This chapter presents an experimental study of upper-limb surface EMG signals and two cases of applying surface EMG signals to control an upper-limb exoskeleton robot. The applied method to process surface EMG signals to use as input information to the control method is also explained. At first, surface EMG signal extraction method and processing method are presented in this chap-ter. Then, the upper-limb muscle activities during daily upper-limb motions have been studied to enable exoskeleton robots to estimate human upper-limb motions based on EMG signals of related muscles. The muscle combinations are identified to separate some motions of upper-limb. Minimum number of muscles to extract signals to control frequent daily upper-limb motions has been identified. In the next step, EMG signal of identified muscles are used to control two upper-limb exoskeleton robots. A three degree of freedom (DOF) exoskeleton robot (W-EXOS) for the forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation are controlled by applying the surface EMG signals of six muscles. Surface EMG signals of upper-limb muscles are applied as input information to control a 6DOF exoskeleton robot (SUEFUL-6). In each case of applying EMG signals experiments have been carried out to evaluate the effectiveness of the EMG based control method.

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Teaching physical motions such as riding, exercising, swimming, etc. to human beings is hard. Coaches face difficulties in communicating their feedback verbally and cannot correct the student mid-action; teaching videos are two dimensional and suffer from perspective distortion. Systems that track a user and provide him real-time feedback have many potential applications: as an aid to the visually challenged, improving rehabilitation, improving exercise routines such as weight training or yoga, teaching new motion tasks, synchronizing motions of multiple actors, etc. It is not easy to deliver real-time feedback in a way that is easy to interpret, yet unobtrusive enough to not distract the user from the motion task. I have developed motion feedback systems that provide real-time feedback to achieve or improve human motion tasks. These systems track the user’s actions with simple sensors, and use tiny vibration motors as feedback devices. Vibration motors provide feedback that is both intuitive and minimally intrusive. My systems’ designs are simple, flexible, and extensible to large-scale, full-body motion tasks. The systems that I developed as part of this thesis address two classes of motion tasks: configuration tasks and trajectory tasks. Configuration tasks guide the user to a target configuration. My systems for configuration tasks use a motion-capture system to track the user. Configuration-task systems restrict the user’s motions to a set of motion primitives, and guide the user to the target configuration by executing a sequence of motion-primitives. Trajectory tasks assume that the user understands the motion task. The systems for trajectory tasks provide corrective feedback that assists the user in improving their performance. This thesis presents the design, implementation, and results of user experiments with the prototype systems I have developed.

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In this paper, the kinematic analysis of constructed assistive robotic leg for rehabilitation of patients who encounter the neurological injury is presented. In order to design an efficient new mechanism, studies were carried out to distinguish the human architec-ture and dynamics. In the study, the motion of a healthy physical subject in walking situation of 1 km/h speed was recorded. Thereafter, a novel robotic leg mechanism was developed to produce similar motion. The robotic leg is driven by a single actuator to drive both the hip and the knee joints mechanism. In order to verify the robot motion with respect to human motion, kinematic analysis of all robot’s joints and links are formulated and are simulated in MATLAB software. The results obtained from the kinematic analy-sis of the developed assistive robotic system show that its motion conforms to the motion and dynamics of a healthy human.

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The paper aims to present the actual status of military robots development by Romanian military Research and Development in the context of today’s warfare and military operations.

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A large proportion of patients with spinal cord injury (SCI) regain ambulatory function. However, during the first 3 months most of the patients are not able to walk unsupported. To enable ambulatory training at such an early stage the body weight is partially relieved and the leg movements are assisted by two therapists. A more recent approach is the application of robotic based assis-tance which allows for longer training duration. From motor learning science and studies including patients with stroke, it is known
that training effects depend on the duration of the training. Longer trainings result in a better walking function. The aim of the present study is to evaluate if prolonged robot assisted walking training leads to a better walking outcome in patients with in-complete SCI and whether such training is feasible or has undesirable effects. Methods/Design: Patients from multiple sites with a subacute incomplete SCI and who are not able to walk independently will be randomized to either standard training (3-5 sessions per week, session duration maximum 25 minutes) or an intensive training (3-5 sessions per week, session duration minimum 50 minutes). After 8 weeks of training and 4 months later the walking ability, the occurrence of adverse events and the perceived rate of exer-tion as well as the patients’ impression of change will be compared between groups

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