Recent Progress in Flexible Microstructural Pressure Sensors toward Human–Machine Interaction and Healthcare Applications

Small Methods ◽  
2021 ◽  
pp. 2001041
Author(s):  
Faliang He ◽  
Xingyan You ◽  
Weiguo Wang ◽  
Tian Bai ◽  
Gaofei Xue ◽  
...  
Keyword(s):  
Recent Progress ◽  
Pressure Sensors ◽  
Healthcare Applications ◽  
Human Machine Interaction ◽  
Machine Interaction

Supersensitive all-fabric pressure sensors using printed textile electrode arrays for human motion monitoring and human–machine interaction

2018 ◽  
Vol 6 (48) ◽  
pp. 13120-13127 ◽  
Author(s):  
Ziqiang Zhou ◽  
Ying Li ◽  
Jiang Cheng ◽  
Shanyong Chen ◽  
Rong Hu ◽  
...  
Keyword(s):  
Cotton Fabric ◽  
Pressure Sensors ◽  
Human Motion ◽  
Electrode Arrays ◽  
Human Machine Interaction ◽  
Silver Paste ◽  
Textile Electrode ◽  
Human Motion Monitoring ◽  
Machine Interaction ◽  
Coated Cotton

Supersensitive all-fabric pressure sensors with a bottom interdigitated textile electrode screen-printed using silver paste and a top bridge of AgNW-coated cotton fabric are successfully fabricated for human motion monitoring and human–machine interaction.

scholarly journals A Review of Printable Flexible and Stretchable Tactile Sensors

Research ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-32 ◽  
Author(s):  
Kirthika Senthil Kumar ◽  
Po-Yen Chen ◽  
Hongliang Ren
Keyword(s):  
Material Properties ◽  
Recent Progress ◽  
Wearable Electronics ◽  
Tactile Sensors ◽  
Human Machine Interaction ◽  
Surrounding Environment ◽  
Challenges And Opportunities ◽  
Varied Range ◽  
Machine Interaction ◽  
Material Preparation

Flexible and stretchable tactile sensors that are printable, nonplanar, and dynamically morphing are emerging to enable proprioceptive interactions with the unstructured surrounding environment. Owing to its varied range of applications in the field of wearable electronics, soft robotics, human-machine interaction, and biomedical devices, it is required of these sensors to be flexible and stretchable conforming to the arbitrary surfaces of their stiff counterparts. The challenges in maintaining the fundamental features of these sensors, such as flexibility, sensitivity, repeatability, linearity, and durability, are tackled by the progress in the fabrication techniques and customization of the material properties. This review is aimed at summarizing the recent progress of rapid prototyping of sensors, printable material preparation, required printing properties, flexible and stretchable mechanisms, and promising applications and highlights challenges and opportunities in this research paradigm.

Conductive graphene-based E-textile for highly sensitive, breathable, and water-resistant multimodal gesture-distinguishable sensors

2020 ◽  
Vol 8 (29) ◽  
pp. 14778-14787
Author(s):  
Xurui Hu ◽  
Tao Huang ◽  
Zhiduo Liu ◽  
Gang Wang ◽  
Da Chen ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Control System ◽  
Remote Control ◽  
Pressure Sensors ◽  
Human Machine Interaction ◽  
Remote Control System ◽  
Highly Sensitive ◽  
Machine Interaction

Graphene E-textile exhibits excellent electrical conductivity, breathability, and washability. The application of a graphene E-textile on a wearable remote-control system by sewing the pressure sensors into the five fingers of a glove to invoke a human–machine interaction.

scholarly journals Backstepping Control of Open-Chain Linkages Actuated by Antagonistic Hill Muscles

2020 ◽  
Vol 142 (10) ◽  
Author(s):  
Holly Warner ◽  
Hanz Richter ◽  
Antonie J. van den Bogert
Keyword(s):  
Inverse Dynamics ◽  
Human Subjects ◽  
Kinematic Chain ◽  
Test Results ◽  
Robotic Rehabilitation ◽  
Healthcare Applications ◽  
Human Machine Interaction ◽  
Open Chain ◽  
Prosthetic Devices ◽  
Machine Interaction

Abstract For human–machine interaction, the forward progression of technology, particularly controls, regularly brings about new possibilities. Indeed, healthcare applications have flourished in recent years, including robotic rehabilitation, exercise, and prosthetic devices. Testing these devices with human subjects is inherently risky and frequently inconsistent. This work offers a novel simulation framework toward overcoming many of these difficulties. Specifically, generating a closed-loop dynamic model of a human or a human subsystem that can connect to device simulations allows simulated human–machine interaction. In this work, a muscle-actuated open kinematic chain linkage is generated to simulate the human, and a backstepping controller based on inverse dynamics is derived. The control architecture directly addresses muscle redundancy, and two options to resolve this redundancy are evaluated. The specific case of a muscle-actuated arm linkage is developed to illustrate the framework. Trajectory tracking is achieved in simulation. The muscles recruited to meet the tracking goal are in agreement with the method used to solve the redundancy problem. In the future coupling such simulations to any relevant simulation of a machine will provide safe, insightful preprototype test results.

A Study for Improving Device-Directed Speech Detection Toward Frictionless Human-Machine Interaction

2019 ◽  
Author(s):  
Che-Wei Huang ◽  
Roland Maas ◽  
Sri Harish Mallidi ◽  
Björn Hoffmeister
Keyword(s):  
Human Machine Interaction ◽  
Speech Detection ◽  
Machine Interaction

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

Holistic, Context-sensitive Human-machine Interaction for Automated Vehicles

ATZ worldwide ◽  
2021 ◽  
Vol 123 (3) ◽  
pp. 46-49
Author(s):  
Tobias Hesse ◽  
Michael Oehl ◽  
Uwe Drewitz ◽  
Meike Jipp
Keyword(s):  
Automated Vehicles ◽  
Human Machine Interaction ◽  
Context Sensitive ◽  
Machine Interaction
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