scholarly journals The Development of Body-Powered Prosthetic Hand Controlled by EMG Signals Using DSP Processor with Virtual Prosthesis Implementation

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Fathia H. A. Salem ◽  
Khaled S. Mohamed ◽  
Sundes B. K. Mohamed ◽  
Amal A. El Gehani
Keyword(s):  
High Performance ◽  
State Of The Art ◽  
The Body ◽  
Prosthetic Hand ◽  
Prosthetic Hands ◽  
Emg Signal ◽  
Mechanical Hand ◽  
Fast Processing ◽  
Opening And Closing ◽  
Two Stages

The state of the art in the technology of prosthetic hands is moving rapidly forward. However, there are only two types of prosthetic hands available in Libya: the Passive Hand and the Mechanical Hand. It is very important, therefore, to develop the prosthesis existing in Libya so that the use of the prosthesis is as practical as possible. Considering the case of amputation below the elbow, with two movements: opening and closing the hand, this work discusses two stages: developing the operation of the body-powered prosthetic hand by controlling it via the surface electromyography signal (sEMG) through dsPIC30f4013 processor and a servo motor and a software based on fuzzy logic concept to detect and process the EMG signal of the patient as well as using it to train the patient how to control the movements without having to fit the prosthetic arm. The proposed system has been practically implemented, tested, and gave satisfied results, especially that the used processor provides fast processing with high performance compared to other types of microcontrollers.

State-of-the-Art Method in Prosthetic Hand Design: A Review

2021 ◽  
Vol 50 ◽  
pp. 15-24
Author(s):  
T. Triwiyanto ◽  
Triana Rahmawati ◽  
I. Putu Alit Pawana ◽  
L. Lamidi ◽  
Torib Hamzah ◽  
...  
Keyword(s):  
Low Power ◽  
Low Cost ◽  
Maximum Voluntary Contraction ◽  
Voluntary Contraction ◽  
Occupational Accidents ◽  
Limb Amputation ◽  
Prosthetic Hand ◽  
Advantages And Disadvantages ◽  
Prosthetic Hands ◽  
Emg Signal

Human limb amputation can be caused due to congenital disabilities, accidents, and certain diseases. Amputation caused by occupational accidents is a frequent occurrence in developing countries. Meanwhile, amputation caused by certain diseases such as diabetes Miletus is also the leading cause. The need for prosthetic hand is increasing along with the increase in those two factors. Several researchers have developed prosthetic hands with advantages and disadvantages. Research on prosthetic hands, which are useful, low power, and low cost, is still a major issue. Therefore, the purpose of this paper is to provide a review of the various designs of prosthetic hands, specifically on the sensor, control, and actuator systems. This paper collected several references from proceedings and journals related to the design of the prosthetic hand. The results show that the EMG signal is widely used by some researchers in controlling prosthetic hands compared to other sensors, following the force-sensitive resistor (FSR) sensor. To control prosthetic hands, some researchers used a threshold system with a value of 20% of the maximum voluntary contraction (MVC), and several other researchers used a pattern recognition model based on the EMG signal feature. Moreover, In the mechanical part, the open-source prosthetic hand model is more widely used than the fabricate prosthetic hand. This is due to the cost required in the prosthetic hand design is cheaper than a fabricated one. The results of this review are expected to provide a recommendation to researchers in the development of low cost, low power, and practical prosthetic hands.

Electromyography Feature Analysis to Recognize the Hand Motion in a Prosthetic Hand Design

2021 ◽  
Vol 50 ◽  
pp. 25-37
Author(s):  
T. Triwiyanto ◽  
Endro Yulianto ◽  
I Dewa Gede Hari Wisana ◽  
Muhammad Ridha Mak’ruf ◽  
Bambang Guruh Irianto ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Time Domain ◽  
Euclidean Distance ◽  
Prosthetic Hand ◽  
Hand Motion ◽  
Prosthetic Hands ◽  
Emg Signal ◽  
Dry Electrode ◽  
Flexion Extension ◽  
Selection Of

The increasing need for prosthetic hands for people with disabilities is one reason for innovation in the field of prosthetic hands to create the best prosthetic hand technology. In the design of EMG-based prosthetic hands, this is determined by several things, among others, the selection of features. The selection of the right features will determine the accuracy of the prosthetic hand Therefore, the purpose of this study is to analysis the time domain feature to obtain the best feature in classifying the hand motion. The contribution of this work is able to detect 4 movements in real time, namely hand close, flexion, extension, and relax. The Electromyograph signal is tapped using an electromyograph (EMG) dry electrode sensor in which there is a circuit of EMG instrumentation amplifier. Furthermore, the analog EMG signal data is processed through the ADC (Analog to Digital Converter) by using MCP3008 device. EMG signal data is processed in Raspberry Pi. A feature extraction process is applied to reduce data and determine the characteristics of each hand movement. Feature extraction used is MAV (mean absolute value), SSI (sign slope integral), VAR (variance), and RMS (root mean square). From the results of the four-time domain feature, then the best feature extraction is determined using scatter plot and Euclidean distance. The results that have been carried out on ten people with each person doing ten sets of movements (hand close, flexion, extension, relax), showing the best Euclidean distance results, is the RMS feature, with a value of 2608.07. This data is the result of the best feature extraction analysis through the method of calculating the distance of feature extraction data using Euclidean distance. This analysis of time domain feature is expected to be useful for further experiment in machine learning implementation so that it can be obtained an effective prosthetic hand.

Evaluation of New 99mTc(CO)3 + Radiolabeled Glycylglycine In Vivo

2019 ◽  
Vol 19 (11) ◽  
pp. 1382-1387
Author(s):  
Ahmet M. Şenışık ◽  
Çiğdem İçhedef ◽  
Ayfer Y. Kılçar ◽  
Eser Uçar ◽  
Kadir Arı ◽  
...  
Keyword(s):  
High Performance ◽  
The Body ◽  
Biological Behavior ◽  
In Vivo Evaluation ◽  
Radiolabeled Peptides ◽  
Tumor Bearing ◽  
Biodistribution Data ◽  
Good Accordance ◽  
Rapid Clearance

Background: Peptide-based agents are used in molecular imaging due to their unique properties, such as rapid clearance from the circulation, high affinity and target selectivity. Many of the radiolabeled peptides have been clinically experienced with diagnostic accuracy. The aim of this study was to investigate in vivo biological behavior of [99mTc(CO)3(H2O)3]+ radiolabeled glycylglycine (GlyGly). Methods: Glycylglycine was radiolabeled with a high radiolabeling yield of 94.69±2%, and quality control of the radiolabeling process was performed by thin layer radiochromatography (TLRC) and High-Performance Liquid Radiochromatography (HPLRC). Lipophilicity study for radiolabeled complex (99mTc(CO)3-Gly-Gly) was carried out using solvent extraction. The in vivo evaluation was performed by both biodistribution and SPECT imaging. Results: The high radiolabelling yield of 99mTc(CO)3-GlyGly was obtained and verified by TLRC and HPLRC as well. According to the in vivo results, SPECT images and biodistribution data are in good accordance. The excretion route from the body was both hepatobiliary and renal. Conclusion: This study shows that 99mTc(CO)3-GlyGly has the potential to be used as a peptide-based imaging agent. Further studies, 99mTc(CO)3-GlyGly can be performed on tumor-bearing animals.

A simplified model of a multi-jointed mechanical finger calibrated with experimental data by vision system

2021 ◽  
Vol 235 (1) ◽  
pp. 164-175
Author(s):  
C Cosenza ◽  
V Niola ◽  
S Savino
Keyword(s):  
Experimental Data ◽  
Vision System ◽  
Control Strategies ◽  
Image Correlation ◽  
Robotic Hand ◽  
Prosthetic Device ◽  
Prosthetic Hands ◽  
Mechanical Hand ◽  
Free Mode ◽  
Mechanical Finger

The development of suitable models for mechanical fingers, whether they are part of prosthetic device or of a robotic hand, is a powerful tool to predict the behaviour of their components since the early stages of design, especially for underactuated mechanisms. Experimental data can improve the reliability of such models and promote their application to build proper control strategies especially for prosthetic hands. Here, we have developed a multi-jointed model of a mechanical finger. The finger is part of the Federica hand: an underactuated mechanical hand that was conceived for prosthetic purpose. The model accounts for friction phenomena in the finger and it is tuned with experimental data acquired through a digital image correlation device. The model allowed us to write kinematics relations of the phalanges and evaluate finger configurations in relation to the closure velocity. Moreover, it was possible to estimate the tendon force and the work analysis occurring during the closure tasks, both in free mode and in presence of objects.

scholarly journals Multiple objects tracking in the UAV system based on hierarchical deep high-resolution network

2021 ◽  
Author(s):  
Wei Huang ◽  
Xiaoshu Zhou ◽  
Mingchao Dong ◽  
Huaiyu Xu
Keyword(s):  
High Resolution ◽  
Object Tracking ◽  
High Performance ◽  
State Of The Art ◽  
Class Imbalance ◽  
Unified Framework ◽  
Multiple Objects ◽  
Tracking Process ◽  
Objects Tracking ◽  
Different Types

AbstractRobust and high-performance visual multi-object tracking is a big challenge in computer vision, especially in a drone scenario. In this paper, an online Multi-Object Tracking (MOT) approach in the UAV system is proposed to handle small target detections and class imbalance challenges, which integrates the merits of deep high-resolution representation network and data association method in a unified framework. Specifically, while applying tracking-by-detection architecture to our tracking framework, a Hierarchical Deep High-resolution network (HDHNet) is proposed, which encourages the model to handle different types and scales of targets, and extract more effective and comprehensive features during online learning. After that, the extracted features are fed into different prediction networks for interesting targets recognition. Besides, an adjustable fusion loss function is proposed by combining focal loss and GIoU loss to solve the problems of class imbalance and hard samples. During the tracking process, these detection results are applied to an improved DeepSORT MOT algorithm in each frame, which is available to make full use of the target appearance features to match one by one on a practical basis. The experimental results on the VisDrone2019 MOT benchmark show that the proposed UAV MOT system achieves the highest accuracy and the best robustness compared with state-of-the-art methods.

scholarly journals Electro-Quasistatic Animal Body Communication for Untethered Rodent Biopotential Recording

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shreeya Sriram ◽  
Shitij Avlani ◽  
Matthew P. Ward ◽  
Shreyas Sen
Keyword(s):  
Lower Energy ◽  
Sensor Node ◽  
State Of The Art ◽  
The Body ◽  
Animal Body ◽  
Current State ◽  
Communication Modalities ◽  
First Time ◽  
Biopotential Recording

AbstractContinuous multi-channel monitoring of biopotential signals is vital in understanding the body as a whole, facilitating accurate models and predictions in neural research. The current state of the art in wireless technologies for untethered biopotential recordings rely on radiative electromagnetic (EM) fields. In such transmissions, only a small fraction of this energy is received since the EM fields are widely radiated resulting in lossy inefficient systems. Using the body as a communication medium (similar to a ’wire’) allows for the containment of the energy within the body, yielding order(s) of magnitude lower energy than radiative EM communication. In this work, we introduce Animal Body Communication (ABC), which utilizes the concept of using the body as a medium into the domain of untethered animal biopotential recording. This work, for the first time, develops the theory and models for animal body communication circuitry and channel loss. Using this theoretical model, a sub-inch$$^3$$ 3 [1″ × 1″ × 0.4″], custom-designed sensor node is built using off the shelf components which is capable of sensing and transmitting biopotential signals, through the body of the rat at significantly lower powers compared to traditional wireless transmissions. In-vivo experimental analysis proves that ABC successfully transmits acquired electrocardiogram (EKG) signals through the body with correlation $$>99\%$$ > 99 % when compared to traditional wireless communication modalities, with a 50$$\times$$ × reduction in power consumption.

scholarly journals Calculating the optimal hematocrit under the constraint of constant cardiac power

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michal Sitina ◽  
Heiko Stark ◽  
Stefan Schuster
Keyword(s):  
Blood Flow ◽  
High Performance ◽  
Animal Species ◽  
Normal Values ◽  
Mechanical Load ◽  
The Body ◽  
Trade Off ◽  
Cardiac Power ◽  
Optimal Value ◽  
Good Agreement

AbstractIn humans and higher animals, a trade-off between sufficiently high erythrocyte concentrations to bind oxygen and sufficiently low blood viscosity to allow rapid blood flow has been achieved during evolution. Optimal hematocrit theory has been successful in predicting hematocrit (HCT) values of about 0.3–0.5, in very good agreement with the normal values observed for humans and many animal species. However, according to those calculations, the optimal value should be independent of the mechanical load of the body. This is in contradiction to the exertional increase in HCT observed in some animals called natural blood dopers and to the illegal practice of blood boosting in high-performance sports. Here, we present a novel calculation to predict the optimal HCT value under the constraint of constant cardiac power and compare it to the optimal value obtained for constant driving pressure. We show that the optimal HCT under constant power ranges from 0.5 to 0.7, in agreement with observed values in natural blood dopers at exertion. We use this result to explain the tendency to better exertional performance at an increased HCT.

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