A Study on Artificial Kinesthesia Generation by Simultaneous Stimulation of Mechanical Vibration and Mechanical Skin Stretch.

Artificially controlled kinesthesia can be applied to many situations because kinesthesia is essential to recognizing body movements. It could be used to generate artificial kinesthesia in rehabilitation or daily motion assist to improve self-efficacy of the robot user. Moreover, the controlled artificial kinesthesia could make people feel as if they are performing the actions of the robotic limbs with their own limbs. Mechanical vibration stimulation is one of the candidates to artificially control kinesthesia. It is known that mechanical vibration stimulation on human muscles or tendons from skin surface evokes an illusion of movement as if the stimulated muscles are extended. That effect of artificial kinesthesia is called Kinesthetic Illusion (KI). In this paper, a method to increase the amount of KI without changing the frequency of the vibration stimulation is investigated by applying mechanical skin stretch stimulation at the same time with the mechanical vibration stimulation. The experiment was conducted by generating KI for flexion motion of the elbow joint on a horizontal plane to evaluate the proposed approach. In the experiments, three out of five subjects showed obvious increase in the amount of KI when skin stretch stimulation was applied at the same time with the mechanical vibration stimulation. The results of this study provide a first step toward artificial kinesthesia control using a wearable robotic device using the mechanical vibration stimulation.

Simultaneous Control of Tonic Vibration Reflex and Kinesthetic Illusion for Elbow Joint Motion Toward Novel Robotic Rehabilitation.

Robotic rehabilitation is one of the most promising applications of robotic technologies. It is known that patients' active participation in rehabilitation is important for their recovery. On the other hand, mechanical vibration stimulation to muscles induces tonic vibration reflex (TVR) and kinesthetic illusion (KI) in the joint motion. In this paper, the possibility of a novel robotic rehabilitation method, in which the TVR is applied to an agonist muscle to enhance the intended motion of patients and the KI is simultaneously applied to an antagonist muscle to enhance the kinesthetic movement sensation of the generating intended motion by changing the frequency of vibration stimulation, is investigated. As the first step toward novel robotic rehabilitation, the proposed method is evaluated in elbow joint motion. The experimental results show the possibility of the proposed novel rehabilitation method.Clinical Relevance- This study shows the possibility of novel robotic rehabilitation.

Towards Control of a Transhumeral Prosthesis with EEG Signals.

Robotic prostheses are expected to allow amputees greater freedom and mobility. However, available options to control transhumeral prostheses are reduced with increasing amputation level. In addition, for electromyography-based control of prostheses, the residual muscles alone cannot generate sufficiently different signals for accurate distal arm function. Thus, controlling a multi-degree of freedom (DoF) transhumeral prosthesis is challenging with currently available techniques. In this paper, an electroencephalogram (EEG)-based hierarchical two-stage approach is proposed to achieve multi-DoF control of a transhumeral prosthesis. In the proposed method, the motion intention for arm reaching or hand lifting is identified using classifiers trained with motion-related EEG features. For this purpose, neural network and k-nearest neighbor classifiers are used. Then, elbow motion and hand endpoint motion is estimated using a different set of neural-network-based classifiers, which are trained with motion information recorded using healthy subjects. The predictions from the classifiers are compared with residual limb motion to generate a final prediction of motion intention. This can then be used to realize multi-DoF control of a prosthesis. The experimental results show the feasibility of the proposed method for multi-DoF control of a transhumeral prosthesis. This proof of concept study was performed with healthy subjects.

Development of a multi-DoF transhumeral robotic arm prosthesis.

An anthropomorphic transhumeral robotic arm prosthesis is proposed in this study. It is capable of generating fifteen degrees-of-freedom, seven active and eight passive. In order to realize wrist motions, a parallel manipulator-based mechanism is proposed. It simulates the human anatomical structure and generates motions in two axes. The hand-of-arm prosthesis consists of under-actuated fingers with intrinsic actuation. The finger mechanism is capable of generating three degrees of freedom, and it exhibits the capability of adjusting the joint angles passively according to the geometry of the grasping object. Additionally, a parameter to evaluate finger mechanisms is introduced, and it measures the adoptability of a finger mechanism. In order to verify the mechanism's efficacy in terms of motion generation, motion simulation and kinematic analysis were carried out. Results demonstrated that the mechanisms are capable of generating the required motions.

Upper-limb tremor suppression with a 7DOF exoskeleton power-assist robot.

A tremor which is one of the involuntary motions is somewhat rhythmic motion that may occur in various body parts. Although there are several kinds of the tremor, an essential tremor is the most common tremor disorder of the arm. The essential tremor is a disorder of unknown cause, and it is common in the elderly. The essential tremor interferes with a patient's daily living activity, because it may occur during a voluntary motion. If a patient of an essential tremor uses an EMG-based controlled power-assist robot, the robot might misunderstand the user's motion intention because of the effect of the essential tremor. In that case, upper-limb power-assist robots must carry out tremor suppression as well as power-assist, since a person performs various precise tasks with certain tools by the upper-limb in daily living. Therefore, it is important to suppress the tremor at the hand and grasped tool. However, in the case of the tremor suppression control method which suppressed the vibrations of the hand and the tip of the tool, vibration of other part such as elbow might occur. In this paper, the tremor suppression control method for upper-limb power-assist robot is proposed. In the proposed method, the vibration of the elbow is suppressed in addition to the hand and the tip of the tool. The validity of the proposed method was verified by the experiments.

Compensation of the effects of muscle fatigue on EMG-based control using fuzzy rules based scheme.

Estimation of the correct motion intention of the user is very important for most of the Electromyography (EMG) based control applications such as prosthetics, power-assist exoskeletons, rehabilitation and teleoperation robots. On the other hand, safety and long term reliability are also vital for those applications, as they interact with human users. By considering these requirements, many EMG-based control applications have been proposed and developed. However, there are still many challenges to be addressed in the case of EMG based control systems. One of the challenges that had not been considered in such EMG-based control in common is the muscle fatigue. The muscle fatiguing effects of the user can deteriorate the effectiveness of the EMG-based control in the long run, which makes the EMG-based control to produce less accurate results. Therefore, in this study we attempted to develop a fuzzy rule based scheme to compensate the effects of muscle fatigues on EMG based control. Fuzzy rule based weights have been estimated based on time and frequency domain features of the EMG signals. Eventually, these weights have been used to modify the controller output according with the muscle fatigue condition in the muscles. The effectiveness of the proposed method has been evaluated by experiments.

Control of a myoelectric arm considering cooperated motion of elbow and shoulder joints.

In order to improve the quality of life of persons who lost their limb due to an accident or a sickness, many myoelectric artificial arms have been proposed. To control the motion of the elbow joint of the myoelectric arm, the EMG signals of the biceps brachii and the triceps brachii muscles are frequently used as input signals. However, since both muscles are the biarticular muscles between the shoulder joint and elbow joint, the amount of the EMG signals of these muscles are affected by the motion of the shoulder joint. In this paper, a control method for a myoelectric arm is proposed in order to cancel the influence of the shoulder joint motion on EMG signals is removed by using the neuro-fuzzy modifier in order to realize proper elbow motion. The effectiveness of the proposed method has been evaluated by performing experiments.

An upper-limb power-assist robot with tremor suppression control.

A tremor is somewhat rhythmic motion that may occur in various body parts. An essential tremor is one of the most common tremor disorders of the arm and it may occur during a voluntary motion. If the essential tremor occurs in the arm, the person may not be able to achieve the target task properly since the human performs various sensitive tasks with certain tools. Suppressing the vibration of the grasped tool is important when the person uses the tool. Power-assist robots are useful for not only the physically weak persons but also for persons involved in physically-taxing work such as a care or a farm work. Although some power-assist robots are controlled by using electromyogram (EMG) signals, EMG signals are influenced by the essential tremor. Therefore, when the user who suffers from the tremor uses the power-assist robot controlled based on EMG signals, the robot might assist the vibration of the tremor. In this paper, the tremor suppression control method is proposed for upper-limb power-assist robot. In proposed method, the vibrations of the hand and the tip of the tool are suppressed. The validity of the proposed method was verified by the experiments.

A lower-limb power-assist robot with perception-assist.

In order to assist the motion in the daily lives of physically weak persons such as elderly persons, many kinds of power-assist robots have been developed. In the case of some physically weak persons, the ability to perceive the environment is sometimes deteriorated also. A method of perception-assist has been proposed to assist not only the user's motion but also the user's interaction with an environment, by applying the modification force to the user's motion if it is necessary. In this paper, the perception-assist for a lower-limb power-assist exoskeleton robot is proposed. In the daily life, the walking is very important for persons to achieve desired tasks. Basically, the robot assists the user's muscle force according to the user's motion intention which is estimated based on EMG signals. If the robot has found problems which might lead the user to dangerous situation such as the falling down, the robot tries to modify the user's motion in addition to the ordinal power-assists to make the user walk properly. Since the user might fall down by the effect of the additional modification force of the perception-assist, the robot automatically prevents the user from falling down by considering ZMP (Zero Moment Point). The effectiveness of the proposed method has been evaluated by performing experiments.

A study of the effect of the femoral head diameter on prosthetic hip joint dislocation using a hip-joint motion simulator.

Prosthetic hip joint dislocation phenomenon is generated by the hip joint simulator and the effect of the femoral head diameter is studied under the same condition which is similar to the condition in daily activities. Impedance control is applied to control the hip joint motion and the joint contact force simultaneously in order to take into account the constraint caused by surrounding tendons, muscles, and a joint capsule of the hip joint. The experimental results show that the hip joint dislocation phenomenon is generated by the simulator and the obtained results about the effect of the femoral head size agree with those of the other research.

EMG-based neuro-fuzzy control of a 4DOF upper-limb power-assist exoskeleton.

We have been developing a 4DOF exoskeleton robot system in order to assist shoulder vertical motion, shoulder horizontal motion, elbow motion, and forearm motion of physically weak persons such as elderly, injured, or disabled persons. The robot is directly attached to a user's body and activated based on EMG (Electromyogram) signals of the user's muscles, since the EMG signals directly reflect the user's motion intention. A neuro-fuzzy controller has been applied to control the exoskeleton robot system. In this paper, controller adaptation method to user's EMG signals is proposed. A motion indicator is introduced to indicate the motion intention of the user for the controller adaptation. The experimental results show the effectiveness of the proposed method.

Modular fuzzy-neuro controller driven by spoken language commands.

We present a methodology of controlling machines using spoken language commands. The two major problems relating to the speech interfaces for machines, namely, the interpretation of words with fuzzy implications and the out-of-vocabulary (OOV) words in natural conversation, are investigated. The system proposed in this paper is designed to overcome the above two problems in controlling machines using spoken language commands. The present system consists of a hidden Markov model (HMM) based automatic speech recognizer (ASR), with a keyword spotting system to capture the machine sensitive words from the running utterances and a fuzzy-neural network (FNN) based controller to represent the words with fuzzy implications in spoken language commands. Significance of the words, i.e., the contextual meaning of the words according to the machine's current state, is introduced to the system to obtain more realistic output equivalent to users' desire. Modularity of the system is also considered to provide a generalization of the methodology for systems having heterogeneous functions without diminishing the performance of the system. The proposed system is experimentally tested by navigating a mobile robot in real time using spoken language commands.

A study on implantable urination assist systems - development of a bladder compression system.

We propose an urination assist system implantable in a patient who has difficulty in urination caused by the neuropathic bladder in order to assist the urination. The proposed system assists the urination by directly pushing the bladder of the patient using shape memory alloys (SMA). Peltier elements are used to control the temperature in the system. The effectiveness of the proposed system is evaluated by experiment with a bladder model.