Research Progress of Human–Computer Interaction Technology Based on Gesture Recognition

Abstract

Gesture recognition, as a core technology of human–computer interaction, has broad application prospects and brings new technical possibilities for smart homes, medical care, sports training, and other fields. Compared with the traditional human–computer interaction models based on PC use with keyboards and mice, gesture recognition-based human–computer interaction modes can transmit information more naturally, flexibly, and intuitively, which has become a research hotspot in the field of human–computer interaction in recent years. This paper described the current status of gesture recognition technology, summarized the principles and development history of electromagnetic wave sensor recognition, stress sensor recognition, electromyographic sensor recognition, and visual sensor recognition, and summarized the improvement of this technology by researchers in recent years through the direction of sensor structure, selection of characteristic signals, the algorithm of signal processing, etc. By sorting out and comparing the typical cases of the four implementations, the advantages and disadvantages of each implementation and the application scenarios were discussed from the two aspects of dataset size and accuracy. Based on the abovementioned discussion, the problems and challenges of current gesture recognition technology were discussed in terms of the biocompatibility of sensor structures, wearability and adaptability, stability, robustness, and crossover of signal acquisition and analysis algorithms, and the future development directions in this field were proposed.

Integrating Human-Computer Interactions in Nigerian Energy System: A Skills Requirement Analysis

“…Defined by a fusion of technologies blurring the lines between the physical, digital, and biological spheres, Industry 4.0 represents a potential turning point to address issues of the Nigerian energy sector. Industry 4.0 introduces various innovative technologies, such as cyber-physical systems (CPS), the Internet of Things (IoT), artificial intelligence (AI), Big Data, Cloud Computing, and others [11]. These technologies could be instrumental in resolving numerous problems currently impeding the growth and efficiency of Nigeria's energy sector.…”

Human-machine interactions based on hand gesture recognition using deep learning methods

“…This research is very relevant and has great potential for application in various areas of human activity, such as in natural interaction, in real world applications, the applicability of deep learning in improving the accuracy and efficiency of the system. In general, hand gesture recognition technology [12]- [15] has significant potential and relevance in the modern world. Its development and application can lead to new innovative products and improved user experience, which makes this topic very important for research and development in the field of computer technology.…”

Advancing Workplace Safety: A Proactive Approach with Convolutional Neural Network for Hand Pose Estimation in Press Machine Operations

“…To comply with this issue, we have developed a Convolutional Neural Network (CNN) model that will stop the workers from misusing the equipment by checking if their hands are placed safely for the entire operation by following OSHA 1910.217 standard. Research and development on the localization of hand movements has become essential in computer science and artificial intelligence (AI) [6][7][8][9]. There has been a significant advancement in hand position tracking and detection with a wide range of applications, including sensor-based [10][11] and vision-based [12-13] approaches.…”