Bionic Research Articles

Numerical Modelling of a Pulsating Flow Generator for Simulating Blood Pressure

Abstract Hypertension is a leading risk factor that deserves to be taken seriously, therefore researches on blood pressure measurement play a critical role. In this work, a liquid-operated pulsating flow circulation system with a bionic arm is set as a blood pressure simulator and a related numerical model is built to analyse the flow under different settings. The motion patterns of the flow generator and the medium used are two of the main factors discussed in this work. By comparing the pressure curves under different conditions and actual experimental data, the numerical model is validated, and so as to find the suitable parameters of the actual system.

Low-Cost EMG Based Bionic ARM using Servo Motor and Arduino

Robotics is one of the technological advancement in the field of both medical and engineering. The main idea of this project is to change the standpoint of remote controlled robotic arms to manually controlled bionic arms. The primary goal of his project is to create a rehabilitation device that can help an upper arm amputee to attain their day-to-day tasks. This project is based on the design and development of the 3D printed arm structure. The whole system is the association of electrodes controlled by the EMG sensor that is attached to the 3D printed arm. This robotic bionic arm is developed using Arduino, EMG sensor, servo motor and MLX temperature sensor. The tension that are generated by the muscle contraction and relaxation results in the voltage level variation. On the bases of the different values obtained, the threshold value is sampled and the bionic arms fingers close, open, pick and place the objects according to the muscle movements. This technology not only used as prosthesis by the upper arm amputee patients, but also has its many favorable applications in the field of surgical operations like doctor operating a patient with the help of robotic arms rather than his own hands, humanoid robotics, etc.

Electromyography Sensor Controlled Bionic Hand for Disabled Persons

The word “Bionic” is amalgam of domain Biology as well as Electronics. In today’s era, we come across new emerging technology which is rapidly evolving. Bionic hand is one of its kinds. However, with upgrade technology the demand for bionic hand will continue to increase day by day in upcoming years with wider awareness. The major purpose behind the project is to help an individual to improve the sensation, integration with the body and the control. The development and operation of bionic hand has been explained and controlled by Electromyography Muscle Sensor. Signals from an amputee muscle are gathered by bionic arms to function. The muscle sensor is the main component which senses electrical activity of our muscles and translate those activity which results in flexing of finger with the help of servo motors. 3-D printing is used in the design and construction of the bionic arm. The result we obtain here after demonstration is 80% movement of little finger, ring finger, middle finger and fore finger as well as 30% movement of Thumb finger. Along with this when pressure is strongly applied, the signals from the muscle goes to the sensor and hence result in approximate 75% movement of all five fingers together.

High Performance Proprioceptive Fiber Actuators Based on Ag Nanoparticles-Incorporated Hybrid Twisted and Coiled System.

Thermally driven fiber actuators are emerging as promising tools for a range of robotic applications, encompassing soft and wearable robots, muscle function restoration, assistive systems, and physical augmentation. Yet, to realize their full potential in practical applications, several challenges, such as a high operational temperature, incorporation of intrinsic self-sensing capabilities for closed-loop feedback control, and reliance on bulky, intricate actuation systems, must be addressed. Here, an Ag nanoparticles-based twisted and coiled fiber actuator that achieves a high contractile actuation of ≈36% is reported at a considerably low operational temperature of ≈83°C based on a synergistic effect of constituent fiber elements with low glass transition temperatures. The fiber actuator can monitor its contractile actuation in real-time based on the piezoresistive properties inherent to its Ag-based conductive region, demonstrating its proprioceptive sensing capability. By exploiting this capability, the proprioceptive fiber actuator adeptly maintains its intended contractile behavior, even when faced with unplanned external disturbances. To demonstrate the capabilities of the fiber actuator, this study integrates it into a closed-loop feedback-controlled bionic arm as an artificial muscle, offering fresh perspectives on the future development of intelligent wearable devices and soft robotic systems.

Interactive control algorithm for shoulder-amputated prosthesis and object based on reinforcement learning

As a prosthesis made to compensate for the residual loss of the amputee’s limb, the shoulder disarticulation upper limb prosthesis replaces the missing arm function of the shoulder amputee to a certain extent. However, the current upper limb prosthesis mainly interacts with the outside world through the prosthetic hand for grasping and gripping, and the interaction between other parts and the environment is often neglected, which is not in line with the use habits of the human arm. To address this problem, this paper proposes a reinforcement learning–based method for controlling the forearm interaction of a shoulder-disconnected upper limb prosthesis, and analyzes and solves the forces during the interaction, reducing the impact of uncertainty on interaction actions and accelerating training while ensuring the stability of handheld items. We evaluated the performance of the control method during the interaction between the upper limb prosthesis and the external environment through simulation experiments. After the training, the bionic arm was able to push the object into the target range for different objects and pushing distance requirements, which showed the good control effect of the method. Also, the control method can be applied to improve the interaction between the robotic arm and the environment.

Design of a Bionic Arm using EMG Signal Processing and Artificial Intelligence

Design of a Bionic Arm using EMG Signal Processing and Artificial Intelligence

Design Approach Of A Gesture And Emg(Electromyography) Controlled Bionic Arm

Design Approach Of A Gesture And Emg(Electromyography) Controlled Bionic Arm

Joint Effort: A new above-elbow bionic arm can control every finger.

Joint Effort: A new above-elbow bionic arm can control every finger.

Google Trends Analysis of Peripheral Nerve Disease and Surgery

Despite advances in the surgical management of peripheral nerve pathologies over the past several decades, it is unknown how public awareness of these procedures has changed. We hypothesize that Google searches for peripheral nerve surgery have increased over time. Google Trends was queried for search volumes of a list of 40 keywords related to the following topics in peripheral nerve surgery: spasticity, nerve injury, prosthetics, and nerve pain. Monthly relative search volume over the first 5years of the study period (2010-2014) was compared with that of the last 5years (2018-2022) of the study period. Search volumes for keywords "nerve injury," "nerve laceration," "peripheral nerve injury," "nerve repair," "nerve transfer", "neuroma," "neuroma pain," "nerve pain," "nerve pain surgery," and "neuroma pain surgery" all increased more than 10% points in relative search volume over the study period (P < 0.0001 for each keyword). In contrast, searches for "rhizotomy," "spasticity surgery," "targeted muscle reinnervation," "bionic arm," and "myoelectric prosthesis" either decreased or remained stable. Technical terms such as "selective neurectomy," "hyperselective neurectomy," "regenerative peripheral nerve interface," and "regenerative peripheral nerve interface surgery" did not have adequate search volume to be reported by Google Trends. The increase in Google searches related to nerve injury and pain between 2010 and 2022 may reflect increasing public recognition of these clinical entities and surgical techniques addressing them. Technical terms relating to nerve pain are infrequently searched, surgeons should use plain English terms for online discovery. Interest in spasticity and myoelectric prosthetics remains stable, indicating an opportunity for better public outreach.

DDPG-based controlling algorithm for upper limb prosthetic shoulder joint

ABSTRACT The development of intelligent prostheses has effectively improved the life of amputees. However, the current prosthetics mainly focus on restoring the basic mobility of amputees, without considering the use habits of the wearer and the diversity of arm movements, which makes the unknown interference and complex control requirements in daily life an obstacle to the use of prosthetics. To solve this problem, this paper proposes a combination method of adaptive control algorithms of bionic arm shoulder joint based on DDPG to realise intelligent control of the shoulder joint of upper limb prosthesis. Based on using adaptive control to reduce the interference of external variables, the accuracy of the joint module system is improved through reinforcement learning. The results show that the controller has a good effect on improving the dynamic performance of the mechanical system and can be widely used in bionic mechanical control.

Development of 3D Printed Bionic Arm Controlled by EMG Sensor

Development of 3D Printed Bionic Arm Controlled by EMG Sensor

Adaptive Control for Joint Module of Bionic Arms

Minimizing the influence of unknown external disturbances while satisfying complex control requirements in daily life is one of the difficulties of bionic arm control. However, the control of modular joints often ignores the dynamic characteristics and coupling relationship of the system, which can not meet the control requirements of a bionic arm prosthesis. In addition, the large vibration caused by unknown interference is not conducive to human-computer interaction. In order to solve this problem, we proposed an adaptive feedback control (AFC) method based on magnetic field-oriented control for the joint module to realize intelligent control of the bionic arm. The disturbance of the joint module is obtained by real-time parameter calculation. At the same time, the controller regulated the output voltage to eliminate the influence of uncertain disturbances. Theoretical analysis and simulation results show that the controller has a good effect on improving the dynamic performance of the joint module system, and maintaining the stability of the system in the interference, satisfying the requirements of bionic arm control.

REVIEW ON RECENT ADVANCEMENTS IN BIONICARM

Bionic arm has been a prime example of bending technology to improve the lives of amputees. This paper aims to study bionic arm and its developments through the years. The paper primarily focuses on the ‘mechanical-human spectrum’ and its implications on the feasibility of the arm. This paper also highlights the various actuation systems used in practice which are a key component of the arm. When feedback is provided to any system its performance is enhanced, this is also true in case of the arm and the paper describes all aspects related to it

Real Time Prosthetic Hand

Electromyography (EMG) is a biomedical signal which is recorded from muscle. It can detect muscle movements. By using HMI (human machine interfacing), EMG can be used to control prosthetic arms by an amputee individual. A 3D printable design for a myoelectric prosthetic arm is presented. The arm is actuated and controlled by a user flexing his/her muscles. The bionic arm presented has the potential to be used by an amputee or person born without a limb. This type of technology does exist although it is expensive and generally not available to people in developing countries. Rapid growth and advancement of the 3D printing industry allows individuals to become small scale producers. Advancements in 3D printed prosthetic arm are attached to victims during war throughout North Africa. These devices are purely mechanical and less complex compare to myoelectric devices. We can see that 3D printed devices have the potential to positively impact people’s lives. 3D printing does have its limitations but growth and development will lead to upgradation during time.

A Multifunctional Light-Driven Swimming Soft Robot for Various Application Scenarios.

The locomotor behavior of creatures in nature can bring a lot of inspiration for the fabrication of soft actuators. In this paper, we fabricated a bionic light-driven swimming soft robot that can perform grasping of tiny objects and achieve the task of object transfer. By adding carbon nanotubes (CNTs), the temperature-sensitive hydrogels can be endowed with light-responsive properties. The fabricated composite hydrogel structure can control the contraction and expansion of volume by light, which is similar to the contraction and diastole behavior of muscles. The oscillation of the fish tail and the grasping action of the normally closed micromanipulator can be achieved by the control of the irradiation of the xenon light source. The bending of the bionic arm can be controlled by the irradiation of a near-infrared (NIR) laser, which transforms the spatial position and posture of the micromanipulator. The proposed scheme is feasible for miniaturized fabrication and application of flexible actuators. This work provides some important insights for the study of light-driven microrobots and light-driven flexible actuators.

Bionic Arm Using Muscle Sensor

Abstract: In this paper, we have presented design and implementation of a 3D printed electromyography based bionic arm, having potential to be used by an upper limb amputee. The user flexes his or her muscles to electronically activate and control the arm. Our main goal was to obtain the fundamental control of the hand at a cost which makes bionic arm accessible to amputees with economic constraints. Although this technology is employed in a number of commercially available prosthetic arms in the global market, but they are not budget-friendly. We have analysed and investigated the several actuation techniques and design parameters used in the commercially available prosthetic hands. Electromyography (EMG) controlled Pulse Width Modulated (PWM) technique has been used for the actuation of servomotors using the microcontroller. The finished 3D model was created using PLA (polylactic acid), and the findings about the mechanical parameters have been briefly mentioned in the paper. This work includes elements from various engineering fields, including Biomechatronics, sensors, transducers, feedback, and control system. A creative mechanical design for a 3D printed prosthetic arm is the system's basis. Modern electronic actuators and microelectronic circuitry is responsible for desired motion and enables complex control architectures. It is intended that a broad readership would find value in this work.

Design and Control of Lightweight Bionic Arm Driven by Soft Twisted and Coiled Artificial Muscles.

Twisted and coiled actuators (TCAs), which are light but capable of producing significant power, were developed in recent times. After their introduction, there have been numerous improvements in performance, including development of techniques such as actuation strain and heating methods. However, the development of robots using TCA is still in its early stages. In this study, a bionic arm driven by TCAs was developed for light and flexible operation. The aim of this study was to gain a foothold in the future of robot development using TCA, which is considered as the appropriate artificial muscle. The main developments were with regard to the design (from actuator design to system design), system configuration for control, and control method. First, a process technology for repeatedly manufacturing TCA, which can be used practically and delivers sufficient performance, was developed. Based on the developed actuator, a joint was designed to move the elbow and hand. The final bionic arm was developed by integrating the TCA, pulley joint, and control system. It moved the elbow up to 100° and allowed the hand to move in three degrees of freedom. Using the control method for each joint, we were able to show the movement by using the hand and elbow.

Bionic arm: Mapping of elbow and wrist flexion using neural network and fuzzy logic

Cases on limb amputation necessitate the use of Transhumeral bionic for artificial limb rehabilitation, which is controlled using Electromyographic (EMG) signals from the muscles. Before the implementation of EMG control, a mapping between the movements of an arm to the angle formed at the corresponding joints is essential to be made. Most of the works in the field of Bionics use Supervised Machine Learning models, chiefly Classification, to map muscle flexion signals to joint actuations in the bionic arm. Ample literature is also there, which uses fuzzy logic for mapping. However, there are very few literatures that compare these two methods of mapping. In this article, 2 models have been discussed regarding the mapping, and their effectiveness is compared. The first model captures elbow and wrist flexion and maps them to their respective angular displacements of joints using a fuzzy logic model. In the second model, a Pattern Recognition Artificial Neural Network (ANN) model under Supervised Machine Learning is incorporated to map elbow and wrist flexion to the corresponding joint angular displacement. The ANN is trained with elbow and wrist joint flexion values and its corresponding joint angles data, optimized, and tested in real-time. This model is verified by comparing the joint angles of a test person (measured using Goniometers) with the joint angles of Bionic models made (using a 360° protractor sheet). The second model gave the insight that supervised machine learning models provide an accurate mapping to the joint flexion in the field of bionics.

Portable System for Home Use Enables Closed-Loop, Continuous Control of Multi-Degree-of-Freedom Bionic Arm.

Commercial prosthetic hands are frequently abandoned due to unintuitive control methods and a lack of sensory feedback from the prosthesis. Advanced neuromyoelectric prostheses can restore intuitive control and sensory feedback to prosthesis users and potentially reduce abandonment. However, not all advanced prosthetic systems are deployable for home use on portable systems with limited computational power. In this work, we use a commercially available portable neural interface processor (the Ripple Neuro Nomad), and a multi-degree-of-freedom bionic arm (the DEKA LUKE Arm) to create a closed-loop neuromyoelectric prosthesis. The system restores intuitive, independent, continuous control over the arm's six-degrees-of-freedom and provides sensory feedback for up to 288 neural and six vibrotactile channels. Additionally, the large storage capacity of the system enables high-resolution logging of EMG, hand positions, prosthesis sensors, and stimulation parameters. We developed two GUIs enabling wireless, real-time adjustments to motor control and feedback parameters: one with nearly full control over motor control and feedback parameters for investigators, and one with restricted capabilities enabling end-user safety. We verified the system's closed-loop function through a fragile egg task with vibrotactile sensory feedback. We tested the neural stimulation with an amplifier capable of eliciting transcutaneous percepts. This neuromyoelectric prosthetic system will be used for an extended take-home trial that could provide strong clinical justification for advanced, closed-loop prostheses.Clinical Relevance- This work establishes an advanced, intuitive, sensorized prosthesis that can be used in home and clinical settings.

Engineering and surgical advancements enable more cognitively integrated bionic arms.

Integrating tactile and kinesthetic feedback in a bionic arm results in performance closer to able-bodied individuals.