scholarly journals Augmented Transcutaneous Stimulation Using an Injectable Electrode

2021 ◽  
Author(s):  
Nishant Verma ◽  
Robert D Graham ◽  
Jonah Mudge ◽  
James K Trevathan ◽  
Manfred Franke ◽  
...  
Keyword(s):  
Energy Transfer ◽  
Low Cost ◽  
Coupling Efficiency ◽  
Power Delivery ◽  
Nerve Blocks ◽  
Surface Electrodes ◽  
Non Invasive ◽  
Transcutaneous Stimulation ◽  
Order Of Magnitude ◽  
Neural Selectivity

AbstractMinimally invasive neuromodulation technologies seek to marry the neural selectivity of implantable devices with the low-cost and non-invasive nature of transcutaneous electrical stimulation (TES). The Injectrode® is a needle-delivered electrode that is injected onto neural structures under image guidance. Power is then transcutaneously delivered to the Injectrode using surface electrodes. The Injectrode serves as a low-impedance conduit to guide current to the deep on-target nerve, reducing activation thresholds by an order of magnitude compared to using only surface stimulation electrodes. To minimize off-target recruitment of cutaneous fibers, the energy transfer efficiency from the surface electrodes to the Injectrode must be optimized. TES energy is transferred to the Injectrode through both capacitive and resistive mechanisms. Electrostatic finite element models generally used in TES research consider only the resistive means of energy transfer by defining tissue conductivities. Here, we present an electroquasistatic model, taking into consideration both the conductivity and permittivity of tissue, to understand transcutaneous power delivery to the Injectrode. The model was validated with measurements taken from (n=4) swine cadavers. We used the validated model to investigate system and anatomic parameters that influence the coupling efficiency of the Injectrode energy delivery system. Our work suggests the relevance of electroquasistatic models to account for capacitive charge transfer mechanisms when studying TES, particularly when high-frequency voltage components are present, such as those used for voltage-controlled pulses and sinusoidal nerve blocks.

scholarly journals Augmented Transcutaneous Stimulation Using an Injectable Electrode: A Computational Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Nishant Verma ◽  
Robert D. Graham ◽  
Jonah Mudge ◽  
James K. Trevathan ◽  
Manfred Franke ◽  
...  
Keyword(s):  
Energy Transfer ◽  
Computational Study ◽  
Low Cost ◽  
Coupling Efficiency ◽  
Power Delivery ◽  
Nerve Blocks ◽  
Surface Electrodes ◽  
Transcutaneous Stimulation ◽  
Order Of Magnitude ◽  
Neural Selectivity

Minimally invasive neuromodulation technologies seek to marry the neural selectivity of implantable devices with the low-cost and non-invasive nature of transcutaneous electrical stimulation (TES). The Injectrode® is a needle-delivered electrode that is injected onto neural structures under image guidance. Power is then transcutaneously delivered to the Injectrode using surface electrodes. The Injectrode serves as a low-impedance conduit to guide current to the deep on-target nerve, reducing activation thresholds by an order of magnitude compared to using only surface stimulation electrodes. To minimize off-target recruitment of cutaneous fibers, the energy transfer efficiency from the surface electrodes to the Injectrode must be optimized. TES energy is transferred to the Injectrode through both capacitive and resistive mechanisms. Electrostatic finite element models generally used in TES research consider only the resistive means of energy transfer by defining tissue conductivities. Here, we present an electroquasistatic model, taking into consideration both the conductivity and permittivity of tissue, to understand transcutaneous power delivery to the Injectrode. The model was validated with measurements taken from (n = 4) swine cadavers. We used the validated model to investigate system and anatomic parameters that influence the coupling efficiency of the Injectrode energy delivery system. Our work suggests the relevance of electroquasistatic models to account for capacitive charge transfer mechanisms when studying TES, particularly when high-frequency voltage components are present, such as those used for voltage-controlled pulses and sinusoidal nerve blocks.

scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

scholarly journals CrossGR

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Xinyi Li ◽  
Liqiong Chang ◽  
Fangfang Song ◽  
Ju Wang ◽  
Xiaojiang Chen ◽  
...  
Keyword(s):  
Gesture Recognition ◽  
Low Cost ◽  
User Involvement ◽  
Recognition System ◽  
Training Data ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Target User ◽  
Order Of Magnitude ◽  
Training Examples

This paper focuses on a fundamental question in Wi-Fi-based gesture recognition: "Can we use the knowledge learned from some users to perform gesture recognition for others?". This problem is also known as cross-target recognition. It arises in many practical deployments of Wi-Fi-based gesture recognition where it is prohibitively expensive to collect training data from every single user. We present CrossGR, a low-cost cross-target gesture recognition system. As a departure from existing approaches, CrossGR does not require prior knowledge (such as who is currently performing a gesture) of the target user. Instead, CrossGR employs a deep neural network to extract user-agnostic but gesture-related Wi-Fi signal characteristics to perform gesture recognition. To provide sufficient training data to build an effective deep learning model, CrossGR employs a generative adversarial network to automatically generate many synthetic training data from a small set of real-world examples collected from a small number of users. Such a strategy allows CrossGR to minimize the user involvement and the associated cost in collecting training examples for building an accurate gesture recognition system. We evaluate CrossGR by applying it to perform gesture recognition across 10 users and 15 gestures. Experimental results show that CrossGR achieves an accuracy of over 82.6% (up to 99.75%). We demonstrate that CrossGR delivers comparable recognition accuracy, but uses an order of magnitude less training samples collected from the end-users when compared to state-of-the-art recognition systems.

scholarly journals Investigation of serial coherent laser beam combination based on Brillouin amplification

2007 ◽  
Vol 25 (1) ◽  
pp. 79-83 ◽  
Author(s):  
SHUANGYI WANG ◽  
ZHIWEI LÜ ◽  
DIANYANG LIN ◽  
LEI DING ◽  
DONGBIN JIANG
Keyword(s):  
Laser Beam ◽  
High Power ◽  
Simple Structure ◽  
Low Cost ◽  
Coupling Efficiency ◽  
Laser Beams ◽  
Beam Combination ◽  
Multiple Beams ◽  
Combination Scheme ◽  
Stokes Beam

Based on transferring energy from multiple pump beams into one Stokes beam using Brillouin amplification, a serial coherent laser beam combination scheme is presented, which has many advantages, such as, simple structure, low cost, ease of adjustment, higher load capability, scalable easily, etc. Furthermore, it has been demonstrated that the combination of several beams using this method is theoretically possible. But in practice, the amplification of high power Stokes beam is a key problem to solve. In this paper, the amplification of Stokes beam whose power is higher than the pump beam is first studied and proved experimentally. Coupling the two laser beams by this method is proved experimentally, and the coupling efficiency reaches more than 80%. Then the feasibility of multiple beams combination based on Brillouin amplification is analyzed and tested theoretically.

Micromolding Fabrication of Biocompatible Dry Micro-Pyramid Array Electrodes for Wearable Biopotential Monitoring

2021 ◽  
Author(s):  
Marco Vinicio Alban ◽  
Haechang Lee ◽  
Hanul Moon ◽  
Seunghyup Yoo
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Skin Irritation ◽  
Electrode Impedance ◽  
Non Invasive ◽  
Solution Processes ◽  
Dry Electrodes ◽  
Array Electrode ◽  
Low Cost Manufacturing ◽  
Electromyography Signals

Abstract Thin dry electrodes are promising components in wearable healthcare devices. Assessing the condition of the human body by monitoring biopotentials facilitates the early diagnosis of diseases as well as their prevention, treatment, and therapy. Existing clinical-use electrodes have limited wearable-device usage because they use gels, require preparation steps, and are uncomfortable to wear. While dry electrodes can improve these issues and have demonstrated performance on par with gel-based electrodes, providing advantages in mobile and wearable applications; the materials and fabrication methods used are not yet at the level of disposable gel electrodes for low-cost mass manufacturing and wide adoption. Here, a low-cost manufacturing process for thin dry electrodes with a conductive micro-pyramidal array is presented for large-scale on-skin wearable applications. The electrode is fabricated using micromolding techniques in conjunction with solution processes in order to guarantee ease of fabrication, high device yield, and the possibility of mass production compatible with current semiconductor production processes. Fabricated using a conductive paste and an epoxy resin that are both biocompatible, the developed micro-pyramidal array electrode operates in a conformal, non-invasive manner, with low skin irritation, which ensures improved comfort for brief or extended use. The operation of the developed electrode was examined by analyzing electrode-skin-electrode impedance, electroencephalography, electrocardiography, and electromyography signals and comparing them with those measured simultaneously using gel electrodes.

Non-invasive intelligent monitoring system for fault detection in induction motor based on bio piezoelectric sensor using ANN

2022 ◽  
Author(s):  
Massine GANA ◽  
Hakim ACHOUR ◽  
Kamel BELAID ◽  
Zakia CHELLI ◽  
Mourad LAGHROUCHE ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Motor ◽  
Vibration Analysis ◽  
Low Cost ◽  
Piezoelectric Sensor ◽  
Integrated System ◽  
Easy Access ◽  
Non Invasive ◽  
Artificial Neural

Abstract This paper presents a design of a low-cost integrated system for the preventive detection of unbalance faults in an induction motor. In this regard, two non-invasive measurements have been collected then monitored in real time and transmitted via an ESP32 board. A new bio-flexible piezoelectric sensor developed previously in our laboratory, was used for vibration analysis. Moreover an infrared thermopile was used for non-contact temperature measurement. The data is transmitted via Wi-Fi to a monitoring station that intervenes to detect an anomaly. The diagnosis of the motor condition is realized using an artificial neural network algorithm implemented on the microcontroller. Besides, a Kalman filter is employed to predict the vibrations while eliminating the noise. The combination of vibration analysis, thermal signature analysis and artificial neural network provides a better diagnosis. It ensures efficiency, accuracy, easy access to data and remote control, which significantly reduces human intervention.

Automated text messaging follow-up for patients who receive peripheral nerve blocks

2021 ◽  
pp. rapm-2021-102472
Author(s):  
Daniel Gessner ◽  
Oluwatobi O Hunter ◽  
Alex Kou ◽  
Edward R Mariano
Keyword(s):  
Regional Anesthesia ◽  
Nerve Block ◽  
Text Messaging ◽  
Low Cost ◽  
Automated System ◽  
Phone Call ◽  
Nerve Blocks ◽  
Patient Response ◽  
Patient Reported

BackgroundRoutine follow-up of patients who receive a nerve block for ambulatory surgery typically consists of a phone call from a regional anesthesia clinician. This process can be burdensome for both patients and clinicians but is necessary to assess the efficacy and complication rate of nerve blocks.MethodsWe present our experience developing an automated system for completing follow-up via short message service text messaging and our preliminary results using it at three clinical sites. The system is built on REDCap, a secure online research data capture platform developed by Vanderbilt University and currently available worldwide.ResultsOur automated system queried patients who received a variety of nerve block techniques, assessed patient-reported nerve block duration, and surveyed patients for potential complications. Patient response rate to text messaging averaged 91% (higher than our rates of daily phone contact reported previously) for patients aged 18 to 90 years.ConclusionsGiven the wide availability of REDCap, we believe this automated text messaging system can be implemented in a variety of health systems at low cost with minimal technical expertise and will improve both the consistency of patient follow-up and the service efficiency of regional anesthesia practices.

scholarly journals 231 A Low-Cost, Reusable Model for Teaching Paraspinous Cervical Nerve Blocks to Residents

2018 ◽  
Vol 72 (4) ◽  
pp. S91-S92
Author(s):  
E.A. Nguyen ◽  
D. Fujihara ◽  
R. DeNolf ◽  
M. Johnson ◽  
V. Totten ◽  
...  
Keyword(s):  
Low Cost ◽  
Cervical Nerve ◽  
Nerve Blocks

scholarly journals Method for auxiliary use of thermography in diagnosing inflammation in the coxofemoral joint in dogs

2018 ◽  
Vol 39 (4) ◽  
pp. 1565
Author(s):  
Fernanda Lúcia Passos Fukahori ◽  
Daniela Maria Bastos de Souza ◽  
Eduardo Alberto Tudury ◽  
George Chaves Jimenez ◽  
José Ferreira da Silva Neto ◽  
...  
Keyword(s):  
Thermal Emission ◽  
Low Cost ◽  
Joint Inflammation ◽  
Domestic Animals ◽  
The Body ◽  
Joint Diseases ◽  
Infrared Images ◽  
Infrared Thermometry ◽  
Non Invasive ◽  
Sensitivity Specificity

Joint diseases are relatively common in domestic animals, such as dogs. The involved inflammation produces thermal emission, which can be imaged using specific sensors that allow capturing of infrared images. Given that there have been few reports on the use of thermography in the diagnosis of inflammation associated with diseases of the hip joint in dogs, we here propose a method for identification of inflammatory foci in dogs by using infrared thermometry. The present study aimed to find non-invasive and low-cost resources that couldfacilitate a clinical diagnosis in cases withinflammation in the coxofemoral joint of dogs.To this end, we developed a system in whichthe Flir Systems TG165 thermograph is coupled to a black PVC cannula with a 30-cm focus-to-animal distance.External effects of the environment on the temperature of the animalswere compared with the body temperature as measured by a conventional thermometer.Thirty-one dogs with and without inflammation in the coxofemoral joint underwent clinical evaluation.We verified that the temperature registered by the thermograph inthe animals with joint inflammation was significantlydifferentfrom that incontrol animals without inflammation, in the lateral projection.The method showed a sensitivity of 80%, specificity of 87.5%, and accuracy of 83.87%. This standardized method of diagnosis of inflammatory foci in the coxofemoral articulation of dogs by way of thermography showed sensitivity, specificity, and satisfactory accuracy.

Sign in / Sign up

Export Citation Format

Share Document