Review on Tactile Sensory Feedback of Prosthetic Hands for the Upper-Limb Amputees by Sensory Afferent Stimulation

Loss of sensory function for upper-limb amputees inevitably devastates their life qualities, and lack of reliable sensory feedback is the biggest defect to sophisticated prosthetic hands, greatly hindering their usefulness and perceptual embodiment. Thus, it is extremely necessary to accomplish an intelligent prosthetic hand with effective tactile sensory feedback for an upper-limb amputee. This paper presents an overview of three kinds of existing sensory feedback approaches, including cutaneous mechanical stimulation(CMS), transcutaneous electrical nerve stimulation(TENS) and direct peripheral nerve electrical stimulation(DPNES). The emphasis concentrates on major scientific achievements, advantages and disadvantages. The TENS on the skin areas with evoked finger sensation(EFS) at upper-limb amputees' residual limbs might be one of the most promising approaches to realize natural sensory feedback.

Application of Forearm FMG signals in Closed Loop Modality-matched Sensory Feedback Stimulation

This study is aimed at exploring a technology that can use the human physiological information,such as Force Myography(FMG)signals to provide sensory feedback to prosthetic hand users.This is based on the principle that with the intent to move the prosthetic hand,the existing limbs in the arm recruit specific group of muscles.These muscles react with a change in the cross-sectional area;piezoelectric sensors placed on these muscles will generate a voltage(FMG signals),in response to the change in muscle volume.The correlation between the amplitude of the FMG signals and intensity of pressure on fingertips during grasping is then computed and a dynamic relation(model)is established through system identification in MATLAB.The estimated models generated a fitting accuracy of more than 80%.The model is then programmed into the Arduino microcontroller,so that a real-time and proportional force feedback is channeled to amputees through a micro actuator.Obtaining such percentages of accuracy in sensory feedback without relying on touch sensors on the prosthetic hand that could be affected by mechanical wear and other interaction factors is promising.Applying advanced signal processing and classification techniques may also refine the findings to better capture and correlate the force variations with the sensory feedback.

Platelet-rich plasma for regeneration of neural feedback pathways around dental implants: a concise review and outlook on future possibilities

Along with the development of new materials, advanced medical imaging and surgical techniques, osseointegrated dental implants are considered a successful and constantly evolving treatment modality for the replacement of missing teeth in patients with complete or partial edentulism. The importance of restoring the peripheral neural feedback pathway and thus repairing the lack of periodontal rnechanoreceptors after tooth extraction has been highlighted in the literature. Nevertheless, regenerating the nerve fibers and reconstructing the neural feedback pathways around osseointegrated implants remain a challenge. Recent studies have provided evidence that platelet-rich plasma （PRP） therapy is a promising treatment for musculoskeletal injuries. Because of its high biological safety, convenience and usability, PRP therapy has gradually gained popularity in the clinical field Although much remains to be learned, the growth factors from PRP might play key roles in peripheral nerve repair mechanisms. This review presents known growth factors contributing to the biological efficacy of PRP and illustrates basic and （pre-）clinical evidence regarding the use of PRP and its relevant products in peripheral nerve regeneration. In addition, the potential of local application of PRP for structural and functional recovery of iniured peripheral nerves around dental implants is discussed.

Control of myoelectric prosthetic hand with a novel proximity-tactile sensor

Currently, prosthetic hands can only achieve several prespecified and discrete hand motion patterns from popular myoelectric control schemes using electromyography(EMG) signals. To achieve continuous and stable grasping within the discrete motion pattern, this paper proposes a control strategy using a customized, flexible capacitance-based proximity-tactile sensor. This sensor is integrated at the fingertip and measures the distance and force before and after contact with an object. During the pregrasping phase, each fingertip’s position is controlled based on the distance between the fingertip and the object to make all fingertips synchronously approach the object at the same distance. Once contact is established, the sensor turns to output the tactile information, by which the contact force of each fingertip is finely controlled. Finally, the method is introduced into the human-machine interaction control for a myoelectric prosthetic hand. The experimental results demonstrate that continuous and stable grasping could be achieved by the proposed control method within the subject’s discrete EMG motion mode. The subject also obtained tactile feedback through the transcutaneous electrical nerve stimulation after contact.

An anthropomorphic controlled hand prosthesis system

Based on HIT/DLR(Harbin Institute of Technology/Deutsches Zentrum für Luft-und Raumfahrt) Prosthetic Hand II,an anthropomorphic controller is developed to help the amputees use and perceive the prosthetic hands more like people with normal physiological hands.The core of the anthropomorphic controller is a hierarchical control system.It is composed of a top controller and a low level controller.The top controller has been designed both to interpret the amputee's intensions through electromyography(EMG) signals recognition and to provide the subject-prosthesis interface control with electro-cutaneous sensory feedback(ESF),while the low level controller is responsible for grasp stability.The control strategies include the EMG control strategy,EMG and ESF closed loop control strategy,and voice control strategy.Through EMG signal recognition,10 types of hand postures are recognized based on support vector machine(SVM).An anthropomorphic closed loop system is constructed to include the customer,sensory feedback system,EMG control system,and the prosthetic hand,so as to help the amputee perform a more successful EMG grasp.Experimental results suggest that the anthropomorphic controller can be used for multi-posture recognition,and that grasp with ESF is a cognitive dual process with visual and sensory feedback.This process while outperforming the visual feedback process provides the concept of grasp force magnitude during manipulation of objects.

Regenerative peripheral nerve interfaces(RPNIs):current status and future direction

Despite significant advancements in neuroprosthetic control strategies,current peripheral nerve interfacing techniques are limited in their ability to facilitate accurate and reliable long-term control.The regenerative peripheral nerve interface(RPNI)is a biologically stable bioamplifier of efferent motor action potentials with demonstrated long-term stability.This innovative,straightforward,and reproducible surgical technique has shown enormous potential in improving prosthetic control for individuals with upper limb amputations.The RPNI consists of an autologous free muscle graft secured around the end of a transected peripheral nerve or individual fascicles within a residual limb.This construct facilitates EMG signal transduction from the residual peripheral nerve to a neuroprosthetic device using indwelling bipolar electrodes on the muscle surface.This review article focuses on the development of the RPNI and its use for intuitive and enhanced prosthetic control and sensory feedback.In addition,this article also highlights the use of RPNIs for the prevention and treatment of postamputation pain.