Combination of Flex Sensor and Electromyography for Hybrid Control Robot

The alternative control methods of robot are very important to solved problems for people with special needs. In this research, a robot arm from the elbow to hand is designed based on human right arm. This robot robot is controlled by human left arm. The positions of flex sensors are studied to recognize the flexion-extension elbow, supination-pronation forearm, flexion-extension wrist and radial-ulnar wrist.The hand of robot has two function grasping and realeasing object. This robot has four joints and six flex sensors are attached to human left arm. Electromyography signals from face muscle contraction are used to classify grasping and releasing hand. The results show that the flex sensor accuracy is 3.54° with standard error is approximately 0.040 V. Seven operators completely tasks to take and release objects at three different locations: perpendicular to the robot, left-front and right-front of the robot. The average times to finish each task are 15.7 ssecond, 17.6 second and 17.1 second. This robot control system works in a real time function. This control method can substitute the right hand function to do taking and releasing object tasks

Monitoring muscle fatigue following continuous load changes

Department of Human Factors EngineeringPrevious studies related to monitoring muscle fatigue during dynamic motion have focused on detecting the accumulation of muscle fatigue. However, it is necessary to detect both accumulation and recovery of muscle fatigue in dynamic muscle contraction while muscle load changes continuously. This study aims to investigate the development and recovery of muscle fatigue in dynamic muscle contraction conditions following continuous load changes. Twenty healthy males conducted repetitive elbow flexion and extension using 2kg and 1kg dumbbell, by turns. They performed the two tasks of different intensity (2kg intensity task, 1kg intensity task) alternately until they felt they could no longer achieve the required movement range or until they experienced unacceptable biceps muscle discomfort. Meanwhile, using EMG signal of biceps brachii muscle, fatigue detections were performed from both dynamic measurements during each dynamic muscle contraction task and isometric measurements during isometric muscle contraction right before and after each task. In each of 2kg and 1kg intensity tasks, pre, post and change value of EMG amplitude (AEMG) and center frequency were computed respectively. They were compared to check the validity of the muscle fatigue monitoring method using Wavelet transform with EMG signal from dynamic measurements. As a result, a decrease of center frequency in 2kg intensity tasks and an increase of center frequency in 1kg intensity tasks were detected. It shows that development and recovery of muscle fatigue were detected in 2kg and 1kg intensity tasks, respectively. Also, the tendency of change value of center frequency from dynamic measurements were corresponded with that from isometric measurements. It suggests that monitoring muscle fatigue in dynamic muscle contraction conditions using wavelet transform was valid to detect the development and recovery of muscle fatigue continuously. The result also shows the possibility of monitoring muscle fatigue in real-time in industry and it could propose a guideline in designing a human-robot interaction system based on monitoring user's muscle fatigue.clos

Programming the KUKA iiwa Robot for Use of Rehabilitation in Health Care

Práce se zabývá problematikou asistované rehabilitace za pomoci průmyslových robotů. Představuje základní rehabilitační metody a seznamuje s existujícími kolaborativními průmyslovými roboty na trhu, které by mohli být pro účely rehabilitace použity. Představuje i konkrétní robotická rehabilitační řešení. Dále uvádí normy vztahující se k použití technických prostředků ve zdravotnictví a také ke kolaborativním robotům v kontaktu s člověkem. Mimo to obsahuje také vlastní návrh rehabilitačního řešení aplikovaném na robotovi KUKA LBR iiwa.This thesis is focused on the topic of assisted rehabilitation withthe use of industrial collaborative robots. It also presents basic methods of regular rehabilitation and the already existing collaborative industry robots on the market, which could be used for the purpose of rehabilitation. It also contains specific robotic solutions for rehabilitation. Then it presents standards related to the use of medical devices and also to collaborative robots in interaction with a human. In addition, this thesis also introduces a proposition of its own rehabilitation solution applied by the KUKA LBR iiwa