RF-AIRCGR: Lightweight Convolutional Neural Network-Based RFID Chinese Character Gesture Recognition Research by Yajun Zhang, Congcong Wang, Feng Li, Weiqian Yu, Yuankang Wang, Jingying Chen

“…Gesture recognition serves as a foundation for Human-Computer Interaction (HCI). Although Radio Frequency Identification (RFID) is gaining popularity due to its advantages (non-invasive, low-cost, and lightweight), most existing research has only addressed the recognition of simple sign language gestures or body movements. …”
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Letter and Person Recognition in Freeform Air-Writing Using Machine Learning Algorithms by Huseyin Kunt, Zeki Yetgin, Furkan Gozukara, Turgay Celik

“…Air-writing is an emerging form of human-computer interaction that enables text entry through hand movements in the air. …”
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Machine learning-enhanced gesture recognition through impedance signal analysis by Huynh Hoang Nhut, Diep Quoc Tuan Nguyen, Dinh Minh Quan Cao, Tran Anh Tu, Dang Nguyen Chau, Phan Thien Luan, Tran Trung Nghia, Ching Congo Tak Shing

“…Gesture recognition is a crucial aspect in the advancement of virtual reality, healthcare, and human-computer interaction, and requires innovative methodologies to meet the increasing demands for precision. …”
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Advances in the Study of AI-assisted Diagnosis and Rehabilitation of ASD by Bosen MA, Xiaorong ZENG, Ran GONG, Farui LI

“…While early research on rehabilitation with non-robot intervention equipment mainly focuses on the single skill training, recent studies have gradually shifted to the comprehensive training due to the technological advancement of human-computer interaction and virtual reality (VR). Different from the single skill training, the comprehensive training is not only concerned with communicative competence, but also creates situations close to real life. …”
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Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification by Hunmin Lee, Ming Jiang, Jinhui Yang, Zhi Yang, Qi Zhao

“…In recent years, significant strides in deep learning have propelled the advancement of electromyography (EMG)-based upper-limb gesture recognition systems, yielding notable successes across a spectrum of domains, including rehabilitation, orthopedics, robotics, and human-computer interaction. Despite these achievements, prevailing methodologies often overlook the intrinsic physical configurations and interconnectivity of multi-channel sensory inputs, resulting in a failure to adequately capture relational information embedded within the connections of deployed EMG sensor network topology. …”
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Sign Language Recognition System for Deaf Patients: Protocol for a Systematic Review by Milena Soriano Marcolino, Lucca Fagundes Ramos Oliveira, Lucas Rocha Valle, Luiza Marinho Motta Santa Rosa, Zilma Silveira Nogueira Reis, Thiago Barbabela de Castro Soares, Elidéa Lúcia Almeida Bernardino, Raniere Alislan Almeida Cordeiro, Raquel Oliveira Prates, Mario Fernando Montenegro Campos

“…ObjectiveThis study aims to systematically review the evidence on communication systems using human-computer interaction techniques developed for deaf people who communicate through sign language that are already in use or proposed for use in health care contexts and have been tested with human users or videos of human users. …”
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Pengaruh Ciri Temporal, Spasial, dan Frekuensi pada Klasifikasi Motor Imagery by Afin Muhammad Nurtsani, Muhammad Adib Syamlan, Agung Wahyu Setiawan

“…Selain itu, pengklasifikasi RF memberikan kinerja yang paling baik dibandingkan dengan SVM; k-NN; serta NB.    Abstract  Human-computer interaction is a necessity and will be deployed in the near future, especially in rehabilitation engineering. …”
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Evaluación bibliométrica de la investigación sobre Tecnologías Habilitadoras para la Transformación Digital en Cuba by Yudayly Stable-Rodríguez, Lee Yang Díaz-Chieng, Alfredo Javier Pérez Gamboa, Esteban Rodríguez-Torres

“…Hubo mayoría de las temáticas artificial inteligente, machine learning, learning systems, human computer interaction y data minning relacionados con la salud. …”
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SkelETT—Skeleton-to-Emotion Transfer Transformer by Pedro Victor Vieira Paiva, Josue Junior Guimaraes Ramos, Marina Gavrilova, Marco Antonio Garcia de Carvalho

“…Emotion recognition plays an essential role in human-computer interaction, spanning diverse domains from human-robot communication and virtual reality to mental health assessment and affective computing. …”
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IoT-Based Multisensors Fusion for Activity Recognition via Key Features and Hybrid Transfer Learning by Ahmad Jalal, Danyal Khan, Touseef Sadiq, Moneerah Alotaibi, Sultan Refa Alotaibi, Hanan Aljuaid, Hameedur Rahman

“…Human activity recognition (HAR) has attracted significant attention in various fields, including healthcare, smart homes, and human-computer interaction. Accurate HAR can enhance user experience, provide critical health insights, and enable sophisticated context-aware applications. …”
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Enhancing feature selection for multi-pose facial expression recognition using a hybrid of quantum inspired firefly algorithm and artificial bee colony algorithm by Mu Panliang, Sanjay Madaan, Siddiq Ahmed Babikir Ali, Gowrishankar J., Ali Khatibi, Anas Ratib Alsoud, Vikas Mittal, Lalit Kumar, A. Johnson Santhosh

“…Abstract Facial expression recognition (FER) has advanced applications in various disciplines, including computer vision, Internet of Things, and artificial intelligence, supporting diverse domains such as medical escort services, learning analysis, fatigue detection, and human-computer interaction. The accuracy of these systems is of utmost concern and depends on effective feature selection, which directly impacts their ability to accurately detect facial expressions across various poses. …”
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Effective Facial Expression Recognition System Using Artificial Intelligence Technique by Imad S. Yousif, Tarik A. Rashid, Ahmed S. Shamsaldin, Sabat A. Abdulhameed, Abdulhady Abas Abdullah

“…Recognizing these facial expressions accurately is essential for a variety of applications — such as tools that use our faces to interact with computers (human-computer interaction, or HCI), security systems and emotionally intelligent artificial intelligence technologies. …”
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Artificial Intelligence–Powered Training Database for Clinical Thinking: App Development Study by Heng Wang, Danni Zheng, Mengying Wang, Hong Ji, Jiangli Han, Yan Wang, Ning Shen, Jie Qiao

“… Abstract BackgroundWith the development of artificial intelligence (AI),ntered the era of intelligent medicine ObjectiveThis study aimed to introduce an app named “XueYiKu,” which includes consultations, physical examinations, auxiliary examinations, and diagnosis, incorporating AI and actual complete hospital medical records to build an online-learning platform using human-computer interaction. MethodsThe “XueYiKu” app was designed as a contactless, self-service, trial-and-error system application based on actual complete hospital medical records and natural language processing technology to comprehensively assess the “clinical competence” of residents at different stages. …”
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Klasifikasi Ekspresi Wajah Menggunakan Covolutional Neural Network by Ahmad Taufiq Akbar, Shoffan Saifullah, Hari Prapcoyo

“…Abstract Facial expression recognition is a significant challenge in image processing and human-computer interaction due to its inherent complexity and variability. …”
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Disposable and flexible smart electronic tapes for long-term biopotential monitoring by Jiuwei Gao, Mingwei Hu, Hao Sun, Yuanyuan Wang, Yuan Wei, Weiwei Li, Lu Zheng, Manzhang Xu, Qianbo Lu, Zhiyuan Liu, Hui Yang, Yongtian Wang, Weitao Song, Xuewen Wang, Wei Huang

“…We anticipate the SET will pioneer next-gen wearable electronics for applications like disease prevention, health monitoring, and human–computer interaction.…”
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A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition by Jiawen Li, Guanyuan Feng, Chen Ling, Ximing Ren, Xin Liu, Shuang Zhang, Leijun Wang, Yanmei Chen, Xianxian Zeng, Rongjun Chen

“…Emotion recognition is an advanced technology for understanding human behavior and psychological states, with extensive applications for mental health monitoring, human–computer interaction, and affective computing. Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. …”
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The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review by Hassan Auf, Petra Svedberg, Jens Nygren, Monika Nair, Lina E Lundgren

“…The key aspects requiring further investigation include the evaluation of the use of AI-supported decision-making from human-AI interaction and human-computer interaction perspectives, longitudinal implementation studies of AI systems in mental health to assess the use, and the integration of shared decision-making in AI systems.…”
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Exploring Health Educational Interventions for Children With Congenital Heart Disease: Scoping Review by Neda Barbazi, Ji Youn Shin, Gurumurthy Hiremath, Carlye Anne Lauff

“…The search covered health care, design, and human-computer interaction disciplines to capture the interdisciplinary nature of CHD health educational interventions. …”
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Microstructured Liquid Metal‐Based Embedded‐Type Sensor Array for Curved Pressure Mapping by Haoyu Li, Chengjun Zhang, Hongyu Xu, Qing Yang, Zexiang Luo, Cheng Li, Lin Kai, Yizhao Meng, Jialiang Zhang, Jie Liang, Feng Chen

“…The stretchable and mechanically stable sensor arrays possess shape‐adaptability that enables pressure mapping on non‐flat surfaces, which has great potential for object recognition in robotic skins and human‐computer interaction.…”
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Characterization and Spatial Distribution of Sand Group Architecture and Channel Types in Tight Gas Reservoirs: A Case Study From the Jurassic Shaximiao Formation of the Jinqiu Gas... by Guian Guo, Deyu Zhu, Xiaojuan Wang, Mingqiu Li, Xu Guan, Xiaoju Zhang, Changjiang Wu, Shaomin Zhang, Li Hu, Juan Zhao, Nan Li, Huiqiang Wang, Bohan Duan

“…The technology of fine characterization for channel sand-bodies on the basis of human–computer interaction and seismic attributes is proposed, and geological modelling of the spatial distribution of sand group architectures and channel types is established. …”
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