Biocybernetic system evaluates indices of operator engagement in automated task

A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.

Real-time myoprocessors for a neural controlled powered exoskeleton arm

Exoskeleton robots are promising assistive/rehabilitative devices that can help people with force deficits or allow the recovery of patients who have suffered from pathologies such as stroke. The key component that allows the user to control the exoskeleton is the human machine interface (HMI). Setting the HMI at the neuro-muscular level may lead to seamless integration and intuitive control of the exoskeleton arm as a natural extension of the human body. At the core of the exoskeleton HMI there is a model of the human muscle, the "myoprocessor," running in real-time and in parallel to the physiological muscle, that predicts joint torques as a function of the joint kinematics and neural activation levels. This paper presents the development of myoprocessors for the upper limb based on the Hill phenomenological muscle model. Genetic algorithms are used to optimize the internal parameters of the myoprocessors utilizing an experimental database that provides inputs to the model and allows for performance assessment. The results indicate high correlation between joint moment predictions of the model and the measured data. Consequently, the myoprocessor seems an adequate model, sufficiently robust for further integration into the exoskeleton control system.

Intelligence by mechanics

Research on the biomechanics of animal and human locomotion provides insight into basic principles of locomotion and respective implications for construction and control. Nearly elastic operation of the leg is necessary to reproduce the basic dynamics in walking and running. Elastic leg operation can be modelled with a spring-mass model. This model can be used as a template with respect to both gaits in the construction and control of legged machines. With respect to the segmented leg, the humanoid arrangement saves energy and ensures structural stability. With the quasi-elastic operation the leg inherits the property of self-stability, i.e. the ability to stabilize a system in the presence of disturbances without sensing the disturbance or its direct effects. Self-stability can be conserved in the presence of musculature with its crucial damping property. To ensure secure foothold visco-elastic suspended muscles serve as shock absorbers. Experiments with technically implemented leg models, which explore some of these principles, are promising.

Adaptive tracking for pneumatic muscle actuators in bicep and tricep configurations

Adaptive tracking techniques are applied to pneumatic muscle actuators arranged in bicep and tricep configurations. The control objective is to force the joint angle to track a specified reference path. Mathematical models are derived for the bicep and tricep configurations. The models are nonlinear and in general time-varying, making adaptive control desirable. Stability results are derived, and the results of simulation studies are presented, contrasting the nonlinear adaptive control to a nonadaptive PID control approach.

The implantable neurocybernetic prosthesis system

The neurocybernetic prosthesis system (NCP) is an implantable, multiprogrammable pulse generator that delivers constant current electrical signals to the vagus nerve for the purpose of reducing the frequency and severity of epileptic seizures. The signals are delivered on a predetermined schedule, or may be initiated by the patient with an external magnet. The device is implanted in a subcutaneous pocket in the chest just below the clavicle, similar to pacemaker placement. The stimulation signal is transmitted from the prosthesis to the vagus nerve through a lead connected to an electrode which is a multi-turn silicone helix, with a platinum band on the inner turn of one helix. The prosthesis can be programmed with any IBM- compatible personal computer using NCP software and a programming wand.

Honda humanoid robots development

Honda has been doing research on robotics since 1986 with a focus upon bipedal walking technology. The research started with straight and static walking of the first prototype two-legged robot. Now, the continuous transition from walking in a straight line to making a turn has been achieved with the latest humanoid robot ASIMO. ASIMO is the most advanced robot of Honda so far in the mechanism and the control system. ASIMO's configuration allows it to operate freely in the human living space. It could be of practical help to humans with its ability of five-finger arms as well as its walking function. The target of further development of ASIMO is to develop a robot to improve life in human society. Much development work will be continued both mechanically and electronically, staying true to Honda's 'challenging spirit'.

Mathematical and empirical proof of principle for an on-body personal lift augmentation device (PLAD)

In our laboratory, we have developed a prototype of a personal lift augmentation device (PLAD) that can be worn by workers during manual handling tasks involving lifting or lowering or static holding in symmetric and asymmetric postures. Our concept was to develop a human-speed on-body assistive device that would reduce the required lumbar moment by 20-30% without negative consequences on other joints or lifting kinematics. This paper provides mathematical proof using simplified free body diagrams and two-dimensional moment balance equations. Empirical proof is also provided based on lifting trials with nine male subjects who executed sagittal plane lifts using three lifting styles (stoop, squat, free) and three different loads (5, 15, and 25kg) under two conditions (PLAD, No-PLAD). Nine Fastrak sensors and six in-line strap force sensors were used to estimate the reduction of compressive and shear forces on L4/L5 as well as estimate the forces transferred to the shoulders and knees. Depending on lifting technique, the PLAD applied an added 23-36Nm of torque to assist the back muscles during lifting tasks. The peak pelvic girdle contact forces were estimated and their magnitudes ranged from 221.3+/-11.2N for stoop lifting, 324.3+/-17.2N for freestyle lifts to 468.47+/-23.2N for squat lifting. The PLAD was able to reduce the compression and shear forces about 23-29% and 7.9-8.5%, respectively.

Vagal stimulation for control of complex partial seizures in medically refractory epileptic patients

Chronic intermittent stimulation of the vagus nerve is a new method currently being tested for the treatment of medically intractable complex partial seizures (CPS). We have studied the effects of vagal stimulation in nine patients with CPS for 4-16 months to determine its safety and efficacy. With the patients maintained on constant dosages of antiepileptic drugs, we recorded the electroencephalogram and electrocardiogram, and performed clinical laboratory tests and gastric analysis over a 6-week baseline period. The neurocybernetic prosthesis (NCP) was then implanted and connected to two spiral electrodes wound around the left vagus nerve. After a 4-week placebo period, vagal stimulation was started. Stimulation parameters were increased stepwise at monthly intervals until patients were being stimulated for 30-second periods at 20-50 Hz with 1-2 mA of current at 250-500 microseconds pulses. A second 4-week placebo period was added 3 months after the implantation. Thereafter, vagal stimulation was resumed and self-stimulation with magnetic activation was allowed for a 1-minute period at the onset of an aura. Six patients had a significant reduction in the frequency, intensity, or duration of seizures. All patients tolerated the implantation and stimulation well and none reported pain, discomfort, or important changes in their daily activities, sleep habits, eating, swallowing, or breathing. There were no remarkable changes in blood pressure or heart rate.

Neural PID Control of Robot Manipulators With Application to an Upper Limb Exoskeleton

In order to minimize steady-state error with respect to uncertainties in robot control, proportional-integral-derivative (PID) control needs a big integral gain, or a neural compensator is added to the classical proportional-derivative (PD) control with a large derivative gain. Both of them deteriorate transient performances of the robot control. In this paper, we extend the popular neural PD control into neural PID control. This novel control is a natural combination of industrial linear PID control and neural compensation. The main contributions of this paper are semiglobal asymptotic stability of the neural PID control and local asymptotic stability of the neural PID control with a velocity observer which are proved with standard weight training algorithms. These conditions give explicit selection methods for the gains of the linear PID control. An experimental study on an upper limb exoskeleton with this neural PID control is addressed.

Adaptive neural control for dual-arm coordination of humanoid robot with unknown nonlinearities in output mechanism

To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of output hysteresis could be ignored. However, in the practical applications, the output hysteresis is widely spread; and its existing limits the motion/force performances of the robotic system. In this paper, an adaptive neural control scheme, which takes the unknown output hysteresis and computational efficiency into account, is presented and investigated. In the controller design, the prior knowledge of system dynamics is assumed to be unknown. The motion error is guaranteed to converge to a small neighborhood of the origin by Lyapunov's stability theory. Simultaneously, the internal force is kept bounded and its error can be made arbitrarily small.

Biomimetic approaches to the control of underwater walking machines

We have developed a biomimetic robot based on the American lobster. The robot is designed to achieve the performance advantages of the animal model by adopting biomechanical features and neurobiological control principles. Three types of controllers are described. The first is a state machine based on the connectivity and dynamics of the lobster central pattern generator (CPG). The state machine controls myomorphic actuators based on shape memory alloys (SMAs) and responds to environmental perturbation through sensors that employ a labelled-line code. The controller supports a library of action patterns and exteroceptive reflexes to mediate tactile navigation, obstacle negotiation and adaptation to surge. We are extending this controller to neuronal network-based models. A second type of leg CPG is based on synaptic networks of electronic neurons and has been adapted to control the SMA actuated leg. A brain is being developed using layered reflexes based on discrete time map-based neurons.

Cerebellar ataxia: quantitative assessment and cybernetic interpretation

To assess neuromotor disorders clinicians often rely on rating scales. Unfortunately, these scales lack the sensitivity and accuracy needed to detect the small changes in motor coordination that reflect the clinical progression of the disease on the basis of which treatment programmes can be adjusted. As a contribution to this topic, the present paper proposes a straightforward kinematic and kinetic analysis of reaching movements of patients with cerebellar ataxia in conjunction with a cybernetic interpretation of the data. The aim of the approach is to capture key deficits in the underlying motor control processes. We suggest that cerebellar ataxia may be characterized by defective feedforward control.

Odour-tracking capability of a silkmoth driving a mobile robot with turning bias and time delay

The reconstruction of mechanisms behind odour-tracking behaviours of animals is expected to enable the development of biomimetic robots capable of adaptive behaviour and effectively locating odour sources. However, because the behavioural mechanisms of animals have not been extensively studied, their behavioural capabilities cannot be verified. In this study, we have employed a mobile robot driven by a genuine insect (insect-controlled robot) to evaluate the behavioural capabilities of a biological system implemented in an artificial system. We used a male silkmoth as the 'driver' and investigated its behavioural capabilities to imposed perturbations during odour tracking. When we manipulated the robot to induce the turning bias, it located the odour source by compensatory turning of the on-board moth. Shifting of the orientation paths to the odour plume boundaries and decreased orientation ability caused by covering the visual field suggested that the moth steered with bilateral olfaction and vision to overcome the bias. An evaluation of the time delays of the moth and robot movements suggested an acceptable range for sensory-motor processing when the insect system was directly applied to artificial systems. Further evaluations of the insect-controlled robot will provide a 'blueprint' for biomimetic robots and strongly promote the field of biomimetics.

The experimental humanoid robot H7: a research platform for autonomous behaviour

This paper gives an overview of the humanoid robot 'H7', which was developed over several years as an experimental platform for walking, autonomous behaviour and human interaction research at the University of Tokyo. H7 was designed to be a human-sized robot capable of operating autonomously in indoor environments designed for humans. The hardware is relatively simple to operate and conduct research on, particularly with respect to the hierarchical design of its control architecture. We describe the overall design goals and methodology, along with a summary of its online walking capabilities, autonomous vision-based behaviours and automatic motion planning. We show experimental results obtained by implementations running within a simulation environment as well as on the actual robot hardware.

Promoting Interactions Between Humans and Robots Using Robotic Emotional Behavior

The objective of a socially assistive robot is to create a close and effective interaction with a human user for the purpose of giving assistance. In particular, the social interaction, guidance, and support that a socially assistive robot can provide a person can be very beneficial to patient-centered care. However, there are a number of research issues that need to be addressed in order to design such robots. This paper focuses on developing effective emotion-based assistive behavior for a socially assistive robot intended for natural human-robot interaction (HRI) scenarios with explicit social and assistive task functionalities. In particular, in this paper, a unique emotional behavior module is presented and implemented in a learning-based control architecture for assistive HRI. The module is utilized to determine the appropriate emotions of the robot to display, as motivated by the well-being of the person, during assistive task-driven interactions in order to elicit suitable actions from users to accomplish a given person-centered assistive task. A novel online updating technique is used in order to allow the emotional model to adapt to new people and scenarios. Experiments presented show the effectiveness of utilizing robotic emotional assistive behavior during HRI scenarios.

Biologically inspired adaptive walking of a quadruped robot

We describe here the efforts to induce a quadruped robot to walk with medium-walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical and the neural systems by comparing biological concepts with those necessary conditions described in physical terms. PD-controller at joints constructs the virtual spring-damper system as the viscoelasticity model of a muscle. The neural system model consists of a central pattern generator (CPG), reflexes and responses. We validate the effectiveness of the proposed neural system model control using the quadruped robots called 'Tekken1&2'. MPEG footage of experiments can be seen at http://www.kimura.is.uec.ac.jp.

Biped walking robots created at Waseda University: WL and WABIAN family

This paper proposes the mechanism and control of the biped humanoid robots WABIAN-RIV and WL-16. WABIAN-RIV has 43 mechanical degrees of freedom (d.f.): 6 d.f. in each leg, 7 d.f. in each arm, 3 d.f. in each hand, 2 d.f. in each eye, 4 d.f. in the neck and 3 d.f. in the waist. Its height is about 1.89 m and its total weight is 127 kg. It has a vision system and a voice recognition system to mimic some of the capabilities of the human senses. WL-16 consists of a pelvis and two legs having six 1 d.f. active linear actuators. An aluminium chair is mounted on two sets of its telescopic poles. To reduce the large support forces during the support phase, a support torque reduction mechanism is developed, which is composed of two compression gas springs with different stiffness. For the stability of the robots, a compensatory motion control algorithm is developed. This control compensates for moments generated by the motion of the lower limbs, using the motion of the trunk and the waist that is obtained by the zero moment point concept and fast Fourier transform. WABIAN-RIV is able to walk forwards, backwards and sideways, dance, carry heavy goods and express emotion, etc. WL-16 can move forwards, backwards and sideways while carrying an adult weighing up to 60 kg.

Applying cybernetic technology to diagnose human pulmonary sounds

Chest auscultation is a crucial and efficient method for diagnosing lung disease; however, it is a subjective process that relies on physician experience and the ability to differentiate between various sound patterns. Because the physiological signals composed of heart sounds and pulmonary sounds (PSs) are greater than 120 Hz and the human ear is not sensitive to low frequencies, successfully making diagnostic classifications is difficult. To solve this problem, we constructed various PS recognition systems for classifying six PS classes: vesicular breath sounds, bronchial breath sounds, tracheal breath sounds, crackles, wheezes, and stridor sounds. First, we used a piezoelectric microphone and data acquisition card to acquire PS signals and perform signal preprocessing. A wavelet transform was used for feature extraction, and the PS signals were decomposed into frequency subbands. Using a statistical method, we extracted 17 features that were used as the input vectors of a neural network. We proposed a 2-stage classifier combined with a back-propagation (BP) neural network and learning vector quantization (LVQ) neural network, which improves classification accuracy by using a haploid neural network. The receiver operating characteristic (ROC) curve verifies the high performance level of the neural network. To expand traditional auscultation methods, we constructed various PS diagnostic systems that can correctly classify the six common PSs. The proposed device overcomes the lack of human sensitivity to low-frequency sounds and various PS waves, characteristic values, and a spectral analysis charts are provided to elucidate the design of the human-machine interface.

Generation of complex motor patterns in american grasshopper via current-controlled thoracic electrical interfacing

Micro-air vehicles (MAVs) have attracted attention for their potential application to military applications, environmental sensing, and search and rescue missions. While progress is being made toward fabrication of a completely human-engineered MAV, another promising approach seeks to interface to, and take control of, an insect's nervous system. Cyborg insects take advantage of their innate exquisite loco-motor, navigation, and sensing abilities. Recently, several groups have demonstrated the feasibility of radio-controlled flight in the hawkmoth and beetle via electrical neural interfaces. Here, we report a method for eliciting the "jump" response in the American grasshopper (S. Americana). We found that stimulating the metathoracic T3 ganglion with constant-current square wave pulses with amplitude 186 ± 40 μA and frequency 190 ± 13 Hz reproducibly evoked (≥95% success rate) the desired motor activity in N=3 test subjects. To the best of our knowledge, this is the first report of an insect cyborg with a synchronous neuromuscular system.

Development of anthropomorphic multi-D.O.F. master-slave arm for mutual telexistence

We developed a robotic arm for a master-slave system to support "mutual telexistence," which realizes remote dexterous manipulation tasks and close physical communication with other people using gestures. In this paper, we describe the specifications of the experimental setup of the master-slave arm to demonstrate the feasibility of the mutual telexistence concept. We developed the master arm of a telexistence robot for interpersonal communication. The last degree of the 7-degree-of-freedom slave arm is resolved by placing a small orientation sensor on the operators arm. This master arm is made light and impedance control is applied in order to grant the operator as much freedom of movement as possible. For this development stage, we compared three control methods and confirmed that the impedance control method is the most appropriate to this system.

Oscillators and crank turning: exploiting natural dynamics with a humanoid robot arm

This paper presents an approach to robot-arm control that exploits the natural dynamics of the arm. This is in contrast to traditional approaches, which either ignore or cancel out arm dynamics. While the traditional approaches are more general, they often result in systems and robot designs that are not robust. The alternative approach gives systems that are computationally simple, robust to variation in system parameters, robust to changes in the dynamics themselves, and versatile. The approach is examined using the example of a compliant robot arm, controlled by independent neural oscillators, in a crank-turning task. A model is constructed, and the robot behaviour compared with the model. These data show that the arm-oscillator system is exploiting the natural dynamics by finding and exciting the resonant mode of the underlying mechanical system. Since this is a natural behaviour of the system, the robot behaviour is robust. The paper concludes by discussing the opportunities and limitations of this approach.

How to make an autonomous robot as a partner with humans: design approach versus emergent approach

In this paper, we discuss what factors are important to realize an autonomous robot as a partner with humans. We believe that it is important to interact with people without boring them, using verbal and non-verbal communication channels. We have already developed autonomous robots such as AIBO and QRIO, whose behaviours are manually programmed and designed. We realized, however, that this design approach has limitations; therefore we propose a new approach, intelligence dynamics, where interacting in a real-world environment using embodiment is considered very important. There are pioneering works related to this approach from brain science, cognitive science, robotics and artificial intelligence. We assert that it is important to study the emergence of entire sets of autonomous behaviours and present our approach towards this goal.

Overcoming the Confucian Psychological Barrier in Government Cyberspace

The Confucian tradition still dictates the behavior of many people in East Asian countries such as South Korea. Even in e-mail communication, people try their best to show signs of respect which is required by the Confucian tradition. This psychological barrier can be detrimental to the development of democracy as people are educated not to challenge opinions of elders or bosses. After a long military dictatorship, South Korea has emerged as a newly democratized nation where the Confucian tradition is less emphasized. However, this tradition dies hard, and citizens are still afraid of offending government officials who have the power to affect lives of citizens. In light of creating a more democratic society, the e-government project has been implemented, and one of the features of cyber-government is to give citizens a place in cyberspace to express their concerns. Even though citizens have to use their real names, it is found that those who wrote messages in the bulletin board of the city of Seoul government's web pages tend not to use terms that are often used in e-mails for the purpose of expressing respect. A survey was conducted, and results show that people were able to overcome the Confucian psychological barrier in government cyberspace. Self-efficacy is proposed to explain this phenomenon.