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14 results for “Human Activity Recognition”
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Review ArticleOpen accessPhrase in the titleHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEdge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNNSuresh Kumar, M Y. Mohamed ParveesHuman Activity Recognition (HAR) is an important research area for various application domains such as healthcare, gaming, telemonitoring, and sports. However, executing HAR algorithms on remote servers or in the cloud have challenges in terms of high latency, increased bandwidth demand, and high energy consumption. Moving the computation to edge-assisted HAR is more effective and flexible solution to address the … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,578 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFeature Extraction of Sit-to-Stand Transition Using Vision-Based Pose EstimationAchmad Rizal, Bayu Erfianto, Sugondo Hadiyoso, IstiqomahSit-to-Stand Transition (STS) and vice versa are important indicators of independence and physical health. For normal people, this movement is easy to do but can be difficult for people who have health problems, such as those who have had an injury or stroke. Sit-to-stand assessments can be used to detect spinal disorders. However, spinal kinematic measurements require special instrumentation and … …Journal of Computer Science, Vol. 21, Issue 3 · 21 Feb 2025 · 6,204 accessesView PDFCite
Research ArticleOpen accessIn the abstractPHASEY: A Contrastive Learning Approach for Enhanced Human Gait Phases RecognitionUrvashi, Deepak Kumar, Vinay Kukreja, Ayush DograHuman gait has gained much attention in behavioral biometrics as it possesses unique and distinctive characteristics. Gait phases, which describe the different patterns of human walking, are significant for the analysis and understanding of movement in an individual. Hence, the identification of gait phases is important for the accurate determination and interpretation of walking patterns, ranging from healthcare and security … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 4,638 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Air-Written Real-Time Multilingual Numeral String Recognition System Using Deep Convolutional Neural NetworksMeenal Jabde, Chandrashekhar Himmatrao Patil, Amol D. Vibhute, Shankar MaliAir-writing is a modern practice for free-space writing of characters or words with hand or finger movements. In the new era, hand gestures are commonly used for Human-Computer Interaction (HCI) or controlling machines in several applications. Writing with a finger or holding any object in hand and 3-D movement in the air is helpful for several applications. However, it is … …Journal of Computer Science, Vol. 20, Issue 12 · 8 Nov 2024 · 5,248 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Prediction Studies Using Wearable Sensors and Machine LearningDivya Sharma, Usha ChauhanNowadays, Human Activity Recognition (HAR) systems have become so demanding that they find applications in the field of assisted living systems, elderly healthcare systems, smart homes, healthcare monitoring applications, surveillance systems, etc. Due to its increasing demand in computer science; machine learning and deep learning have brought a paradigm shift in the area of sensor-based recognition systems. Providing accurate information … …Journal of Computer Science, Vol. 20, Issue 4 · 14 Feb 2024 · 7,201 accessesView PDFCite
Review ArticleOpen accessIn the abstractFace Recognition as a Biometric ApplicationRelly Victoria Virgil PetrescuA facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from the given image with faces within a database. It is also described as … …Journal of Mechatronics and Robotics, Vol. 3, Issue 1 · 14 May 2019 · 18,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractDistributed and Parallel Decision Forest for Human Activities Prediction: Experimental Analysis on HAR-Smartphones DatasetBudi Padmaja, Venkata Rama Prasad Vaddella, Kota Venkata Naga SunithaSensor-based human motion detection requires the subtle amount of knowledge about various human activities from fitted sensor observations and readings. The prevalent pattern recognition methodologies have made immense progress over recent years. Nonetheless, these kind of methods usually rely on the particular heuristic variable extraction, which could inhibit generalization realization. This paper presents a distributed and parallel decision forest approach … …Journal of Computer Science, Vol. 15, Issue 5 · 11 May 2019 · 7,392 accessesView PDFCite
EditorialOpen accessIn the abstractFocalize the Structure of Myd88 in TLR Signaling Pathway to Modulate Innate Immune Response: New Target for Old DiseasesShuai Xing, Ping ZhouAll diseases have their Achilles’ Heel to target and this is especially true for immunorelated diseases which must be treated by targeting the immune system somewhere and somehow correctly. In the most recent decade, immunologists recognized that the Toll-Like Receptor (TLR) signaling pathway in innate immune system plays a double-edged role in the pathogenesis of many notorious diseases. Although the … …American Journal of Immunology, Vol. 13, Issue 3 · 6 Sep 2017 · 7,862 accessesView PDFCite