An Autonomous Exoskeleton for Ankle Plantarflexion Assistance

Wu, An-Ming; Yang, Xingbang; Kuan, Jiun-Yih; Herr, Hugh M.

doi:10.1109/icra.2019.8793913

Cited by 5 publications

(8 citation statements)

References 18 publications

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“…Electric actuators were the most popular actuators deployed in the reviewed PAEs. They were powered by on-board battery packs [37,41,56,57,61,[65][66][67][76][77][78][79][80][81][82][83][84]86,87,94,[100][101][102]112,113,115,[118][119][120]126,127,130,144,145,[156][157][158][159][160][172][173][174][175]177,184,187,189,234,235], DC off-board power supply units [10,…”

Section: Low-level Control and Machine-machine Sensorsmentioning

confidence: 99%

“…Cable/rope tension Tension sensor [53,182] force sensor [57] load cell [39,58,69,[108][109][110][122][123][124][125][126][127][128][129]180,183,204] strain gauge [72,113,181] Mechanical deflection Potentiometer [10,55,67,108,110,137,146,153,176] encoder [206,207,236] Pressure Pressure sensor [62,63,146,156,158,166,171,173,176,232] Pneumatic muscle force Load cell [11,38,49,50,…”

Section: Measured Parameter Sensormentioning

confidence: 99%

“…Motor position Motor [113] Encoder (ENX16 EASY 500IMP) Motor position In actuator module [115,116] Motor Encoder Motor position and velocity Motor [39,143,147,148] Quadrature encoders (2×195 RPM and 2×60 RPM HD premium planetary gearheads)…”

Section: Pneumatic Muscle Forcementioning

confidence: 99%

“…Electric actuators were the most popular actuators deployed in the reviewed PAEs. They were powered by on-board battery packs [ 37 , 41 , 56 , 57 , 61 , 65 , 66 , 67 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 86 , 87 , 94 , 100 , 101 , 102 , 112 , 113 , 115 , 118 , 119 , 120 , 126 , 127 , 130 , 144 , 145 , 156 , 157 , 158 , 159 , 160 , 172 , 173 , 174 , 175 , 177 , 184 , 187 , 189 , 234 , 235 ], DC off-board power supply units [ 10 , 39 , 109 , 116 ...…”

Section: Sensor Technologies Used In Control Hierarchy Of the Paesmentioning

confidence: 99%

“…Classical proportional–integral–derivative (PID) feedback controllers [ 39 , 53 , 54 , 55 , 56 , 67 , 68 , 76 , 77 , 78 , 79 , 82 , 86 , 101 , 102 , 108 , 109 , 110 , 114 , 119 , 120 , 121 , 136 , 138 , 139 , 140 , 154 , 155 ] were the most frequently used control algorithms in the reviewed PAEs due to the simplicity of real-time implementation [ 239 ]. Integral, proportional, and derivative feedback is based on the past (I), present (P) and future (D) state of the system Three types of controllers have been devised based on the integral, proportional, and derivative feedback controllers that are widely used in PAEs: P [ 100 , 106 , 107 , 113 , 146 , 172 , 178 , 185 , 186 , 187 , 204 ], PI [ 85 , 100 , 105 , 178 , 185 , 186 , 187 ], and PD [ 10 ,…”

Section: Sensor Technologies Used In Control Hierarchy Of the Paesmentioning

confidence: 99%

See 4 more Smart Citations

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

kian

Widanapathirana

Joseph

et al. 2022

Sensors

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Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided.

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Section: Low-level Control and Machine-machine Sensorsmentioning

confidence: 99%

Section: Measured Parameter Sensormentioning

confidence: 99%

Section: Pneumatic Muscle Forcementioning

confidence: 99%

Section: Sensor Technologies Used In Control Hierarchy Of the Paesmentioning

confidence: 99%

Section: Sensor Technologies Used In Control Hierarchy Of the Paesmentioning

confidence: 99%

See 3 more Smart Citations

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

kian

Widanapathirana

Joseph

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

A systematic review of technological advancements in signal sensing, actuation, control and training methods in robotic exoskeletons for rehabilitation

Mathew

Thomas

Navaneeth

et al. 2022

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Purpose The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research. Design/methodology/approach Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143. Findings Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially. Research limitations/implications Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject. Originality/value The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

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Leaf-Inspired FSR Array and Insole-Type Sensor Module for Mobile Three-Dimensional Ground Reaction Force Estimation

Kim,

Song,

et al. 2024

2024 IEEE International Conference on Robotics and Automation (ICRA)

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An Autonomous Exoskeleton for Ankle Plantarflexion Assistance

Cited by 5 publications

References 18 publications

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

A systematic review of technological advancements in signal sensing, actuation, control and training methods in robotic exoskeletons for rehabilitation

Leaf-Inspired FSR Array and Insole-Type Sensor Module for Mobile Three-Dimensional Ground Reaction Force Estimation

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