Zhijiang Lu

Development of a three freedoms ankle rehabilitation robot for ankle training

In recent years, rehabilitation robot has been a trend to replace traditional therapist rehabilitation on hemiplegic rehabilitation. Researchers have proposed many ankle rehabilitation robots on ankle rehabilitation training. However, most of them are only focusing on single freedom training or providing a passive training to the patient. In this paper, a novel ankle robot with 3 freedoms which combines the active training with passive training together is presented. To build the ankle physiological model, an experiment to detect the ankle physiological data is established. And based on the data, an ankle rehabilitation robot with three degrees is proposed. In order to detect the dynamic movements of the ankle, the robot embeds force sensors and motor encoders. Then, the detail design of the mechanism is introduced. There are pedal parts, thigh fixing parts, base, driving unit and sensing unit in mechanism. Each part of the ankle robot is introduced in detail. Comparing with the other ankle rehabilitation robots, this robot uses three blushless motors to direct three rotation motions directly, and the whole structure is simple and reliable.

Mechanism design and control strategies of an ankle robot for rehabilitation training

It has become a trend that ankle rehabilitation robots replace traditional therapist in rehabilitation field. Many ankle rehabilitation robots have been proposed for rehabilitation training by researchers. However, most of current researches are only focusing on providing the passive training. They not only ignore the active force training for patient, but also neglect the relationship between passive training and neurological rehabilitation. In this paper, an ankle robot combining active training and passive training, subjective awareness and objective training is proposed. The ankle physiological model and mechanism of ankle rehabilitation robot are described. The control strategies of advanced training modes, passive training and active training, subjective awareness and objective training are introduced. Finally, experiments are established to testify the mechanical performance of ankle robot. Furthermore, experiment of passive training and active training is held among healthy people and the result show a good stability of the control system.

Development of a novel ankle rehabilitation robot with three freedoms for ankle rehabilitation training

Ankle rehabilitation training takes an important role in the hemiplegic rehabilitation training. Traditional training requires the physical therapist treating the patient as one to one. The training process is repeating and needs a long period. The performances of training rely heavily on the skill of therapists. The training effectiveness depends on the skills of the therapist. To improve the training effectiveness, there are many ankle rehabilitation robots are proposed. However all of them are only focusing on providing a passive training to the patient. In this paper, an ankle rehabilitation robot with three degrees is proposed. This robot can not only realizes the passive training but also has much more sensors to detect the movements of the ankle, especially realizes the patient active training. In this paper, the detail design of the mechanism is introduced. The mechanical structure includes pedal parts, thigh fixing parts, cross slider parts, driving unit and sensing unit. Comparing with current ankle rehabilitation researches, this robot uses linear motion in horizontal and vertical plane instead of rotary motion to realize dorsiflexion/plantar flexion and abduction/adduction. Finally, we present ankle motion space analysis and ankle robot workspace analysis of ankle robot to verify the feasibility of the robot.

Development of lower limb motion detection based on LPMS

Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. It leads to a great need for hemiplegic rehabilitation. In traditional rehabilitation, each patient must be treated by therapist, one by one. However, since the individual differences of therapists, no effectiveness rehabilitation is guaranteed. And the rehabilitation status of patient is still diagnosed by therapists with their subjective experience. This would cause the inhomogeneity on rehabilitation evaluation and sometimes negative influence on the rehabilitation effect. To solve these problems, many research groups proposed rehabilitation evaluation systems to assess the status of the hemiplegic patients quantitatively. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. However, many motion detection methods do not meet the detection requirements, such as mechanical tracking and optical sensor, etc. In this article we present a method to detect lower limb motion of hemiplegic patients based on inertial sensor technology. LPMS, a high performance, easy wearable, portable and large measurement range sensor, is selected as the motion sensor. We obtain the gesture quaternion of lower limb through LPMS, and then use the algorithm to convert quaternion to matrix and Euler angle. Combining with the simplified lower limb motion model, we compute the rotation angle of joint by processing the rotation quaternion in Matlab. Finally, the curve of rotation angle of knee is established. The method detecting the motion of lower limb can be integrated into the rehabilitation robot control system, realizing intelligent detection and evaluation. Thus, the rehabilitation robots could be expected adjusting training parameters based on patient status automatically, expected to have significant impacts in medical rehabilitation robot field.

Image based visual servoing from hybrid projected features

in this paper, we address the issue of hybrid visual servoing, which improve the performance of robotics system. Different from most of existing hybrid methods combining image based(IBVS) and position based(PBVS) visual servoing methods, we consider directly image features in error function, which is a robust IBVS method. In the framework of unified projection model, we select six proper features to control full-DOF motion. Invariants to rotational motion are computed with spherical projection model and used to control the translational motion, while invariants to translation motion are computed with perspective projection model and used to control the rotational motion. These hybrid projected features ensure good decoupled control between translational and rotational motions. Furtherly, two virtual moments calculated with SVM regression model are proposed to control the rotational motions around the x-axis and y-axis, which ensure improved decoupled properties. Simulation results are provided to illustrate the effectiveness and optimal performance of the proposed method.

Development of a novel finger and wrist rehabilitation robot for finger and wrist training

Up to now, with the developments of society, aging problems are more serious. With the requirements of rehabilitation, a large of hemiplegia rehabilitation devices are launched out. But most of the hand training robots just limit to the fingers flexible training. They ignored the importance of functional training of hand, and ignore wrist cooperative training in the rehabilitation process. In this paper, a novel finger and wrist rehabilitation robot will be introduced for hemiplegia rehabilitation, a creative hand rehabilitation way is presented. Two rehabilitation units are included -wrist rehabilitation unit and hand rehabilitation unit. Novel torque sensor units with a simple structure are designed to detect torque. The detail of the sensor is introduced in the paper. The proposed finger and wrist rehabilitation robot leads to further research on the rehabilitation robot.

Lower limb motion analysis based on inertial sensor

Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. The need for hemiplegic rehabilitation is increasing quickly. As traditional rehabilitation, each patient must be treated by therapist, one by one. However, because of the different levels of therapists, the rehabilitation cannot be performed as the as the same. Normally, the rehabilitation status diagnosing is still be performed by therapists with the subjective experience. It caused the inhomogeneity on rehabilitation evaluation. It also sometimes causes negative influence on the rehabilitation effect. To solve these problems, many researches focusing on assessing the status of the hemiplegic patients quantitatively are proposed rehabilitation evaluation systems. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. In this paper, a method is presented to detect lower limb motion of hemiplegic patients based on inertial sensor technology. The gesture quaternion of lower limb can be obtained through LPMS. With the matrix and Euler angle changing algorithm, combining with the simplified lower limb motion model, the rotation angle of joint can be computed. Finally, the curve of rotation angle of knee is established.

Development of an ankle robot MKA-III for rehabilitation training

With the developments of robotics, it has become a fashion trend that ankle rehabilitation robots assist traditional training in rehabilitation field. In this thesis, a novel ankle robot combing with 3 degrees of freedom, combining passive-active training, subjective awareness and objective training was proposed. Prior to robot developments, the requirement of ankle robot was analyzed based on the ankle structure and rehabilitation. In order to acquire the range of ankle motion, an experiment was established to detect the physiological data. Based on traditional rehabilitation therapy, a novel robot-assist rehabilitation therapy combing subjective awareness and objective training was proposed. Based on the requirements analysis, a novel mechanism structure of cross-circle was proposed to robot movement around ankle center. The mechanical structure includes four parts, adduction/abduction parts, dorsiflexion/plantar flexion parts, inversion/eversion parts and sensing unit. Each part of ankle rehabilitation robot was introduced in detail. By means of stress analysis and strength check, the feasibility of the structure was verified. After the mechanism design, the hardware configuration of control system was built up. Finally, the core control strategy, position control and force control were proposed.

Mechanism design of an ankle robot MKA-III for rehabilitation training

With the development of aging society, the number of hemiplegia patients grows rapidly and over 75% of survivors suffering hemiplegia need rehabilitation training. To assist therapists, series of rehabilitation training robots were carried out. However, most of current researches are only focusing on function training. They ignore the importance of neurological rehabilitation in early phrase of hemiplegia. Early rehabilitation takes a fundamental position in neurological rehabilitation and whole-body rehabilitation. To fulfill all of those requirements, MKA series have been developed. During the experiment, there is some problems including unreliable transmission and dehumanization design. For these reasons, in this paper, we propose the MKA-III. Based on physiological structure and rehabilitation theory, the mechanism was design. In this paper, the detail design of the mechanism is introduced. The mechanical structure includes four parts, adduction/abduction parts, dorsiflexion/plantar flexion parts, inversion/eversion parts and sensing unit. Each part of ankle rehabilitation robot was introduced in detail. In addition, for the motor control and information acquisition, the hard system is introduced.

Gait motion analysis based on WB-4 sensor with quaternion algorithm

Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. The needs for hemiplegic rehabilitation is increasing quickly. As traditional rehabilitation, each patient must be treated by therapist, one by one. However, because of the different levels of therapists, the rehabilitation cannot be performed as the as the same. Normally, the rehabilitation status diagnosing is still be performed by therapists with the subjective experience. It caused the inhomogeneity on rehabilitation evaluation. It also sometimes causes negative influence on the rehabilitation effect. To solve these problems, many researches focusing on assessing the status of the hemiplegic patients quantitatively are proposed rehabilitation evaluation systems. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. In this paper, a method is presented to detect lower limb motion of hemiplegic patients based on inertial sensor technology. The gesture quaternion of lower limb can be obtained through LPMS. With the matrix and Euler angle changing algorithm, combining with the simplified lower limb motion model, the rotation angle of joint can be computed. Finally, the curve of rotation angle of knee is established.