Non-contact Human-computer Interaction Research Articles

GO/MoS2@PVA composite membrane-based optical fiber Mach-Zehnder interferometer for humidity sensing and its non-contact sensing application.

A humidity sensor based on an optical fiber Mach-Zehnder interferometer (MZI) coated with a GO/MoS2@PVA composite membrane was investigated for non-contact sensing. MoS2 was used as a nanospacer to enhance the humidity-sensitive properties of GO, and the adhesion and stability of the composite membrane on the fiber surface could be increased by PVA. The proposed sensor shows a maximum sensitivity of 0.26 dB/%RH with average response and recovery times of 1.62 and 1.11 s, respectively. In non-contact sensing applications, the sensor can effectively recognize a maximum distance of 10 mm for the proximity of a human finger with a distance variation interval of 3 mm. The proposed sensor is expected to be applied in non-contact distance detection and localization or as a non-contact human-computer interaction panel.

Multimedia Interactive Technology for Improving Language Perception in English Teaching and Learning

Abstract Based on Direct Show software, this paper acquires English teaching videos and stores them in the corresponding files. As the position of the teaching projection screen may be different in height, it will lead to the phenomenon that the captured image will be tilted, and it is necessary to use the affine transformation and perspective transformation methods to realize the correction of the teaching projection image. In order to promote the general application of multimedia interactive technology in the teaching process, dynamic gesture tracking with Kalzmann filtering is utilized to construct a non-contact human-computer interaction system, which is applied to the process of English teaching, thus designing an English teaching model incorporating multimedia interactive technology and analyzing the effect of the model. It was found that the mean score of the experimental group’s pre-experimental evaluation was 19.225, and the mean score for the post-experimental assessment was 23.087, t=2.274, P (two-sided)=0.018<0.05 at the 0.05 significance level, which is a significant difference. It shows that compared with traditional English teaching methods, the teaching mode that integrates multimedia interactive technology can effectively improve the English language perception ability of college students in China.

High-performance supercapacitor and ultra-sensitive humidity sensor based on bifunctional NiCo2O4/g-C3N4 nanocomposites powered by triboelectric nanogenerator

Flexible wearable humidity sensor (HS) has become indispensable in various fields such as man–machine interaction, biomedical applications, and industrial environmental monitoring. In particular, the HS powered by supercapacitor (SC) can meet the demand of environmental protection. In this study, an integrated SC and HS system (SCHS) based on the bifunctional material NiCo2O4/g-C3N4 is proposed. Additionally, a humidity signal detection and wireless transmission device is developed to match SCHS. The large surface area of g-C3N4 provides a significant number of surface-active sites that facilitate its synergistic effect with NiCo2O4, which has high electrochemical activity and excellent conductivity. Their synergistic effect makes g-C3N4/NiCo2O4 nanocomposites not only show remarkable sensitivity (1471 kΩ/% RH@11 % RH) to humidity sensing, but also show ultra-high specific capacitance (1061F g−1@0.5 A g−1 current density) on supercapacitors. The SCHS with excellent performances is used for non-contact human–computer interaction, respiratory monitoring of patients with respiratory diseases and humidity monitoring in hazardous industrial environments. In addition, a freestanding-rotation-disk (FRD-TENG) is used as a backup power supply for humidity monitoring system and wireless transmitter module in emergency situations. This work provides a universal and effective strategy for reducing the spread of infectious diseases and protecting lives and property.

Toward Robust Device-Free Gesture Recognition Based on Intrinsic Spectrogram of mmWave Signals

Device-free gesture recognition is a potential noncontact human–computer interaction technique. It leverages the unique influence of the conducted gesture on surrounding wireless signals to accomplish gesture recognition. Existing methods usually leverage doppler spectrogram of the influenced wireless signals to characterize the motion pattern of gestures. These methods have achieved satisfactory accuracy when the gestures are conducted in a relatively fixed location, direction, and speed. However, when gestures are conducted in a different scenario, the recognition accuracy will drop dramatically. In this article, we try to solve this issue by characterizing the gesture motion pattern using a novel robust intrinsic spectrogram, which is independent of the conducted scenario. Specifically, we create a virtual coordinate system in which the coordinates of a gesture trajectory remain unchanged no matter where and how the gesture is conducted. Then, we design a coordinate transformation method to transform the raw doppler spectrogram into the robust intrinsic spectrogram to characterize the intrinsic motion pattern of the gesture. We further feed the intrinsic spectrogram into a deep network to realize gesture recognition. Extensive evaluations on a 77-GHz mmWave testbed show that the proposed method could achieve an average recognize accuracy of 88.4% with ten types of gestures.

A Novel Adaptive Mutation PSO Optimized SVM Algorithm for sEMG-Based Gesture Recognition

In the field of noncontact human-computer interaction, it is of crucial importance to distinguish different surface electromyography (sEMG) gestures accurately for intelligent prosthetic control. Gesture recognition based on low sampling frequency sEMG signal can extend the application of wearable low-cost EMG sensor (for example, MYO bracelet) in motion control. In this paper, a combination of sEMG gesture recognition consisting of feature extraction, genetic algorithm (GA), and support vector machine (SVM) model is proposed. Particularly, a novel adaptive mutation particle swarm optimization (AMPSO) algorithm is proposed to optimize the parameters of SVM; moreover, a new calculation method of mutation probability is also defined. The AMPSO-SVM model based on combination processing is successfully applied to MYO bracelet dataset, and four gesture classifications are carried out. Furthermore, AMPSO-SVM is compared with PSO-SVM, GS-SVM, and BP. The sEMG gesture recognition rate of AMPSO-SVM is 0.975, PSO-SVM is 0.9463, GS-SVM is 0.9093, and BP is 0.9019. The experimental results show that AMPSO-SVM is effective for low-frequency sEMG signals of different gestures.

Flexible pressure sensor based on PVDF nanofiber

The development of wearable electronic devices has created a better blueprint for future human-computer interaction and intelligent living. Flexible pressure sensor is an important link to the development of wearable electronic devices. Despite significant progress made to date, there are still issues to be solved, including complex material synthesis, cumbersome preparation process and poor sensitivity response to human body signal. In this paper, we report flexible sensors that could be applied in different conditions. The sensors are fabricated by combination electrospinning-prepared PVDF nanofiber film with PDMS/Ag NWs and PET/ITO electrodes, respectively. The sensors based on PVDF nanofiber film feature good piezoelectric property with quantitative pressure measurement. Furthermore, they can act as a real-time monitor of human movement due to their conformal form factors. In addition, the sensors realize non-direct contact sensing, providing a broad design idea for future non-contact human-computer interaction. Our approach provides a new, simple, and cost-effective strategy for the development of wearable pressure sensors.

LexiPal: Kinect-based application for dyslexia using multisensory approach and natural user interface

Considered as an effective learning strategy for dyslexia, multisensory approach demands visual, auditory, and kinesthetic activity. While development of software application implementing multisensory approach has shown promising result, previous applications did not accurately resemble multisensory strategy because there are no kinesthetic implementations. This research proposes a Kinect-based application, termed LexiPal, which incorporates kinesthetic activity in multisensory implementation by using Natural User Interface (NUI). NUI provides more intuitive ways of interacting with the application by using body movement and gesture. LexiPal implements NUI by fusing several technologies including Augmented/Mixed Reality (AR/MR), non-contact human-computer interaction, skeletal tracking, hand tracking, and gesture recognition. For evaluation purpose, LexiPal was tested on 40 dyslexic children and they considered LexiPal user interaction as easy to use and enjoyable, which attract them to play the learning content again in the near future.

A non-contact human-computer interaction application design based on electrostatic current of human body

This paper puts forward a non-contact Human-Computer Interaction HCI method applied to game control based on electrostatic current of human body. By setting an electrode array, the induced current signals generated on the electrodes caused by hand motions can be measured by detection circuit and collected into PC by NI series M high-speed data acquisition device PXI6259. The direction of a hand motion can be figured out by processing the signals with LabVIEW programming. Furthermore, a game Mary programmed by LabVIEW can be played with this non-contact HCI technique, the corresponding hand motions: up, down, left and right can control the jump, squat, backward and forward motions of the game object Mary. After repeated experiments, the feasibility of this method has been proved. Namely, a non-contact controlling of a game can be realised with the HCI method based on electrostatic current of human body.

A non-contact mouse for surgeon-computer interaction

We have developed a system that uses computer vision to replace standard computer mouse functions with hand gestures. The system is designed to enable non-contact human-computer interaction (HCI), so that surgeons will be able to make more effective use of computers during surgery. In this paper, we begin by discussing the need for non-contact computer interfaces in the operating room. We then describe the design of our non-contact mouse system, focusing on the techniques used for hand detection, tracking, and gesture recognition. Finally, we present preliminary results from testing and planned future work.

A non-contact mouse for surgeon-computer interaction

We have developed a system that uses computer vision to replace standard computer mouse functions with hand gestures. The system is designed to enable non-contact human-computer interaction (HCI), ...