scholarly journals A bionic soft robotic glove mimicking finger actions based on sEMG recognition

2021 ◽  
Author(s):  
Shumi Zhao ◽  
Ziwen Wang ◽  
Yisong Lei ◽  
Shaotong Huang ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Specific Surface ◽  
Action Recognition ◽  
Electric Potential ◽  
Soft Robotics ◽  
Novel Technique ◽  
Glove Finger ◽  
Finger Motion ◽  
Human Finger ◽  
Forearm Muscle ◽  
Semg Signals

Abstract Compared with rigid robots, soft robotics is more suitable to develop anthropomorphic digits that mimics the biological structures and dexterous motions of human finger. This study proposed a surface electromyogram (sEMG) sensors-based soft robotic glove system which was able to recognize the finger activities and execute the same operation via the bionic glove. Finger activities can be recognized by using electrodes sensors to monitor the electric potential variations on specific surface of the forearm muscle regions. A hybrid robotic digit was designed that utilizes pneumatic bellow actuators to satisfy the anatomical range of the finger motion in order to mimic finger action according to sEMG information. The moving trajectory of digit tip and the range motion of each joint of the robotic digit were measured in experiments under the pressure from 0kPa to 70kPa. The bionic soft robotic glove successfully demonstrated the finger action recognition and robotic digits controlling for a variety of manipulation tasks. The feasible results provided a novel technique for controlling the soft robotic glove through sEMG signals holistically and practically, and also give inspiration and guidance for multiple fingers remote operational applications.

scholarly journals Research on finger movement sensing performance of conductive gloves

2019 ◽  
Vol 14 ◽  
pp. 155892501988762 ◽  
Author(s):  
Xiaoxue Han ◽  
Xuhong Miao ◽  
Xi Chen ◽  
Gaoming Jiang ◽  
Li Niu
Keyword(s):  
Index Finger ◽  
Dynamic Test ◽  
Rehabilitation Medicine ◽  
Proximal Interphalangeal Joint ◽  
Knitted Fabric ◽  
Resistance Change ◽  
Flexible Sensors ◽  
Finger Motion ◽  
Human Finger ◽  
Resistance Data

Knitted flexible sensors are sensors based on the loop structure of knitted fabric, which are soft and close-fitting. Monitoring finger motion can obtain useful information for some applications such as rehabilitation medicine, sports bionics, or human–computer interaction. In this paper, a conductive glove was knitted by SHIMA Seiki SWG 061N-15G computerized flat knitting machine. One experimenter wore it to measure motions data of index finger. The glove has a conductive intarsia area knitted by silver-nylon filaments. The experimenter performed static and dynamic test of hand posture, respectively, then observed the effect of figure bending characteristics on the glove resistance data. The result showed that human finger motion can be monitored successfully by the conductive glove without hard transducers, and both of the bending rate ( Br) and bending angle of the finger proximal interphalangeal joint ( Pba) affect the resistance change of the conductive area of the glove. In other words, the conductive glove has potentials to monitor and reflect human finger motions in detail.

scholarly journals Design of a Two-DOFs Driving Mechanism for a Motion-Assisted Finger Exoskeleton

2020 ◽  
Vol 10 (7) ◽  
pp. 2619 ◽  
Author(s):  
Giuseppe Carbone ◽  
Eike Christian Gerding ◽  
Burkard Corves ◽  
Daniele Cafolla ◽  
Matteo Russo ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Experimental Tests ◽  
Design Solution ◽  
Driving Mechanism ◽  
Dimensional Synthesis ◽  
Linkage Mechanism ◽  
Healthy Human ◽  
Wide Range ◽  
Finger Motion ◽  
Human Finger

This paper presents a novel exoskeleton mechanism for finger motion assistance. The exoskeleton is designed as a serial 2-degrees-of-freedom wearable mechanism that is able to guide human finger motion. The design process starts by analyzing the motion of healthy human fingers by video motion tracking. The experimental data are used to obtain the kinematics of a human finger. Then, a graphic/geometric synthesis procedure is implemented for achieving the dimensional synthesis of the proposed novel 2 degrees of freedom linkage mechanism for the finger exoskeleton. The proposed linkage mechanism can drive the three finger phalanxes by using two independent actuators that are both installed on the back of the hand palm. A prototype is designed based on the proposed design by using additive manufacturing. Results of numerical simulations and experimental tests are reported and discussed to prove the feasibility and the operational effectiveness of the proposed design solution that can assist a wide range of finger motions with proper adaptability to a variety of human fingers.

scholarly journals Electrospun Nanofibers: Characteristic Agents and their Applications

2021 ◽  
Author(s):  
Lingayya Hiremath ◽  
O. Sruti ◽  
B.M. Aishwarya ◽  
N.G. Kala ◽  
E. Keshamma
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Surface Functionalization ◽  
Electrospun Nanofibers ◽  
High Specific Surface Area ◽  
Active Ingredients ◽  
Novel Technique ◽  
Large Size ◽  
Potential Applications ◽  
High Flexibility

This study aimed to introduce antibacterial nanofibers, produced by electrospinning as a novel technique in constructing nanostructured materials. The large size and less bioavailability due to impenetrable (or partial/improper penetration) membrane has resulted in production of nanofibers. These nano sized Fibers were successful in delivering the active ingredients and served the purpose of using plants for its cause. Some of the active ingredients include antimicrobial compounds that are incorporated into various products to prevent unwanted microbial growth. As higher bioavailability is one of the most crucial parameters when it comes to medical solutions, electro spun nanofibers are highly preferred. This method is preferable for organic polymers as they have high flexibility, high specific surface area and surface functionalization. Electrospinning technology has been used for the fabrication and assembly of nanofibers into membranes, which have extended the range of potential applications in the biomedical, environmental protection, nanosensor, electronic/optical, protective clothing fields and various other fields.

The Effect of Pigments in Rubber

1932 ◽  
Vol 5 (3) ◽  
pp. 326-335
Author(s):  
F. Boiry
Keyword(s):  
Zinc Oxide ◽  
Specific Surface ◽  
Chemical Reactions ◽  
Electric Potential ◽  
Hydrated Lime ◽  
Magnesium Carbonate ◽  
The Other ◽  
Mechanical Working ◽  
Adsorption Phenomenon ◽  
Black Light

Abstract 1. Gas black, light calcined magnesia, litharge, hydrated lime, and, to a lesser degree, lamp black give mixtures which do not disintegrate in benzene hydrocarbons. These mixtures disaggregate only after prolonged immersion in an excess of solvent, and the less pigment they contain and the less disaggregated the rubber, as a result of the mechanical working, the longer is this time. The other pigments with rubber form mixtures which disaggregate very rapidly, and from which the rubber dissolves very rapidly. 2. This effect of pigments of the first group is a result of adsorption of the rubber by the pigment particles. 3. In the case of gas black and lamp black, this adsorption phenomenon depends chiefly upon the very great specific surface of these pigments. With magnesia and magnesium carbonate, with hydrated lime, and with litharge it depends chiefly upon a difference in electric potential between the particles of pigment and the rubber. 4. There is a relation between the influence of the pigments on the solubility of raw rubber and their reënforcing effect on rubber after vulcanization. Gas black, magnesium carbonate, and calcined magnesium are the most active in both these respects. The relation is clearly defined in the case of lamp black, less so with litharge, and much less so with zinc oxide and with hydrated lime. The differences in the behavior of these last pigments are apparently due to chemical reactions which take place during vulcanization. 5. Tests carried out to modify the properties of these pigments have not up to the present time given definite results.

A Mechanical Design of One D.O.F. Anthropomorphic Finger Based on a Human Finger Motion

2000 ◽  
Author(s):  
Giorgio Figliolini ◽  
Marco Ceccarelli
Keyword(s):  
Mechanical Design ◽  
Analytical Formulation ◽  
Numerical Examples ◽  
Kinematic Characteristics ◽  
Practical Design ◽  
Finger Motion ◽  
Human Finger

Abstract In this paper we propose an analytical formulation for simulation and design of one d.o.f. articulated finger mechanism with three phalanges. The formulation is based on a study of design and operation of index human finger. In particular, we propose a suitable mechanical design for an anthropomorphic finger as both an approximation of human architecture and an easy practical design. Kinematic characteristics are illustrated with numerical examples.

scholarly journals Surface Electromyography-Based Action Recognition and Manipulator Control

2020 ◽  
Vol 10 (17) ◽  
pp. 5823
Author(s):  
Tianao Cao ◽  
Dan Liu ◽  
Qisong Wang ◽  
Ou Bai ◽  
Jinwei Sun
Keyword(s):  
Real Time ◽  
Action Recognition ◽  
Surface Electromyography ◽  
Emg Activity ◽  
Support Vector ◽  
High Signal ◽  
Wrist Flexion ◽  
Manipulator Control ◽  
Semg Signals

To improve the quality of lives of disabled people, the application of intelligent prosthesis was presented and investigated. In particular, surface Electromyography (sEMG) signals succeeded in controlling the manipulator in human–machine interface, due to the fact that EMG activity belongs to one of the most widely utilized biosignals and can reflect the straightforward motion intention of humans. However, the accuracy of real-time action recognition is usually low and there is usually obvious delay in a controlling manipulator, as a result of which the task of tracking human movement precisely, cannot be guaranteed. Therefore, this study proposes a method of action recognition and manipulator control. We built a multifunctional sEMG detection and action recognition system that integrated all discrete components. A biopotential measurement analog-to-digital converter with a high signal–noise rate (SNR) was chosen to ensure the high quality of the acquired sEMG signals. The acquired data were divided into sliding windows for processing in a shorter time. Mean Absolute Value (MAV), Waveform Length (WL), and Root Mean Square (RMS) were finally extracted and we found that compared to the Genetic-Algorithm-based Support Vector Machine (GA–SVM), the back propagation (BP) neural network performed better in joint action classification. The results showed that the average accuracy of judging the 5 actions (fist clenching, hand opening, wrist flexion, wrist extension, and calling me) was up to 93.2% and the response time was within 200 ms, which achieved a simultaneous control of the manipulator. Our work took into account the action recognition accuracy and real-time performance, and realized the sEMG-based manipulator control eventually, which made it easier for people with arm disabilities to communicate better with the outside world.

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