Journal Article2020Cited by 93

Human activity recognition from wearable sensor data using self-attention

Saif Mahmud, M Tonmoy, Kishor Kumar Bhaumik, AK Mahbubur Rahman, M Ashraful Amin, Mohammad Shoyaib, Muhammad Asif Hossain Khan, Amin Ahsan Ali

arXiv preprint arXiv:2003.09018

IOS Press, ISBN: 0922-6389

DOI: 10.3233/faia200236Open AccessURL

Abstract

Human Activity Recognition from body-worn sensor data poses an inherent challenge in capturing spatial and temporal dependencies of time-series signals. In this regard, the existing recurrent or convolutional or their hybrid models for activity recognition struggle to capture spatio-temporal context from the feature space of sensor reading sequence. To address this complex problem, we propose a self-attention based neural network model that foregoes recurrent architectures and utilizes different types of attention mechanisms to generate higher dimensional feature representation used for classification. We performed extensive experiments on four popular publicly available HAR datasets: PAMAP2, Opportunity, Skoda and USC-HAD. Our model achieve significant performance improvement over recent state-of-the-art models in both benchmark test subjects and Leave-one-subject-out evaluation. We also observe that the sensor attention maps produced by our model is able capture the importance of the modality and placement of the sensors in predicting the different activity classes.

Keywords

  • human activity recognition
  • self-attention
  • wearable sensors
  • Opportunity dataset
  • leave-one-subject-out evaluation
  • spatiotemporal dependencies
  • sensor placement
  • PAMAP2
  • attention maps

CCDS Authors

Saif Mahmud
Saif Mahmud

Saif Mahmud

  • Alumni, CCDS

  • PhD Student

    Cornell University, USA

  • BSc

    University of Dhaka, Bangladesh

Published at

PAKDD

Kishor Kumar Bhaumik
Kishor Kumar Bhaumik

Kishor Kumar Bhaumik

  • Alumni, CCDS

  • PhD student

    University of California, Riverside, USA

  • BSc

    Independent University, Bangladesh (IUB)

Published at

WACV, Pattern Recognition

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, Pattern Recognition, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Prof. Amin Ahsan Ali, PhD
Amin Ahsan Ali, PhD

Prof. Amin Ahsan Ali, PhD

  • Director, AI/ML Wing
  • Supervisor, ComBio Wing

  • Professor

    Department of Computer Science and Engineering

    Independent University, Bangladesh (IUB)

Published at

ACL, CHI, UbiComp, ECCV, IJCAI, ECAI, WACV, IPSN, PAKDD, LREC, IJCNN, ICPR, ICIP, BEA, BLP, ICMLA, Scientific Reports, Scientific Data, Pattern Recognition, Information Sciences, Ad Hoc Networks, Drug and Alcohol Dependence, PLOS ONE

Cited By

  1. 1.Harish Haresamudram, Irfan Essa, Thomas Plötz. (2021). Contrastive Predictive Coding for Human Activity Recognition. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 5(2), 1–26[10.1145/3463506]
  2. 2.Sungho Suh, Vitor Fortes Rey, Paul Lukowicz. (2022). TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation. Knowledge-Based Systems, 260, 110143[10.1016/j.knosys.2022.110143]
  3. 3.Ehab Essa, Islam R. Abdelmaksoud. (2023). Temporal-channel convolution with self-attention network for human activity recognition using wearable sensors. Knowledge-Based Systems, 278, 110867[10.1016/j.knosys.2023.110867]
  4. 4.Bulat Khaertdinov, Esam Ghaleb, Stylianos Asteriadis. (2021). Contrastive Self-supervised Learning for Sensor-based Human Activity Recognition. IEEE International Joint Conference on Biometrics (IJCB), 1–8[10.1109/ijcb52358.2021.9484410]
  5. 5.Yin Tang, Lei Zhang, Hao Wu, Jun He, Aiguo Song. (2022). Dual-Branch Interactive Networks on Multichannel Time Series for Human Activity Recognition. IEEE Journal of Biomedical and Health Informatics, 26(10), 5223–5234[10.1109/jbhi.2022.3193148]
  6. 6.Ye Zhang, Longguang Wang, Huiling Chen, Aosheng Tian, Shilin Zhou, Yulan Guo. (2022). IF-ConvTransformer. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 6(2), 1–26[10.1145/3534584]
  7. 7.Bulat Khaertdinov, Esam Ghaleb, Stylianos Asteriadis. (2021). Deep Triplet Networks with Attention for Sensor-based Human Activity Recognition. IEEE International Conference on Pervasive Computing and Communications, 1–10[10.1109/percom50583.2021.9439116]
  8. 8.Toufik Benmessabih, Rim Slama, Vincent Havard, David Baudry. (2024). Online human motion analysis in industrial context: A review. Engineering Applications of Artificial Intelligence, 131, 107850[10.1016/j.engappai.2024.107850]
  9. 9.Hui Chen, Charles Gouin-Vallerand, Kévin Bouchard, Sébastien Gaboury, Mélanie Couture, Nathalie Bier, Sylvain Giroux. (2024). Enhancing Human Activity Recognition in Smart Homes with Self-Supervised Learning and Self-Attention. Sensors, 24(3), 884[10.3390/s24030884]
  10. 10.Inyong Koo, Yeonju Park, Minki Jeong, Changick Kim. (2022). Contrastive Accelerometer–Gyroscope Embedding Model for Human Activity Recognition. IEEE Sensors Journal, 23(1), 506–513[10.1109/jsen.2022.3222825]
  11. 11.Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang. (2021). Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition. Information Fusion, 80, 1–22[10.1016/j.inffus.2021.10.009]
  12. 12.Harish Haresamudram, Chi Ian Tang, Sungho Suh, Paul Lukowicz, Thomas Plötz. (2025). Past, Present, and Future of Sensor-based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 9(2), 1–44[10.1145/3729467]
  13. 13.Bulat Khaertdinov, Stylianos Asteriadis, Esam Ghaleb. (2022). Dynamic Temperature Scaling in Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition. IEEE Transactions on Biometrics Behavior and Identity Science, 4(4), 498–507[10.1109/tbiom.2022.3180591]
  14. 14.Dongzhou Cheng, Lei Zhang, Lutong Qin, Shuoyuan Wang, Hao Wu, Aiguo Song. (2024). MaskCAE: Masked Convolutional AutoEncoder via Sensor Data Reconstruction for Self-Supervised Human Activity Recognition. IEEE Journal of Biomedical and Health Informatics, 28(5), 2687–2698[10.1109/jbhi.2024.3373019]
  15. 15.Shan Ullah, Mehdi Pirahandeh, Deok-Hwan Kim. (2023). Self-attention deep ConvLSTM with sparse-learned channel dependencies for wearable sensor-based human activity recognition. Neurocomputing, 571, 127157[10.1016/j.neucom.2023.127157]
  16. 16.Razvan Brinzea, Bulat Khaertdinov, Stylianos Asteriadis. (2022). Contrastive Learning with Cross-Modal Knowledge Mining for Multimodal Human Activity Recognition. International Joint Conference on Neural Networks (IJCNN), 01–08[10.1109/ijcnn55064.2022.9892522]
  17. 17.Shuoyuan Wang, Lei Zhang, Xing Wang, Wenbo Huang, Hao Wu, Aiguo Song. (2024). PatchHAR: A MLP-Like Architecture for Efficient Activity Recognition Using Wearables. IEEE Transactions on Biometrics Behavior and Identity Science, 6(2), 169–181[10.1109/tbiom.2024.3354261]
  18. 18.Gabriela Augustinov, Muhammad Adeel Nisar, Frédéric Li, Amir Tabatabaei, Marcin Grzegorzek, Keywan Sohrabi, Sebastian Fudickar. (2022). Transformer-Based Recognition of Activities of Daily Living from Wearable Sensor Data. International Workshop on Sensor-based Activity Recognition and Interaction (iWOAR), 1–8[10.1145/3558884.3558895]
  19. 19.Sungho Suh, Vitor Fortes Rey, Paul Lukowicz. (2022). Adversarial Deep Feature Extraction Network for User Independent Human Activity Recognition. IEEE International Conference on Pervasive Computing and Communications, 217–226[10.1109/percom53586.2022.9762387]
  20. 20.Manuel Gil-Martín, Rubén San-Segundo, Fernando Fernández-Martínez, Javier Ferreiros-López. (2021). Time Analysis in Human Activity Recognition. Neural Processing Letters, 53(6), 4507–4525[10.1007/s11063-021-10611-w]
  21. 21.Jaime Morales, Naoya Yoshimura, Qingxin Xia, Atsushi Wada, Yasuo Namioka, Takuya Maekawa. (2022). Acceleration-based Human Activity Recognition of Packaging Tasks Using Motif-guided Attention Networks. IEEE International Conference on Pervasive Computing and Communications, 1–12[10.1109/percom53586.2022.9762388]
  22. 22.Rana Sabah, Meng Chun Lam, Faizan Qamar, B. B. Zaidan. (2024). A BiLSTM-Based Feature Fusion With CNN Model: Integrating Smartphone Sensor Data for Pedestrian Activity Recognition. IEEE Access, 12, 142957–142978[10.1109/access.2024.3468470]
  23. 23.Yan Wang, Xin Wang, Hongmei Yang, Yingrui Geng, Hongnian Yu, Ge Zheng, Liang Liao. (2023). MhaGNN: A Novel Framework for Wearable Sensor-Based Human Activity Recognition Combining Multi-Head Attention and Graph Neural Networks. IEEE Transactions on Instrumentation and Measurement, 72, 1–14[10.1109/tim.2023.3276004]
  24. 24.Bulat Khaertdinov, Stylianos Asteriadis. (2022). Temporal Feature Alignment in Contrastive Self-Supervised Learning for Human Activity Recognition. IEEE International Joint Conference on Biometrics (IJCB), 1–9[10.1109/ijcb54206.2022.10007984]
  25. 25.M. Tanjid Hasan Tonmoy, Saif Mahmud, A. K. M. Mahbubur Rahman, M. Ashraful Amin, Amin Ahsan Ali. (2021). Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition. Lecture notes in computer science, 351–363[10.1007/978-3-030-75768-7_28]
  26. 26.Xuan Li, Hengxin Chen, Shengdong He, Xinrun Chen, Shuang Dong, Ping Yan, Bin Fang. (2023). Action recognition based on multimode fusion for VR online platform. Virtual Reality, 27(3), 1797–1812[10.1007/s10055-023-00773-4]
  27. 27.Saltanat Aidarova, Temirlan Nurmakhan, Rakhat Myrzakhan, Siamac Fazli, Adnan Yazici. (2025). Advancing Activity Recognition With Multimodal Fusion and Transformer Techniques. IEEE Sensors Journal, 25(11), 19632–19649[10.1109/jsen.2025.3555663]
  28. 28.Lei Jin, Xiaojuan Wang, Jiaming Chu, Mingshu He. (2021). Human Activity Recognition Machine With an Anchor-Based Loss Function. IEEE Sensors Journal, 22(1), 741–756[10.1109/jsen.2021.3130761]
  29. 29.Yong Li, Luping Wang, Fen Liu. (2022). Multi-Branch Attention-Based Grouped Convolution Network for Human Activity Recognition Using Inertial Sensors. Electronics, 11(16), 2526[10.3390/electronics11162526]
  30. 30.Feng Xu, Xuchen Gao, Weigang Wang. (2025). A human activity recognition model based on deep neural network integrating attention mechanism. Scientific Reports, 15(1), 23192[10.1038/s41598-025-98763-w]
  31. 31.Tobias King, Yexu Zhou, Tobias Röddiger, Michael Beigl. (2025). MicroNAS for memory and latency constrained hardware aware neural architecture search in time series classification on microcontrollers. Scientific Reports, 15(1), 7575[10.1038/s41598-025-90764-z]
  32. 32.Jiaoyi Wu, Hexiang Zhang, Enzan Xiao, Tianshuang Liang, Xiaolong Zou, Jiantong Sun, Chengliang Fan, Zutao Zhang. (2025). Driver abnormal behavior detection enabled self-powered magnetic suspension hybrid wristband and AI for smart transportation. Energy Conversion and Management, 326, 119485[10.1016/j.enconman.2025.119485]
  33. 33.Yu Liang, Kaile Feng, Zizhuo Ren. (2023). Human Activity Recognition Based on Transformer via Smart-phone Sensors. International Conference on Computer Communication and Artificial Intelligence (CCAI), 267–271[10.1109/ccai57533.2023.10201297]
  34. 34.Yuxin Zhang, Pari Delir Haghighi, Frada Burstein, Lina Yao, Flavia Cicuttini. (2021). On-Device Lumbar-Pelvic Movement Detection Using Dual-IMU: A DNN-Based Approach. IEEE Access, 9, 62241–62254[10.1109/access.2021.3074755]
  35. 35.Mohammad Belal, Taimur Hassan, Abdelfatah Hassan, Divya Velayudhan, Noureldin Elhendawi, Ahmad Aljarah, Irfan Hussain. (2025). FSID: a novel approach to human activity recognition using few-shot weight imprinting. Scientific Reports, 15(1), 20865[10.1038/s41598-025-04323-7]
  36. 36.Federica Comuni, Christopher Meszaros, Niklas Akerblom, Morteza Haghir Chehreghani. (2022). Passive and Active Learning of Driver Behavior from Electric Vehicles. IEEE International Conference on Intelligent Transportation Systems (ITSC), 929–936[10.1109/itsc55140.2022.9922012]
  37. 37.Minjung Lee, Seoung Bum Kim. (2022). Sensor-Based Open-Set Human Activity Recognition Using Representation Learning With Mixup Triplets. IEEE Access, 10, 119333–119344[10.1109/access.2022.3221425]
  38. 38.Emanuele Lattanzi, Lorenzo Calisti, Chiara Contoli. (2024). Are Transformers a Useful Tool for Tiny devices in Human Activity Recognition?. International Conference on Advances in Artificial Intelligence (ICAAI), 339–344[10.1145/3704137.3704171]
  39. 39.Wenbo Zhao, Ling Fan. (2024). Time-series representation learning via Time-Frequency Fusion Contrasting. Frontiers in Artificial Intelligence, 7, 1414352[10.3389/frai.2024.1414352]
  40. 40.Rebeen Ali Hamad, Wai Lok Woo, Bo Wei, Longzhi Yang. (2025). Self-Supervised Learning for Activity Recognition Based on Datasets With Imbalanced Classes. IEEE Transactions on Emerging Topics in Computational Intelligence, 9(5), 3441–3454[10.1109/tetci.2025.3526504]
  41. 41.Ayokunle Olalekan Ige, Mohd Halim Mohd Noor. (2022). A lightweight deep learning with feature weighting for activity recognition. Computational Intelligence, 39(2), 315–343[10.1111/coin.12565]
  42. 42.Matej Kralik, Marek Suppa. (2021). Waveglove: Transformer-Based Hand Gesture Recognition Using Multiple Inertial Sensors. European Signal Processing Conference (EUSIPCO), 1576–1580[10.23919/eusipco54536.2021.9616000]
  43. 43.Yan Mao, Guoyin Zhang, Cuicui Ye. (2024). A Spatio-temporal Graph Transformer driven model for recognizing fine-grained data human activity. Alexandria Engineering Journal, 104, 31–45[10.1016/j.aej.2024.06.042]
  44. 44.Shizhuo Deng, Zhubao Guo, Da Teng, Boqian Lin, Dongyue Chen, Tong Jia, Hao Wang. (2023). Self-relation attention networks for weakly supervised few-shot activity recognition. Knowledge-Based Systems, 276, 110720[10.1016/j.knosys.2023.110720]
  45. 45.Monika Arya, Hanumat Sastry G. (2022). Ensemble Federated Learning for Classifying IoMT Data Streams. IEEE International Conference for Convergence in Technology (I2CT), 1–5[10.1109/i2ct54291.2022.9824145]
  46. 46.Taoran Sheng, Manfred Huber. (2025). Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches. Sensors, 25(13), 4032[10.3390/s25134032]
  47. 47.Vanessa Camilleri, Reno Yuri Camilleri, Mark Fialovszky, Daniel Pace, Dylan Seychell, Matthew Montebello. (2025). Towards Explainable Multimodal Sensing for Swimming Analysis: Early Findings from the SWIM-360 Project. Sensors, 25(22), 7047[10.3390/s25227047]
  48. 48.Vitor Fortes Rey, Pedro Martelleto Bressane Rezende, Bo Zhou, Sungho Suh, Paul Lukowicz. (2025). COA-HAR: Exploring contrastive online test-time adaptation for wearable sensor-based human activity recognition using sensor data augmentation. Expert Systems with Applications, 297, 129288[10.1016/j.eswa.2025.129288]
  49. 49.Andrés Tello, Victoria Degeler. (2025). Contrasting Global and Local Representations for Human Activity Recognition using Graph Neural Networks. ACM Symposium on Applied Computing, 630–637[10.1145/3672608.3707743]
  50. 50.Lei Wang, Yicheng Yan, Dongsheng Huang, Yuanyuan Pan, Chak Fong Cheang, Kunming Luo, Jianqing Li. (2025). AHARNet: Adaptive Human Activity Recognition Model for Multimodal Consumer Electronics With Different Computation Resources. IEEE Transactions on Consumer Electronics, 71(2), 5847–5855[10.1109/tce.2025.3540853]
  51. 51.Sina Elahi, Tom Mery, Christophe Panthier, Alain Saad, Damien Gatinel, Alexandre Alahi. (2024). Eye-Rubbing Detection Using a Smartwatch: A Feasibility Study Demonstrated High Accuracy With Machine Learning. Translational Vision Science & Technology, 13(9), 1[10.1167/tvst.13.9.1]
  52. 52.Rebeen Ali Hamad, Longzhi Yang, Wai Lok Woo, Bo Wei. (2022). Cross-Domain Activity Recognition Using Shared Representation in Sensor Data. IEEE Sensors Journal, 22(13), 13273–13284[10.1109/jsen.2022.3178083]
  53. 53.Ramachandra, Sandeep, Hoelzemann, Alexander, Van Laerhoven, Kristof. (2021). Transformer Networks for Data Augmentation of Human Physical Activity Recognition. arXiv (Cornell University)[10.48550/arxiv.2109.01081]
  54. 54.Shikha Dixit, Shivi Goel, Sneha Jaiswal, Puneet Kumar Goyal. (2024). Driver Behaviour Analysis to Improve Road Safety: A Comprehensive Study. International Conference on Computing, Sciences and Communications (ICCSC), 1–5[10.1109/iccsc62048.2024.10830329]
  55. 55.Xin Wang, Yan Wang, Chenggang Lu, Hongnian Yu, Hongli He, Zhikang Li. (2021). A case study: effect of wrist sensor displacement on HAR performance using LSTM and attention mechanism. International Conference on Advanced Mechatronic Systems, 103–108[10.1109/icamechs54019.2021.9661535]
  56. 56.Md. Hasan Tarek, Md. Eusha Kadir, Mahir Mahbub, Pritom Saha Akash, Amin Ahsan Ali, Mohammad Shoyaib. (2020). Mutual Information based Feature Selection for Nurse Care Activity Recognition. International Conference on Informatics, Electronics & Vision (ICIEV), 1–6[10.1109/icievicivpr48672.2020.9306645]
  57. 57.Meenambika Chandirakumar, Thanushanth Kanagarajah, Nithursika Kalanantharasan, Sandareka Wickramanayake, Dulani Meedeniya. (2025). Human Activity Recognition Using Spatio-Temporal Dual Attention with Cross-Sensor Attention. International Joint Conference on Neural Networks (IJCNN), 1–8[10.1109/ijcnn64981.2025.11228134]
  58. 58.Han Wu, Haotian Feng, Lida Shi, Hongda Zhang, Hao Xu. (2024). The SES framework and Frequency domain information fusion strategy for Human activity recognition. International Joint Conference on Neural Networks (IJCNN), 1–9[10.1109/ijcnn60899.2024.10650417]
  59. 59.Orhan Torkul, Íhsan Hakan Selví, Merve Şíşcí, Deníz Demírcíoğlu Díren. (2024). A New Model for Assembly Task Recognition: A Case Study of Seru Production System. IEEE Access, 12, 157418–157442[10.1109/access.2024.3484955]
  60. 60.Shengzhi Wang, Shuo Xiao, Yu Wang, Haifeng Jiang, Guopeng Zhang. (2022). A Deep Dilated Convolutional Self-attention Model for Multimodal Human Activity Recognition. Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition, 16, 791–797[10.1109/icpr56361.2022.9956723]
  61. 61.G R Nithin, Mihika Chhabra, Yujiao Hao, Boyu Wang, Rong Zheng. (2021). Sensor-Based Human Activity Recognition for Elderly In-patients with a Luong Self-Attention Network. IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, 97–101[10.1109/chase52844.2021.00019]
  62. 62.Moumita Bhattacharya, Qingquan Sun, Jiang Lu, Yunfei Hou. (2025). Application of Transformer to Wearable Sensor-based Complex Human Activity Recognition. International Conference on Artificial Intelligence and Big Data (ICAIBD), 585–588[10.1109/icaibd64986.2025.11082055]
  63. 63.Mehdi Ejtehadi, Gloria Edumaba Graham, Cailin Ringstrom, Elisa Du, Robert Riener, Diego Paez-Granados. (2025). Tifex-Py: Time-Series Feature Extraction for Python in a Human Activity Recognition Scenario. International Conference on Rehabilitation Robotics, 2025, 1332–1339[10.1109/icorr66766.2025.11062978]
  64. 64.Su Hu, Junyu Zeng, Ximing Lin, Xin Zhong, Fangyi Liang, Peixi Chen, Xuemei Bai. (2025). Accident LLM: A multimodal large language model of accident description based on Inter-Frame Attention Mechanism. International Symposium on Computer Applications and Information Systems (ISCAIS), 345–350[10.1109/iscait64916.2025.11010470]
  65. 65.Qian Huang, ZhongQi Chen, Chang Li, WeiWen Qian. (2025). Human Action Recognition in Multi-Level Convolutional Temporal Attention Network. IEEE International Conference on Acoustics Speech and Signal Processing, 1–5[10.1109/icassp49660.2025.10889140]
  66. 66.Max Conway, Brian Reily, Christopher Reardon. (2024). Learned Sensor Fusion For Robust Human Activity Recognition in Challenging Environments. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 11537–11543[10.1109/iros58592.2024.10802830]
  67. 67.Jaehyuk An, Younghoon Kwon, Yoon-Sik Cho. (2023). A Supervised Autoencoder for Human Activity Recognition with Inertial Sensors. IEEE International Conference on Big Data (BigData), 1–5[10.1109/bigdata59044.2023.10416944]
  68. 68.Fuqin Deng, Yongshen Huang, Guangwen Yao, Hufei Zhu, Bing Luo, Shufen Liang, Ningbo Yi. (2022). Improving Convolution Neural Networks with Window-based Transformer Blocks for Laser Welding Process Monitoring. IEEE International Conference on Industrial Technology (ICIT), 25, 1–8[10.1109/icit48603.2022.10002719]
  69. 69.Changhao Ni, Shengxiao Guan. (2021). A Parallel Network used to Human Activity Recognition. International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE), 11912, 359–362[10.1109/icbaie52039.2021.9389941]
  70. 70.Riyad Bin Rafiq, Weishi Shi, Mark V. Albert. (2026). KARL: Knowledge-Attentive Representation Learning for Wearable Hand Gesture Recognition in Motor-Impaired Individuals. Lecture notes in computer science, 530–546[10.1007/978-3-032-37679-4_30]
  71. 71.Bo Wu. (2026). ARMA-Net: Adaptive Reliability-Aware Modality Attention for Missing-Modality Multisource IoT Sensor Fusion. IEEE Internet of Things Journal, 13(21), 49670–49678[10.1109/jiot.2026.3725660]
  72. 72.Yichao Diao, Hoi Leong Lee, Gang Jin. (2026). MST-HDQ: Multi-Scale temporal hash discriminative quantization for wearable sensor sequence recognition. Journal of King Saud University - Computer and Information Sciences, 38(7)[10.1007/s44443-026-01053-2]
  73. 73.Sakorn Mekruksavanich, Wikanda Phaphan, Anuchit Jitpattanakul. (2026). A Lightweight Multi-Scale Convolution-Attention Transformer for IMU-Based Human Activity Recognition on Wearable Devices. International Conference on Big Data Analytics and Practices (IBDAP), 1–6[10.1109/ibdap69915.2026.11677760]
  74. 74.Monu Nagar, Himani Sikarwar, Debasis Das. (2026). Enhancing Cross-User Generalization in Human Activity Recognition With Adaptive Noise Scheduling and Linear Attention. IEEE Sensors Journal, 26(14), 21626–21635[10.1109/jsen.2026.3694802]
  75. 75.Zhonghang Li, Fucheng Miao, Wei Zhang, Guan Gui. (2026). Wearable Sensor-Based Human Activity Recognition Using Deep Spiking Convolutional LSTM with Residual Attention. Information Communication Technologies Conference (ICTC), 195–199[10.1109/ictc70246.2026.11650001]
  76. 76.Yaxiong Lei, Hyochan Cho, Fergus Buchanan, Shijing He, Xinya Gong, Yuheng Wang, Juan Ye. (2026). TinyGaze: Lightweight Gaze-Gesture Recognition on Commodity Mobile Devices. CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA), 1–6[10.1145/3772363.3798475]
  77. 77.Francisco M. Calatrava-Nicolas, Vitor Fortes Rey, Paul Lukowicz, Todor Stoyanov, Oscar Martinez Mozos. (2026). Rotation Estimation Auxiliary Task for Wrist Inertial-Based Human Activity Recognition. IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 1–6[10.1109/percomworkshops68308.2026.11585279]
  78. 78.Priyanka Kaushik, Jigar Soni, Bhawna, Neeraj Varshney, Anshika Tyagi, Krishan Kumar Garg. (2026). Design and Implementation of an Artificial Intelligence—Based System for Stock Market Prediction and Investment Insights. IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), 1–5[10.1109/iatmsi68868.2026.11465588]
  79. 79.Oktay Ozan Güner, Sergio Consoli, Vicenç Gómez, Mario Ceresa. (2026). Differentially Private Fine-Tuning of Self-Supervised Learning Models for Human Activity Recognition on Wearables. Communications in computer and information science, 3–20[10.1007/978-3-032-16708-8_1]
  80. 80.Taoran Sheng, Manfred Huber. (2025). Label-Efficient Human Activity Recognition from Wearables via Self-Supervised Representation Learning. International Conference on Machine Learning and Applications, 316–323[10.1109/icmla66185.2025.00049]
  81. 81.E. Riveros, D. Vega-Oliveros, A. Soriano-Vargas, A. Rocha. (2025). Towards Intelligent Dietary Monitoring: Deep Learning Techniques for Alimentary Activity Detection. International Conference on Soft Computing & Machine Intelligence (ISCMI), 604–608[10.1109/iscmi67495.2025.11357866]
  82. 82.Anjani Kumar Reddy Challa, Vamshi Krishna Raavi, Harshavardan Bandari, Dhanvanth Kumar Gude, Siddharth Kumar. (2025). Human Activity Recognition Reimagined: The CGRNHAR Self-Supervised Approach. Global AI Summit - International Conference on Artificial Intelligence and Emerging Technology (AI Summit), 359–364[10.1109/aisummit66170.2025.11411187]
  83. 83.Aadhira Suleim A R, Anlin Sahaya Infant Tinu M. (2025). Smart Wearable Sensor System for Real-Time Biomechanical Analysis with AI Integration. International Conference on Biomedical Engineering and Sustainable Healthcare (ICBMESH), 1–6[10.1109/icbmesh66209.2025.11182236]
  84. 84.Jinghua Yan, Wenkai Zhou, Wei Zhang, Yuchao Lu, Lin Huang. (2025). MHCAGE:Multi-Head Attention-based Combined Accelerometer and Gyroscope Embedding Network. International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE), 631–636[10.1109/aemcse65292.2025.11042562]
  85. 85.Jiangtao Fan, Anish Jindal, Amir Atapour-Abarghouei. (2025). Multi-scale Efficient Spatial Attention on Human Activity Recognition Using Wearable Sensors. Communications in computer and information science, 150–164[10.1007/978-981-96-6963-9_11]
  86. 86.Haoning Wu, Shaowu Wu, Zhicheng Zhang, Hao Zhou, Xiaoping Wu, Xiaoguang Niu, Duo Li. (2025). MPAM: Dual-Transformer for Millimeter-Wave Sensing Based Multi-person Activity Monitoring System. Lecture notes in computer science, 320–331[10.1007/978-981-96-8728-2_26]
  87. 87.Joel Osei-Asamoah, Nathan Amanquah. (2024). Recognition of Walking Terrain Using Machine Learning. IEEE International Conference on Adaptive Science & Technology, 1–6[10.1109/icast61769.2024.10856487]
  88. 88.Jiancong Ye, Mengxuan Wang, Junpei Zhong, Hongjie Jiang. (2024). A review on devices and learning techniques in domestic intelligent environment. Journal of Ambient Intelligence and Humanized Computing, 15(4), 2361–2380[10.1007/s12652-024-04759-1]
  89. 89.Utkarsh Mishra, Sarthak Tyagi, Puneet Goyal, Shruti Gupta. (2024). A Novel Approach Distracted Driver Detection System Using ML Techniques. SSRN Electronic Journal[10.2139/ssrn.4811988]
  90. 90.Bulat Khaertdinov. (2024). Feature representation learning for human activity recognition. [10.26481/dis.20240618bk]
  91. 91.Weilin Li, Xueying Wang, Hong Wu. (2023). Multiscale Class-Attention Transformer for Bird Migration State Prediction. International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 34, 1–5[10.1109/iccwamtip60502.2023.10387026]
  92. 92.Linh Trinh, Bach Ha. (2022). An incorporation of deep temporal convolutional networks with hidden markov models post-processing for sensor-based human activity recognition. International Symposium on Information and Communication Technology, 96–102[10.1145/3568562.3568610]
  93. 93.Jianning Wu, Qiaoling Tan, Xiaoyan Wu. (2022). An Advanced Attention-Enhanced Hybrid Deep Learning Model for WBSNs’ Gait Pattern Recognition. Research Square[10.21203/rs.3.rs-1251973/v1]
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