Development of an End-effector Typed Walking Rehabilitation Robot Capable of Power Assistance

김정준,; 김명주,; 곽노식,; 김창휘,; 김형식,; 김정엽,

doi:10.3795/ksme-a.2018.42.8.721

Cited by 4 publications

(2 citation statements)

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“…The most common disorder is associated with the human body's knees, hips, and spine [2]. With the help of timely rehabilitation, early recovery in walking can be expected [3][4][5][6]. Many different types of walking assistance devices have been reported in past years.…”

Section: Introductionmentioning

confidence: 99%

Calibration and optimization of FSR based smart walking assistance device

Kumar

Padhye²,

Kulkarni³

et al. 2023

Eng. Res. Express

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The movement of the legs is a very important activity and routine exercise in human life for the fundamental necessity of mobility. Few smart walking assistance (SWA) devices have recently been developed to support walking for older people and osteoarthritis patients. A smart walking assistance device was developed using force-sensitive resistors (FSRs) to support mobility. Precise motion control of the walker wheel is necessary to direct the SWA device in the intended direction. Due to the inaccuracy in motor manufacturing and its internal resistances, the motors and respective attached wheels run at different speeds even though the electrical input signal is the same. The asynchronization in the motors attached to the wheels leads to deviation in the intended path of the user. It is very important to follow the exact path by SWA as per the requirement and safety of the user. In this paper, the speed asynchronization issue of the SWA device is addressed. The asynchronization problem is solved using mathematical modeling followed by implementing effective speed control techniques to provide speed synchronization in all the driving motors of SWA. Further, the power consumption of SWA is also analyzed. It has been found that the proposed SWA device, after calibration and optimization with pulse width modulation (PWM) mapping performed a successful operation with a power-saving of 27.62% at no-load and 77.33 % at load conditions.

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Section: Introductionmentioning

confidence: 99%

Calibration and optimization of FSR based smart walking assistance device

Kumar

Padhye²,

Kulkarni³

et al. 2023

Eng. Res. Express

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“…In this paper, the image local feature technology is used to assist the rehabilitation robot in target recognition and tracking [5][6]. Through the analysis of rehabilitation robots and the research of related vision technologies, an effective treatment assistance system is provided [7].…”

Section: Introductionmentioning

confidence: 99%

Target Recognition Method of Rehabilitation Robot Based on Image Local Features

Xing

2020

IEEE Access

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Target recognition technology is an important topic in the field of artificial intelligence, which is widely used in fields such as medicine, robot vision, highway traffic, and VR technology. In the robot vision system, the target recognition technology requires high precision, real-time, and practicality, and it must be able to cope with the harsh recognition environment on site. This paper mainly studies the target recognition method of rehabilitation robot based on image local features. In this paper, a rehabilitation robot recognition system is established based on the local features of the image and the target recognition technology. Firstly, after collecting or processing the initially prepared images, feature extraction is performed, and the feature vectors extracted from the features are classified and recognized and then transferred to the recognition model of the rehabilitation robot. Then, according to the functional requirements of the rehabilitation robot recognition system, the "one-to-many" rehabilitation mode and real-time system monitoring are realized to accurately identify the target state. Finally, the Harris algorithm is used to convert the predetermined image set into a grayscale image, and the Gaussian distribution is used uniformly to determine the location and proportion of the feature points, and extract the corresponding image.The Harris matching method used in this article is very effective and has the highest accuracy. The number of correct matches accounted for 58.3%. Compared with the SIFT algorithm and the Harris+SIFT algorithm, the accuracy rate increases by 12.3% and 14.4%, respectively. The recall rate increased by 13.2% and 8.9% respectively. The experimental results show that the target recognition technology of rehabilitation robot based on image local features is more accurate than general technology.

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Gait Training Algorithm of an End-Effector Typed Hybrid Walking Rehabilitation Robot

Kim

Park

2019

Int. J. Precis. Eng. Manuf.

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Development of an End-effector Typed Walking Rehabilitation Robot Capable of Power Assistance

Cited by 4 publications

References 0 publications

Calibration and optimization of FSR based smart walking assistance device

Calibration and optimization of FSR based smart walking assistance device

Target Recognition Method of Rehabilitation Robot Based on Image Local Features

Gait Training Algorithm of an End-Effector Typed Hybrid Walking Rehabilitation Robot

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