5-Link model based gait trajectory adaption control strategies of the gait rehabilitation exoskeleton for post-stroke patients

Zhang, Jiafan; Dong, Yi; Yang, Canjun; Geng, Yu; Chen, Ying; Yin, Yan

doi:10.1016/j.mechatronics.2010.02.003

Cited by 79 publications

(39 citation statements)

References 8 publications

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“…In general, lower-limb rehabilitation robots can be divided into two categories, that is, exoskeleton robots and end-effector robots [9]. For example, Lokomat [10], BLEEX [11], and LOPES [12, 13] are typical exoskeleton robots, while Rutgers Ankle [14] and Haptic Walker [15] are end-effector robots.…”

Section: Development Of Lower-limb Rehabilitation Robotsmentioning

confidence: 99%

Robotics in Lower-Limb Rehabilitation after Stroke

Zhang

Zan

Wang

2017

Behavioural Neurology

106

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With the increase in the elderly, stroke has become a common disease, often leading to motor dysfunction and even permanent disability. Lower-limb rehabilitation robots can help patients to carry out reasonable and effective training to improve the motor function of paralyzed extremity. In this paper, the developments of lower-limb rehabilitation robots in the past decades are reviewed. Specifically, we provide a classification, a comparison, and a design overview of the driving modes, training paradigm, and control strategy of the lower-limb rehabilitation robots in the reviewed literature. A brief review on the gait detection technology of lower-limb rehabilitation robots is also presented. Finally, we discuss the future directions of the lower-limb rehabilitation robots.

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Section: Development Of Lower-limb Rehabilitation Robotsmentioning

confidence: 99%

Robotics in Lower-Limb Rehabilitation after Stroke

Zhang

Zan

Wang

2017

Behavioural Neurology

106

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“…To make patients recover sooner from the hospital, a gait rehabilitation robot assisted training with some quantitatively detected sensor data is the most commonly used training method at present [22,23], but it is mainly applicable to recover in the hospital without a precise and objective evaluation method of training effect [24,25]. Therefore, combined with the 'medical + internet' model, an app based on plantar pressure analysis is introduced, which can obtain the doctor's training plan via the internet and transmit it to the plantar pressure testing device.…”

Section: Conclusion and Prospectsmentioning

confidence: 99%

Development of an E-Health App for Lower Limb Postoperative Rehabilitation Based on Plantar Pressure Analysis

Cheng

Mei

et al. 2018

Applied Sciences

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Abstract:The traditional postoperative rehabilitation training mode of lower limbs is mostly confined to hospitals or nursing sites. With the increase of postoperative patients, the current shortage of medical resources is obviously not satisfactory, and the medical costs are high, thus it is difficult to apply widely. A new mobile phone application (app) based on plantar pressure analysis is developed to fulfill the requirements of remote postoperative rehabilitation. It is designed, implemented, tested, and used for pilot experiment in conjunction with the system design methodology of the waterfall model. Preliminary testing and a pilot experiment showed that the app has realized basic functions and can achieve patient rehabilitation out of hospitals. The development of the app can shorten the hospitalization time of patients, reduce medical costs, and make up for the current shortage of medical resources. In the future, more experiments will be done to verify the effectiveness of the app.

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“…In recent literature, a number of exoskeleton robotic legs have been developed and investigated mainly focusing on two different applications. We categorize these studies into two types: 1) enhancement of walking over a long distance or increasing load capability to carry heavy load repetitively [13], [14] and 2) rehabilitation aids for gait disorder persons or aged people [15], [18], [19]. Elderly people or gait disorder patients may lose muscular strength in their legs and become bedridden.…”

Section: A Bio-inspired Locomotion and Mechanismsmentioning

confidence: 99%