Query: Hemiplegia　finger robot

title: Design of Finger Bending Angle Detection System and FES System Based on Finger Wrist Rehabilitation Robot
abstract: At present, in the China, the incidence of stroke hemiplegia in the elderly population is relatively high and still on the rise. Therefore, rehabilitation treatment for hemiplegia in the elderly is particularly important. However, the traditional rehabilitation treatment focuses on the functional training of the patient's wrist and finger joints, ignoring the importance of neurological rehabilitation in the early hemiplegia stage. In this paper, On the basis of the traditional rehabilitation of finger movement function, we added the rehabilitation training of wrist joint. a new type of wrist and knuckle rehabilitation robot is proposed, The finger bending angle detection system and the FES(Functional Electrical Stimulation) system are built. The bending angle data detected by the bending angle data glove is used to control the FES functional power of the other finger. The bending Angle data of the fingers on the healthy side were detected by using the bending Angle data glove. To control the stimulation intensity of the FES functional electrical stimulation device of the finger on the affected side, So as to control the intensity of muscle contraction and the Angle of finger bending.

title: EEG based neurofeedback training with shoulder exoskeleton robot assistance triggered by the contralesional primary motor cortex activity in poststroke patients with severe chronic hemiplegia
abstract: Recent clinical studies have shown that electroencephalogram (EEG) based neurofeedback training promotes functional recovery of finger movements in poststroke patients (Pichiorri F et al.  2015) However, impairment of shoulder elevation in poststroke severe chronic hemiplegia is a debilitating condition with no evidence based, accessible treatment. To verify motor recovery evidence of neurofeedback training with our shoulder exoskeleton robot, this study reports upper extremity section of Fugl Meyer assessment (FMA UE) associated with the evaluation of up conditioning of contralesional corticospinal pathways.  Eight poststroke patients with severe hemiplegia in the chronic stage were recruited (FMA UE score 16.8 4.4) Patients engaged in 1 hour daily training for 7 consecutive days Fig. 1 and clinical and neurophysiological measurements were performed 1 day before and after the intervention. FMA UE was used for the primary outcome measure. A 128 channel whole head EEG was used to assess the hemispheric lateralization of event related desynchronization (ERD) Single pulse transcranial magnetic stimulation (TMS) was applied to the contralesional primary motor cortex to assess the corticospinal excitability in 6 tested patients.  All participants finished the intervention without adverse events. FMA UE was significantly improved after the intervention (paired t test, P  The results from this study demonstrated targeted up conditioning of contralesional corticospinal pathways and efficacy of neurofeedback training with our shoulder exoskeleton robot.

title: Measurement of Immediate Effect by Therapeutic Electrical Stimulation Using a New Desktop Rehabilitation Robot
abstract: More frequent use of robot technology in the field of rehabilitation is driving the need for smaller, less cumbersome devices. The objectives of the present study were to evaluate and compare quantitatively the upper limb function of chronic stroke patients before and after therapeutic electrical stimulation using a newly developed rehabilitation robot.  Five stroke patients (3 men, 2 women; mean age: 66.4 9.6 years; time since stroke: 36.0 52.9 months) in the sub acute and chronic phase of stroke induced hemiplegia (induced by cerebral hemorrhage in four and by cerebral infarction in one; Brunnstrom stages III V) participated in the study. None of them had any secondary motor neuron dysfunction or unstable disease control. Before and after 15 min of therapeutic electrical stimulation for repeated finger flexion and extension, participants performed reaching movements while moving the rehabilitation robot with their affected hand. Assessment parameters included Maximum swerve, Average speed, and smoothness of movements, as calculated by Jerk cost X (right left direction) and Jerk cost Y (forward backward direction)  All patients were able to use the rehabilitation robot to perform the reaching movements. Clear differences were observed before and after therapeutic electrical stimulation for Maximum swerve and Average speed in the X direction, and there was a tendency for Jerk cost X to differ before and after therapeutic electrical stimulation. In contrast, there were no significant differences in either Jerk cost Y or Average speed in the Y direction before and after the stimulation.  The immediate effects of therapeutic electrical stimulation in chronic stroke patients can be quantified using our newly developed rehabilitation robot. Successful quantification of the effects of therapeutic electrical stimulation in stroke patients using smaller robotic systems could revolutionize the rehabilitation of these and other patients suffering from motor dysfunction or paralysis.

title: Toward Grasping Against the Environment: Locking Polygonal Objects Against a Wall Using Two Finger Robot Hands
abstract: Caging offers a robust strategy for grasping objects with robot hands. This letter utilizes caging for locking polygonal objects against a wall using minimalistic two finger robot hands. From the object's perspective, the wall and two finger hand form an equivalent three finger hand. The object is first caged by trapezoidal finger formations of the equivalent three finger hand, and the hand is then closed until the object is locked against the wall in the desired grasp. The object can then be safely grasped and moved away from the wall, or it can be held fixed against it to be worked on by tools. This letter presents a novel and efficient caging to locking algorithm. While the equivalent hand's configuration space is four dimensional, the algorithm uses the hand's two dimensional contact space, which represents all contacts by two and three of the equivalent hand's fingers along the object boundary. The problem of computing the critical cage formation that allows the object to escape the equivalent hand is reduced to a search along a caging graph constructed incrementally in the equivalent hand's contact space. Starting from the desired locking grasp, the graph is searched for an escape path which passes through the critical cage formation. The technique is demonstrated with a detailed example.

title: Anticipatory effect of execution on observation: an approach using ExoPinch finger robot
abstract: This study aims to explore the mirror neuron system (MNS) involvement using mu (8 12 Hz)/beta (15 25 Hz) band suppression in an action observation execution paradigm.  Electrophysiological (EEG) data from 16 electrodes were recorded while 8 participants observed video clips of a hand squeezing a spring. Specifically, the effect of anticipated execution on observation was studied. For this purpose, a fully actuated finger exoskeleton robot was utilized to synchronize observation and execution and to control the execution condition for the participants. Anticipatory effect was created with a randomized robot accompany session.  The results showed that the observational condition (with or without anticipation) interacted with hemisphere at central channels near somatosensory cortex. Additionally, we explored the response of MNS on the kinetics features of visual stimuli (hard or soft spring)  The results showed an interaction effect of kinetics features and hemisphere at frontal channels corresponding nearly to the ventral premotor cortex area of the brain. The activation of mirror neurons in this area plays a crucial role in observational learning. Based on our results, we propose that specific type of visual stimuli can be combined with the functional abilities of the MNS in the action observation based treatment of hand motor dysfunction of stroke patients to have a positive additional impact.

title: Object Grabbing With A Five Finger Robot Hand Using Two Camera Vision
abstract: This paper discusses the problem of visual based object grabbing using a five finger robotic hand connected to a 4 DOF manipulator on an intelligent mobile robot. The CamShift algorithm is used to analyze the dynamic vision acquired by a pair of stereo cameras in three dimension space. Afterwards, inverse and forward kinematics of manipulator and fingers are performed to drive the robot hand to appropriate position and grab a cup. In addition, a coordinate estimation correction method was proposed to improve the accuracy of the calculated position. The proposed method is validated in several experiments.

title: Randomized Controlled Trial of Gait Training Using Gait Exercise Assist Robot (GEAR) in Stroke Patients with Hemiplegia.
abstract: This trial aimed to validate the effectiveness of using the Gait Exercise Assist Robot (GEAR) in patients with hemiplegia after primary stroke.  The study design was open label randomized controlled trial. Twenty six patients with hemiplegia after primary stroke admitted to the comprehensive inpatient rehabilitation wards were enrolled and randomized to a group using GEAR in gait training and a control group. The intervention period was 4 weeks. Evaluations were conducted at admission, during intervention period, 8 weeks from start of intervention, and at discharge. Primary outcome measure was improvement efficiency of Functional Independence Measure (FIM) walk score (FIM walk improvement efficiency) that was calculated at the time of achieving FIM walk score 5 (supervision level) during the intervention period or as weekly gain in FIM walk score during 4 weeks for those who did not achieve score 5.  FIM walk improvement efficiency was .7 .4 in GEAR group and .4 .3 in control group, and was significantly higher in GEAR group (P .01) The FIM walk score gain after 4 weeks was significantly higher in the GEAR group (P .01) but there were no significant differences between 2 groups after 8 weeks and at discharge.  Gait training using GEAR for 4 weeks improved walking ability of subacute stroke patients. GEAR contributes to early improvement of walking ability probably by the knee flexion assist during swing phase on the paralyzed side thereby increasing the volume of training, and by the finely adjustable stance/swing assist mechanism for the paralyzed limb which optimizes the training difficulty level.

title: An articulated finger driven by single mode piezoelectric actuator for compact and high precision robot hand.
abstract: In this paper, a novel finger driven by single mode piezoelectric actuator for a compact and high precision robot hand is proposed. Three piezoelectric actuators are articulated by two sets of connecting elements to form the finger. The finger utilizes a single model of the piezoelectric actuator to generate friction force to drive the joint. Without the difficulty to adjust for the coincidence of modal frequencies, the design of the piezoelectric actuator has fewer restrictions on size and structure; thus, the finger has a compact structure. The bidirectional motion of the joint is achieved by changing the temporal phase difference of two excitation signals applied on the two adjacent piezoelectric actuators. In addition, due to the characteristics of piezoelectric drive, such as power cut self locking and quick response, the finger has a high resolution to realize micromanipulation for high precise movement. In our design, the first order longitudinal vibration mode of the piezoelectric actuator is used to generate the friction force. By using a finite element model, the geometric parameters of the piezoelectric actuator are obtained. A prototype of the finger is fabricated and experimentally investigated, the size (111 x 10 x 10 mm) is approximately 1.5 times that of a human middle finger, and the weight is 0.11 kg. The experimental results indicate that the angular speed of the prototype reaches 6.6 rad/s, the resolution is 20 mrad, and the startup and shutdown response times are 26 ms and 7 ms under a voltage of 400 Vpp, respectively. The fingertip force is 0.27 N under a voltage of 400 Vpp. The proposed finger has a compact size and simple structure with a high resolution (20 mrad)

title: Continuous Sensing Ability of Robot Finger Joints with Tactile Sensors
abstract: Human symbiotic robots are required to support daily activities of aging societies. However, deficient sensing ability on the current robot hands makes it difficult to perform grasping actions and efficiently accomplish manipulation tasks. Therefore, sufficient data and higher sensing ability are required for operating robot hands. In this research, a new robot finger mechanism is developed. This mechanism has the center of rotation located about the edge of the soft skin. The finger is actuated with an arrangement of a slider, linear motor, and a link mechanism. Hereby, robot finger can attach flexible skin and sensor continuously. Also, sensing ability comparison of other robot finger and the new finger with proposed mechanism is evaluated. As a result, the ability of proposed finger mechanism is confirmed.

title: Design and Kinematics Analysis of a Bionic Finger Hand Rehabilitation Robot Mechanism
abstract: The rehabilitation process of human fingers is a coupling movement of wearable hand rehabilitation equipment and human fingers, and its design must be based on the kinematics of human fingers. In this paper, the forward kinematics and inverse kinematics models are established for the index finger. Kinematics analysis is carried out. Then a bionic finger rehabilitation robot is designed according to the movement characteristics of the finger, A parallelogram linkage mechanism is proposed to make the joint independent drive, realize the flexion/extension movement, and perform positive kinematics and inverse kinematics analysis on the mechanism. The results show that it conforms to the kinematics of the index finger and can be used as the mechanism model of the finger rehabilitation robot.