A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> To more fully explore the possibility of control of the autonomic nervous system (ANS) in the human S, this study investigated the effects of instructions and exteroeeptive feedback on the control of spontaneous galvanic skin responsivity (GSR). Two sets of instructions (“Relax” and “Think”) were alternately presented to Ss under four types of meter feedback: accurate, positive, negative, and control. In addition to GSR activity, respiration and cardiac rate were recorded. The results indicated that Ss receiving accurate feedback were significantly better able to comply with the “Relax”-“Think” instructions; next most effective was positive feedback, while negative and control feedback were least effective. No within-subject relationships were found between control of spontaneous GSRs and respiration or cardiac activity. The results suggest that Ss are responsive to the consequences of their antonomic behavior in much the same manner as they are responsive to the consequences of other learned behaviors. <s> BIB001 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Methods for realizing three SSF systems for the VA/NU myoelectric hand have been shown. In some cases, estimates concerning amputer acceptance, and references relating to improvements in function, were made. These estimates are purely speculative, and are not intended as a substitute for accurate information which can only be obtained by complete laboratory evaluations of the SSF system codes and by placing the systems on subjects. At this time, it appears that all three of the systems are technically feasible, and that they could be made clinically practical through careful design. <s> BIB002 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> ABSTRACTMore than 6,600 one-page surveys were sent to individuals throughout the country with upper-limb loss or absence. Of those surveys, 2,477 were returned, and demographic information was recorded. A more comprehensive seven-page survey was then sent to the respondents who agreed to participate <s> BIB003 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> In recent years technical innovations have combined to make artificial limbs much more comfortable, efficient, and lifelike than earlier versions. Future innovations are likely to depend on the interaction between three powerful forces—amputees' demands, advances in surgery and engineering, and healthcare funding sufficient to sustain development and application of technological solutions. This article looks at the innovative new prostheses that are currently available and discusses future developments. <s> BIB004 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> BackgroundThe users of today's commercial prosthetic hands are not given any conscious sensory feedback. To overcome this deficiency in prosthetic hands we have recently proposed a sensory feedback system utilising a "tactile display" on the remaining amputation residual limb acting as man-machine interface. Our system uses the recorded pressure in a hand prosthesis and feeds back this pressure onto the forearm skin. Here we describe the design and technical solution of the sensory feedback system aimed at hand prostheses for trans-radial/humeral amputees. Critical parameters for the sensory feedback system were investigated.MethodsA sensory feedback system consisting of five actuators, control electronics and a test application running on a computer has been designed and built. Firstly, we investigate which force levels were applied to the forearm skin of the user while operating the sensory feedback system. Secondly, we study if the proposed system could be used together with a myoelectric control system. The displacement of the skin caused by the sensory feedback system would generate artefacts in the recorded myoelectric signals. Accordingly, EMG recordings were performed and an analysis of the these are included. The sensory feedback system was also preliminarily evaluated in a laboratory setting on two healthy non-amputated test subjects with a computer generating the stimuli, with regards to spatial resolution and force discrimination.ResultsWe showed that the sensory feedback system generated approximately proportional force to the angle of control. The system can be used together with a myoelectric system as the artefacts, generated by the actuators, were easily removed using a simple filter. Furthermore, the application of the system on two test subjects showed that they were able to discriminate tactile sensation with regards to spatial resolution and level of force.ConclusionsThe results of these initial experiments in non-amputees indicate that the proposed tactile display, in its simple form, can be used to relocate tactile input from an artificial hand to the forearm and that the system can coexist with a myoelectric control systems. The proposed system may be a valuable addition to users of myoelectric prosthesis providing conscious sensory feedback during manipulation of objects. <s> BIB005 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Objective. Technologically advanced assistive devices are nowadays available to restore grasping, but effective and effortless control integrating both feed-forward (commands) and feedback (sensory information) is still missing. The goal of this work was to develop a user friendly interface for the semi-automatic and closed-loop control of grasping and to test its feasibility. Approach. We developed a controller based on stereovision to automatically select grasp type and size and augmented reality (AR) to provide artificial proprioceptive feedback. The system was experimentally tested in healthy subjects using a dexterous hand prosthesis to grasp a set of daily objects. The subjects wore AR glasses with an integrated stereo-camera pair, and triggered the system via a simple myoelectric interface. Main results. The results demonstrated that the subjects got easily acquainted with the semi-autonomous control. The stereovision grasp decoder successfully estimated the grasp type and size in realistic, cluttered environments. When allowed (forced) to correct the automatic system decisions, the subjects successfully utilized the AR feedback and achieved close to ideal system performance. Significance. The new method implements a high level, low effort control of complex functions in addition to the low level closed-loop control. The latter is achieved by providing rich visual feedback, which is integrated into the real life environment. The proposed system is an effective interface applicable with small alterations for many advanced prosthetic and orthotic/therapeutic rehabilitation devices. <s> BIB006 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> This paper investigates the motion control of two link (rigid-flexible) manipulator through analysis, computer simulation. An explicit nonlinear dynamic model is developed using assumed mode method. The balance of moments and shear forces are represented by using the boundary conditions. The dynamic model is linearized around the operating point of the system. The linear feedback plus model based feed-forward control is developed as well, based on three different measurements. The joint angles and the tip deflection are used in this study. The control inputs are generated using linear dynamic model. The simulation results of proposed control are compared with those of PD control, in order to show the efficiency of the developed model and the proposed controller. As a future work; the proposed controller will be tested using two link (rigid-flexible) test-rig. <s> BIB007 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> The control of lightweight flexible robot using delayed measurements (i.e. vision sensor measurements) and moving along predefined paths is the focus of this work. The flexible robot dynamics is derived on the basis of a Lagrangian-assumed modes method. Noised and delayed tip deflection vision measurements are used beside the base tracking position for state variables estimation process. In order to generate the required control inputs a special state estimation approach is proposed to overcome noise and time delay and noise problems in the measurements. Two state estimators are suggested for each of the measurements, and the states resulted from these two estimators are combined in order for the end effector to follow the desired response. The one link flexible arm prototype dynamic model is chosen for developing a case study. Extensive simulation results are illustrated and discussed. <s> BIB008 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> This research clarifies the control problem of quadrotor system using PD control. In order to design the control a nonlinear dynamic model of the quadrotor system is derived. The dynamic model contains set of equations valid for hovering. Those set of equations evolved a complex mathematical model with more realistic aerodynamic coefficients and actuator models. Two different control loops are designed in this work to control the motion of the quadrotor system. While the first loop is used to control position of the system; the second loop is utilized to control the orientation. The estimated control inputs are updated based on direct feedback of orientation and the position of the system. The simulation results show the effectiveness of overall systems model and the presented control approach. The work will be expanded later; where off-board test-rig can be used to test the suggested control approach. <s> BIB009 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Electrical stimulation of sensory nerves is a powerful tool for studying neural coding because it can activate neural populations in ways that natural stimulation cannot. Electrical stimulation of the nerve has also been used to restore sensation to patients who have suffered the loss of a limb. We have used long-term implanted electrical interfaces to elucidate the neural basis of perceived intensity in the sense of touch. To this end, we assessed the sensory correlates of neural firing rate and neuronal population recruitment independently by varying two parameters of nerve stimulation: pulse frequency and pulse width. Specifically, two amputees, chronically implanted with peripheral nerve electrodes, performed each of three psychophysical tasks-intensity discrimination, magnitude scaling, and intensity matching-in response to electrical stimulation of their somatosensory nerves. We found that stimulation pulse width and pulse frequency had systematic, cooperative effects on perceived tactile intensity and that the artificial tactile sensations could be reliably matched to skin indentations on the intact limb. We identified a quantity we termed the activation charge rate (ACR), derived from stimulation parameters, that predicted the magnitude of artificial tactile percepts across all testing conditions. On the basis of principles of nerve fiber recruitment, the ACR represents the total population spike count in the activated neural population. Our findings support the hypothesis that population spike count drives the magnitude of tactile percepts and indicate that sensory magnitude can be manipulated systematically by varying a single stimulation quantity. <s> BIB010 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Objective. Tactile feedback is critical to grip and object manipulation. Its absence results in reliance on visual and auditory cues. Our objective was to assess the effect of sensory feedback on task performance in individuals with limb loss. Approach. Stimulation of the peripheral nerves using implanted cuff electrodes provided two subjects with sensory feedback with intensity proportional to forces on the thumb, index, and middle fingers of their prosthetic hand during object manipulation. Both subjects perceived the sensation on their phantom hand at locations corresponding to the locations of the forces on the prosthetic hand. A bend sensor measured prosthetic hand span. Hand span modulated the intensity of sensory feedback perceived on the thenar eminence for subject 1 and the middle finger for subject 2. We performed three functional tests with the blindfolded subjects. First, the subject tried to determine whether or not a wooden block had been placed in his prosthetic hand. Second, the subject had to locate and remove magnetic blocks from a metal table. Third, the subject performed the Southampton Hand Assessment Procedure (SHAP). We also measured the subject's sense of embodiment with a survey and his self-confidence. Main results. Blindfolded performance with sensory feedback was similar to sighted performance in the wooden block and magnetic block tasks. Performance on the SHAP, a measure of hand mechanical function and control, was similar with and without sensory feedback. An embodiment survey showed an improved sense of integration of the prosthesis in self body image with sensory feedback. Significance. Sensory feedback by peripheral nerve stimulation improved object discrimination and manipulation, embodiment, and confidence. With both forms of feedback, the blindfolded subjects tended toward results obtained with visual feedback. <s> BIB011 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Tactile feedback is pivotal for grasping and manipulation in humans. Providing functionally effective sensory feedback to prostheses users is an open challenge. Past paradigms were mostly based on vibro- or electrotactile stimulations. However, the tactile sensitivity on the targeted body parts (usually the forearm) is greatly less than that of the hand/fingertips, restricting the amount of information that can be provided through this channel. Visual feedback is the most investigated technique in motor learning studies, where it showed positive effects in learning both simple and complex tasks; however, it was not exploited in prosthetics due to technological limitations. Here, we investigated if visual information provided in the form of augmented reality (AR) feedback can be integrated by able-bodied participants in their sensorimotor control of a pick-and-lift task while controlling a robotic hand. For this purpose, we provided visual continuous feedback related to grip force and hand closure to the participants. Each variable was mapped to the length of one of the two ellipse axes visualized on the screen of wearable single-eye display AR glasses. We observed changes in behavior when subtle (i.e., not announced to the participants) manipulation of the AR feedback was introduced, which indicated that the participants integrated the artificial feedback within the sensorimotor control of the task. These results demonstrate that it is possible to deliver effective information through AR feedback in a compact and wearable fashion. This feedback modality may be exploited for delivering sensory feedback to amputees in a clinical scenario. <s> BIB012 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Utilization of robotic manipulator with multi-link structure encompasses a great influence in most of the present industries. However, controlling the motion of multi-link manipulator has become a troublesome errand particularly once the flexible structure is employed. As of now, the framework utilizes the complicated arithmetic to resolve desired hub angle with the coupling result and vibration within the framework. Hence, this research aims to develop a dynamic system and controller for double-link flexible robotics manipulator (DLFRM) with the enhancement on hub angle position and vibration concealment. The research utilised neural network because the model estimation supported NARX model structure. In the controllers’ development, this research focuses on self-tuning controller. P-Type iterative learning algorithm (ILA) control theme was enforced to adapt the controller parameters to fulfill the required performances once there is changes to the system. The hybrid of proportional-integral-derivate (PID) controller was developed for hub motion and end-point vibration suppression of every link respectively. The controllers were tested in MATLAB/Simulink simulation setting. The performance of the controller was compared with the fixed hybrid PID-PID controller in term of input tracking and vibration concealment. The results indicated that the proposed controller was effective to maneuver the double-link flexible robotic manipulator to the specified position with reduction of the vibration at the tip of the DLFRM structure. <s> BIB013 </s> A Review of Non-Invasive Haptic Feedback stimulation Techniques for Upper Extremity Prostheses <s> Introduction <s> Stroke is a leading cause of disability which can affect shoulder and elbow movements which are necessary for reaching activities in numerous daily routines. Rehabilitation under the supervision of physiotherapists in healthcare settings is to encourage the recovery process. Unfortunately, these sessions are often labor-intensive and limited intervention time between physiotherapist and the stroke patient due to staff constraints. Dedicated robotic devices have been developed to overcome this issues. However, the high cost of these robots is a major concern as it limits their cost-benefit profiles, thus impeding large scale implementation. This paper presents a simple and portable unactuated interactive rehabilitation device for upper limb rehabilitation purposes. This device has been developed by using a conventional mouse integrated with three interactive training modules, namely the Triangle, Square, and Circle modules intended for training shoulder and elbow movements. Results from five healthy subjects showed the more deviation from the path will be happened when the subject move their hand to the other side of their dominant hand. Besides, the shape of the module that includes combination of X and Y axis direction is more difficult compare to either X or Y axis. <s> BIB014
In spite of the fast progress in medical science over recent decades, patients of upper limb amputation have only little change in the daily life BIB004 . In fact, the amputees thought that most of the upper limb prostheses are still as a hook at the end of the arm  . According to the statistical study that has been made on 2477 amputees of upper limb mutilation BIB003 , the basic requirement of the typical upper limb prostheses are: (i) enable the users to perform their daily life activities with less visual attention required, (ii) allow the patients to manipulate different sizes of objects as easy as possible, and (iii) design a prosthetic hand which has the highest similarity to the healthy human hand in overall appearance and functionality. However, the insufficiency to deliver exteroceptive BIB001 and proprioceptive BIB002 information makes the upper limb prostheses very difficult to control. Nowadays, many research efforts seek to overcome the challenges of the lack of sensation during using the prostheses and enable the amputees to discover their environment through their own prosthetic hands. Some efforts have been made towards examining the ability to use the visual feedback information in performing both simple and complex tasks. To achieve this investigation, a single-eye display augmented reality (AR) feedback was designed and tested with an able-body volunteer to pick and lift objects in simple and complex duties BIB012 BIB006 . The study concluded that the AR feedback sensor has the ability to provide information of grasping force to the amputees in very helpful ways. In addition, the virtual feedback is an effective technique to compensate the lack of sensation, while using the prosthetic robotic hand. On the other hand, the invasive and non-invasive techniques were used for the same purposes. The invasive technique depends on the surgical intervention to access the nervous system of the amputees, and pass the information directly from the tactile sensors to the user's brain. An implanted cuff electrodes external device has been used to generate square, biphasic, and charge balanced pulses that are delivered to the nerves to restore the sensation at the fingertips of the upper limb prostheses BIB010 BIB011 . Most opinions encourage the use of non-surgical intervention (non-invasive technique), in which the lack of sensation at the missing part can be compensated by stimulating other parts of the body using an external stimulus to excite the patients' skin BIB005 . The non-invasive haptic feedback stimulation system usually is coupled with the myoelectric prosthetic hand for improving its controller performance and recovering the sensation. The myoelectric prosthetic drives by the bio-signal, such as the electric muscle activity of the residual limb. A bio-signal is any signal in living beings that can be continually measured and monitored. The muscle activity is usually recorded with surface electromyography (EMG) by electrodes positioned on the residual limb  . Fig. 1 explains the signal flow's block diagram of myoelectric prostheses. The biosignals measured by EMG sensors record and amplify the muscle activity. After analog/digital conversion, the control system processes and interprets the EMG data. The control system's output signal is used to drive the robotic hand by controlling its driving motors. In general, the Lagrange's equation and model expansion method can be utilized to develop the dynamic equations of the prosthetic hand during the design and development stage BIB007 BIB008  BIB013 BIB014 BIB009 . Finally, the position, velocity, acceleration, and the grasping strength of the prosthetic hand can be measured by the sensory system and used as feedback to the controller to enhance its performance.