Modeling and design on control system of lower limb rehabilitation exoskeleton robot

Masengo, Gilbert; Zhang, Xiaodong; Yin, Guofu

doi:10.1109/urai.2016.7734058

Cited by 25 publications

(12 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Power assistive devices have been developed in recent years [1][2][3] for various purposes: in the welfare field for nursing [4,5], rehabilitation [6][7][8][9][10], and gait assistance [11][12][13][14][15][16][17][18][19]; in the industrial field for assembling and load-carrying [20][21][22][23][24]; and in the military field [25]. For example, Sankai [4] developed a robot suit HAL (Hybrid Assistive Limb) driven by electric motors, and it detects the walking intention by bioelectrical sensors attached to the users.…”

Section: Introductionmentioning

confidence: 99%

“…One of the technical challenges for realizing a practical assistive device is to synchronize the assistive force to the wearer's motion. To detect the wearer's intention of motion, most conventional devices require users to wear electric sensors, such as bioelectrical sensors [4,5], joint-angle sensors [10,14,20,22], inertial measurement unit (IMU) [11][12][13], force/torque sensors [6,15,17,22], and undersole pressure sensors [11][12][13]20,25]. The reliability of the intention detection can be increased by fusing multi-modal information from different type sensors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Motion Control of Soft Gait Assistive Suit by Gait Phase Detection Using Pressure Information

et al. 2019

View full text Add to dashboard Cite

Power assistive devices have been developed in recent years. To detect the wearer’s motion, conventional devices require users to wear sensors. However, wearing many sensors increases the wearing time, and usability of the device will become worse. We developed a soft gait assistive suit actuated by pneumatic artificial rubber muscles (PARMs) and proposed its control method. The proposed suit is easy to wear because the attachment unit does not have any electrical sensors that need to be attached to the trainee’s body. A target application is forward walking exercise on a treadmill. The control unit detects the pre-swing phase in the gait cycle using the pressure information in the calf back PARMs. After the detection, the suit assists the trainee’s leg motion. The assist force is generated by the controlled PARM pressure, and the pressure input time is changed appropriately considering the gait cycle time. We conducted walking experiments; (1) verifies the proposed control method works correctly, and (2) verifies whether the gait assistive suit is effective for decreasing muscular activity. Finally, we confirmed that the accurate phase detection can be achieved by using the proposed control method, and the suit can reduce muscular activity of the trainee’s leg.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Motion Control of Soft Gait Assistive Suit by Gait Phase Detection Using Pressure Information

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Lee et al realized BCI controllers based on EEG signals for wearable devices [11]. Few exoskeletons based solutions have also been proposed for Paraplegia or lower limb paralysis which is a spinal cord injury that paralyzes the lower limbs [12]. This BCI based exoskeleton was designed by decoding the signal of EEG related to the user.…”

Section: Introductionmentioning

confidence: 99%

Brain-Controlled Adaptive Lower Limb Exoskeleton for Rehabilitation of Post-Stroke Paralyzed

Vinoj

Jacob²,

Menon³

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Stroke is a standout amongst the most imperative reasons of incapacity on the planet. Due to partial or full paralysis, the majority of patients are compelled to rely upon parental figures and caregivers in residual life. With post-stroke rehabilitation, different types of assistive technologies have been proposed to offer developments to the influenced body parts of the incapacitated. In a large portion of these devices, the clients neither have control over the tasks nor can get feedback concerning the status of the exoskeleton. Additionally, there is no arrangement to detect user movements or accidental fall. The proposed framework tackles these issues utilizing a brain-controlled lower limb exoskeleton (BCLLE) in which the exoskeleton movements are controlled based on user intentions. An adaptive mechanism based on sensory feedback is integrated to reduce the system false rate. The BCLLE uses a flexible design which can be customized according to the degree of disability. The exoskeleton is modeled according to the human body anatomy, which makes it a perfect fit for the affected body part. The BCLLE system also automatically identifies the status of the paralyzed person and transmits information securely using Novel-T Symmetric Encryption Algorithm (NTSA) to caregivers in case of emergencies. The exoskeleton is fitted with motors which are controlled by the brain waves of the user with an electroencephalogram (EEG) headset. The EEG headset captures the human intentions based on the signals acquired from the brain. The brain-computer interface converts these signals into digital data and is interfaced with the motors via a microcontroller. The microcontroller controls the high torque motors connected to the exoskeleton's joints based on user intentions. Classification accuracy of more than 80% is obtained with our proposed method which is much higher compared with all existing solutions. INDEX TERMS Artificial skin, assistive technologies, brain-computer interface (BCI), electroencephalogram (EEG), brain-controlled exoskeleton, paralyzed, stroke.

show abstract

“…Considering the above demand, applying power-assistive devices would be effective in realizing load-adjustable gait training. Power-assistive devices have been developed in recent years [12]- [14] for diverse purposes: in the welfare field for nursing [15], [16], rehabilitation [17]- [21], gait assistance [22]- [30], in the industrial field for assembling and load-carrying [31]- [35], and in the military field [36]. One of the technical challenges for realizing a practical assistive device is synchronizing the assistive force to the wearer's motion.…”

Section: A Backgroundmentioning

confidence: 99%

Running Motion Assistance Using a Soft Gait-Assistive Suit and Its Experimental Validation

et al. 2021

View full text Add to dashboard Cite

A gait training method that can adjust the target leg load is required to meet the varied demands of trainees. In this study, we propose a running training method using a soft gait-assistive suit-a power-assistive device that adds an external force to the leg of a trainee by actuating a pneumatic artificial muscle (PAM). Herein, the assisting force is applied to the leg of the trainee so that muscle activity is reduced throughout the gait cycle. We detected the terminal stance phase as an appropriate assist timing from the pressure information, and the detected timing was used for the PAM control. We conducted a verification experiment of the PAM pressure variation. In a running mode of 7.0 to 10.0 km/h, all data showed that the PAM at the calf front has better detectability than that at the calf back, which is used in conventional detection methods. The experimental results confirmed that the PAM for gait phase detection should be positioned at the calf front during running. The effectiveness of the proposed running training method was verified through experiments on four trainees using a treadmill. The leg electromyogram of the trainees was measured and changes observed. Accordingly, 14 out of 16 channels of the four trainees showed a significant difference, and the electromyograms decreased by the suit assistance in the range of -1.4 to -80.3 % maximum voluntary contraction. Thus, the experimental results quantitatively confirmed that the proposed running assistance method is effective in reducing muscular activity.INDEX TERMS gait phase detection, pneumatic artificial muscle, pressure-based control, running training, soft gait-assistive suit

show abstract

Modeling and design on control system of lower limb rehabilitation exoskeleton robot

Cited by 25 publications

References 3 publications

A Motion Control of Soft Gait Assistive Suit by Gait Phase Detection Using Pressure Information

A Motion Control of Soft Gait Assistive Suit by Gait Phase Detection Using Pressure Information

Brain-Controlled Adaptive Lower Limb Exoskeleton for Rehabilitation of Post-Stroke Paralyzed

Running Motion Assistance Using a Soft Gait-Assistive Suit and Its Experimental Validation

Contact Info

Product

Resources

About