology in a literature review and compare advantages and disadvantages, focusing on specific evaluation criteria for out-of-the-lab applications to provide guidelines for the selection of RAS. Based on the gained insights, we present the development, optimization, and evaluation of a cable-based RAS for out-of-the-lab applications in a wearable assistive soft hand exoskeleton. The presented RAS features full wearability, high durability, high efficiency, and appealing design while fulfilling ergonomic criteria such as low mass and high wearing comfort. This work aims to support the transfer of RAS for wearable robotics from controlled lab environments to out-of-the-lab applications.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Remote Actuation Systems for Fully Wearable Assistive Devices: Requirements, Selection, and Optimization for Out-of-the-Lab Application of a Hand Exoskeleton

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Despite the importance of pHMI design on device function, the methods and specifications associated with developing pHMI components have been largely ignored in published literature. An extensive review reveals that details on the pHMI tend to fall into one of three categories: (a) authors refer to an orthosis but the design is either not described or only briefly described in terms of appearance (Perry et al, 2007;Jarrassé et al, 2008;Klein et al, 2008;Pylatiuk et al, 2009;Gmerek, 2012;Ohnishi et al, 2013;Rohm et al, 2013;Vaca Benitez et al, 2013;Herrnstadt and Menon, 2016;Sangha et al, 2016); (b) authors describe a generic orthosis design with added compliance to mitigate forces due to misalignment or dissimilarities in anthropometric shape, in which case the design elements focus on kinematics (Jarrassé and Morel, 2012); or (c) authors explain human interface details but do not report on the shape of their orthosis design (Jackson et al, 2007;Rocon et al, 2007;Gupta et al, 2008;Vanderniepen et al, 2009;Ragonesi et al, 2010;Vitiello et al, 2013;Alavi et al, 2017;Ates et al, 2017). In other words, most papers present the mechanical design and/or controller design, but very little content, if any, is focused on the design of the physical interface with the user.…”

Section: Introductionmentioning

confidence: 99%

3D Scanning of the Forearm for Orthosis and HMI Applications

et al. 2021

View full text Add to dashboard Cite

The rise of rehabilitation robotics has ignited a global investigation into the human machine interface (HMI) between device and user. Previous research on wearable robotics has primarily focused on robotic kinematics and controls but rarely on the actual design of the physical HMI (pHMI). This paper presents a data-driven statistical forearm surface model for designing a forearm orthosis in exoskeleton applications. The forearms of 6 subjects were 3D scanned in a custom-built jig to capture data in extreme pronation and supination poses, creating 3D point clouds of the forearm surface. Resulting data was characterized into a series of ellipses from 20 to 100% of the forearm length. Key ellipse parameters in the model include: normalized major and minor axis length, normalized center point location, tilt angle, and circularity ratio. Single-subject (SS) ellipse parameters were normalized with respect to forearm radiale-stylion (RS) length and circumference and then averaged over the 6 subjects. Averaged parameter profiles were fit with 3rd-order polynomials to create combined-subjects (CS) elliptical models of the forearm. CS models were created in the jig as-is (CS1) and after alignment to ellipse centers at 20 and 100% of the forearm length (CS2). Normalized curve fits of ellipse major and minor axes in model CS2 achieve R2 values ranging from 0.898 to 0.980 indicating a high degree of correlation between cross-sectional size and position along the forearm. Most other parameters showed poor correlation with forearm position (0.005 < R2 < 0.391) with the exception of tilt angle in pronation (0.877) and circularity in supination (0.657). Normalized RMSE of the CS2 ellipse-fit model ranged from 0.21 to 0.64% of forearm circumference and 0.22 to 0.46% of forearm length. The average and peak surface deviation between the scaled CS2 model and individual scans along the forearm varied from 0.56 to 2.86 mm (subject averages) and 3.86 to 7.16 (subject maximums), with the peak deviation occurring between 45 and 50% RS length. The developed equations allow reconstruction of a scalable 3D model that can be sized based on two user measures, RS length and forearm circumference, or based on generic arm measurements taken from existing anthropometric databases.

show abstract

“…Currently, the upper limb movements pattern-based methods focus separately on the hand, arm, elbow and shoulder action (Ohnishi et al , 2013; Dalley et al , 2012; Cipriani et al , 2011). However, there are many muscles associated with composite action pattern of shoulder and arm elbow muscles.…”

Section: Introductionmentioning

confidence: 99%

sEMG-based shoulder-elbow composite motion pattern recognition and control methods for upper limb rehabilitation robot

Zhang

Dai

et al. 2019

View full text Add to dashboard Cite

Purpose This paper aims to develop a signal acquisition system of surface electromyography (sEMG) and use the characteristics of (sEMG) signal to interference action pattern. Design/methodology/approach This paper proposes a fusion method based on combining the coefficient of AR model and wavelet coefficient. It improves the recognition rate of the target action. To overcome the slow convergence speed and local optimum in standard BP network, the study presents a BP algorithm which combine with LM algorithm and PSO algorithm, and it improves the convergence speed and the recognition rate of the target action. Findings Experiments verify the effectiveness of the system from two aspects the target motion recognition rate and the corresponding reaction speed of the robotic system. Originality/value The study developed a signal acquisition system of sEMG and used the characteristics of (sEMG) signal to interference action pattern. The myoelectricity integral values are presented to determine the starting point and end point of target movement, which is more effective than using single sample point amplitude method.

show abstract

Powered orthosis and attachable power-assist device with Hydraulic Bilateral Servo System

Cited by 6 publications

References 10 publications

Remote Actuation Systems for Fully Wearable Assistive Devices: Requirements, Selection, and Optimization for Out-of-the-Lab Application of a Hand Exoskeleton

Remote Actuation Systems for Fully Wearable Assistive Devices: Requirements, Selection, and Optimization for Out-of-the-Lab Application of a Hand Exoskeleton

3D Scanning of the Forearm for Orthosis and HMI Applications

sEMG-based shoulder-elbow composite motion pattern recognition and control methods for upper limb rehabilitation robot

Contact Info

Product

Resources

About