{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T13:54:12Z","timestamp":1758981252040,"version":"3.44.0"},"reference-count":84,"publisher":"Association for Computing Machinery (ACM)","issue":"2","funder":[{"DOI":"10.13039\/501100006374","name":"Ministry of Science and ICT, South Korea","doi-asserted-by":"publisher","award":["RS-2019-II190079"],"award-info":[{"award-number":["RS-2019-II190079"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"HORIZON EUROPE Framework Programme","doi-asserted-by":"publisher","award":["101162257"],"award-info":[{"award-number":["101162257"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006374","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["01IW21003"],"award-info":[{"award-number":["01IW21003"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2025,6,9]]},"abstract":"<jats:p>Sensor-based human activity recognition (HAR) has predominantly focused on Inertial Measurement Units and vision data, often overlooking the capabilities unique to pressure sensors, which capture subtle body dynamics and shifts in the center of mass. Despite their potential for postural and balance-based activities, pressure sensors remain underutilized in the HAR domain due to limited datasets. To bridge this gap, we propose to exploit generative foundation models with pressure-specific HAR techniques. Specifically, we present a bidirectional TextxPressure model that uses generative foundation models to interpret pressure data as natural language. TxP accomplishes two tasks: (1) Text2Pressure, converting activity text descriptions into pressure sequences, and (2) Pressure2Text, generating activity descriptions and classifications from dynamic pressure maps. Leveraging pre-trained models like CLIP and LLaMA 2 13B Chat, TxP is trained on our synthetic PressLang dataset, containing over 81,100 text-pressure pairs. Validated on real-world data for activities such as yoga and daily tasks, TxP provides novel approaches to data augmentation and classification grounded in atomic actions. This consequently improved HAR performance by up to 12.4% in macro F1 score compared to the state-of-the-art, advancing pressure-based HAR with broader applications and deeper insights into human movement. The data and code will be available on TxP.<\/jats:p>","DOI":"10.1145\/3732001","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T21:21:56Z","timestamp":1750281716000},"page":"1-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["TxP: Reciprocal Generation of Ground Pressure Dynamics and Activity Descriptions for Improving Human Activity Recognition"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7133-0205","authenticated-orcid":false,"given":"Lala Shakti Swarup","family":"Ray","sequence":"first","affiliation":[{"name":"DFKI, Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6294-2915","authenticated-orcid":false,"given":"Lars","family":"Krupp","sequence":"additional","affiliation":[{"name":"RPTU and DFKI, Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8371-2921","authenticated-orcid":false,"given":"Vitor Fortes","family":"Rey","sequence":"additional","affiliation":[{"name":"RPTU and DFKI, Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8976-5960","authenticated-orcid":false,"given":"Bo","family":"Zhou","sequence":"additional","affiliation":[{"name":"RPTU and DFKI, Kaiserslautern, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3723-1980","authenticated-orcid":false,"given":"Sungho","family":"Suh","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0320-6656","authenticated-orcid":false,"given":"Paul","family":"Lukowicz","sequence":"additional","affiliation":[{"name":"RPTU and DFKI, Kaiserslautern, Germany"}]}],"member":"320","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3239692"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/adfm.201905241"},{"key":"e_1_2_2_3_1","volume-title":"Single to Concurrent Sensor based Human Activity Recognition: Perception and Open Challenges","author":"Ankalaki Shilpa","year":"2024","unstructured":"Shilpa Ankalaki. 2024. Simple to Complex, Single to Concurrent Sensor based Human Activity Recognition: Perception and Open Challenges. IEEE Access (2024)."},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)CO.1943-7862.0001849"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3594739.3610713"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-15443-5"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21155240"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20071-7_33"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3651296"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.3389\/fbioe.2022.909653"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01321"},{"key":"e_1_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3158902"},{"key":"e_1_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.3390\/s23115281"},{"key":"e_1_2_2_14_1","volume-title":"Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al.","author":"Driess Danny","year":"2023","unstructured":"Danny Driess, Fei Xia, Mehdi SM Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, et al. 2023. Palm-e: An embodied multimodal language model. arXiv preprint arXiv:2303.03378 (2023)."},{"key":"e_1_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.3390\/mps5030045"},{"key":"e_1_2_2_16_1","volume-title":"Proceedings of the 2024 ACM International Symposium on Wearable Computers. 25--31","author":"Rey Vitor Fortes","year":"2024","unstructured":"Vitor Fortes Rey, Lala Shakti Swarup Ray, Qingxin Xia, Kaishun Wu, and Paul Lukowicz. 2024. Enhancing Inertial Hand based HAR through Joint Representation of Language, Pose and Synthetic IMUs. In Proceedings of the 2024 ACM International Symposium on Wearable Computers. 25--31."},{"key":"e_1_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01457"},{"key":"e_1_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICONSTEM.2016.7560922"},{"key":"e_1_2_2_19_1","volume-title":"Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752","author":"Gu Albert","year":"2023","unstructured":"Albert Gu and Tri Dao. 2023. Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752 (2023)."},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00186"},{"key":"e_1_2_2_21_1","volume-title":"Human activity recognition in artificial intelligence framework: a narrative review. Artificial intelligence review 55, 6","author":"Gupta Neha","year":"2022","unstructured":"Neha Gupta, Suneet K Gupta, Rajesh K Pathak, Vanita Jain, Parisa Rashidi, and Jasjit S Suri. 2022. Human activity recognition in artificial intelligence framework: a narrative review. Artificial intelligence review 55, 6 (2022), 4755--4808."},{"key":"e_1_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3173582"},{"volume-title":"2nd NeurIPS Workshop on Touch Processing: From Data to Knowledge.","author":"Han Isaac","key":"e_1_2_2_23_1","unstructured":"Isaac Han, Seoyoung Lee, Sangyeon Park, Ecehan Akan, Yiyue Luo, and Kyung-Joong Kim. [n. d.]. Smart Insole: Predicting 3D human pose from foot pressure. In 2nd NeurIPS Workshop on Touch Processing: From Data to Knowledge."},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02510"},{"key":"e_1_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1089\/soro.2020.0083"},{"key":"e_1_2_2_26_1","volume-title":"Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685","author":"Hu Edward J","year":"2021","unstructured":"Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021. Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021)."},{"key":"e_1_2_2_27_1","volume-title":"BSDGAN: Balancing Sensor Data Generative Adversarial Networks for Human Activity Recognition. In 2023 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8.","author":"Hu Yifan","year":"2023","unstructured":"Yifan Hu. 2023. BSDGAN: Balancing Sensor Data Generative Adversarial Networks for Human Activity Recognition. In 2023 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8."},{"key":"e_1_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.01.015"},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17217845"},{"key":"e_1_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/adhm.202001461"},{"key":"e_1_2_2_31_1","volume-title":"Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al.","author":"Jiang Albert Q","year":"2023","unstructured":"Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023. Mistral 7B. arXiv preprint arXiv:2310.06825 (2023)."},{"key":"e_1_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274357"},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411841"},{"key":"e_1_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01123"},{"key":"e_1_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3678545"},{"key":"e_1_2_2_36_1","volume-title":"International conference on machine learning. PMLR","author":"Li Junnan","year":"2023","unstructured":"Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023. Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In International conference on machine learning. PMLR, 19730--19742."},{"key":"e_1_2_2_37_1","volume-title":"Motion-x: A large-scale 3d expressive whole-body human motion dataset. Advances in Neural Information Processing Systems 36","author":"Lin Jing","year":"2024","unstructured":"Jing Lin, Ailing Zeng, Shunlin Lu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, and Lei Zhang. 2024. Motion-x: A large-scale 3d expressive whole-body human motion dataset. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/PerCom59722.2024.10494489"},{"key":"e_1_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1002\/adfm.202308175"},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3596711.3596800"},{"key":"e_1_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00554"},{"key":"e_1_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21010128"},{"key":"e_1_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.202109357"},{"key":"e_1_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.883"},{"key":"e_1_2_2_45_1","volume-title":"Yan Yan, and Anne HH Ngu.","author":"Ni Jianyuan","year":"2024","unstructured":"Jianyuan Ni, Hao Tang, Syed Tousiful Haque, Yan Yan, and Anne HH Ngu. 2024. A Survey on Multimodal Wearable Sensor-based Human Action Recognition. arXiv preprint arXiv:2404.15349 (2024)."},{"key":"e_1_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3361754"},{"key":"e_1_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01123"},{"key":"e_1_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00870"},{"key":"e_1_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/BHI.2017.7897206"},{"key":"e_1_2_2_50_1","volume-title":"International conference on machine learning. PMLR, 8748--8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748--8763."},{"key":"e_1_2_2_51_1","volume-title":"Mohammad Farukh Hashmi, and Aditya Gupta","author":"Rani Gundala Jhansi","year":"2023","unstructured":"Gundala Jhansi Rani, Mohammad Farukh Hashmi, and Aditya Gupta. 2023. Surface electromyography and artificial intelligence for human activity recognition-A systematic review on methods, emerging trends applications, challenges, and future implementation. IEEE Access (2023)."},{"key":"e_1_2_2_52_1","volume-title":"ALS-HAR: Harnessing Wearable Ambient Light Sensors to Enhance IMU-based HAR. arXiv preprint arXiv:2408.09527","author":"Swarup Ray Lala Shakti","year":"2024","unstructured":"Lala Shakti Swarup Ray, Daniel Gei\u00dfler, Mengxi Liu, Bo Zhou, Sungho Suh, and Paul Lukowicz. 2024. ALS-HAR: Harnessing Wearable Ambient Light Sensors to Enhance IMU-based HAR. arXiv preprint arXiv:2408.09527 (2024)."},{"key":"e_1_2_2_53_1","volume-title":"Bo Zhou, Sungho Suh, and Paul Lukowicz.","author":"Swarup Ray Lala Shakti","year":"2023","unstructured":"Lala Shakti Swarup Ray, Vitor Fortes Rey, Bo Zhou, Sungho Suh, and Paul Lukowicz. 2023. PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps. arXiv preprint arXiv:2308.00538 (2023)."},{"key":"e_1_2_2_54_1","volume-title":"2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 461--464","author":"Swarup Ray Lala Shakti","year":"2024","unstructured":"Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh, Lars Krupp, Vitor Fortes Rey, and Paul Lukowicz. 2024. Text me the data: Generating Ground Pressure Sequence from Textual Descriptions for HAR. In 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 461--464."},{"key":"e_1_2_2_55_1","volume-title":"2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 484--489","author":"Swarup Ray Lala Shakti","year":"2023","unstructured":"Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh, and Paul Lukowicz. 2023. Pressim: An end-to-end framework for dynamic ground pressure profile generation from monocular videos using physics-based 3d simulation. In 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 484--489."},{"key":"e_1_2_2_56_1","doi-asserted-by":"publisher","unstructured":"Lala Shakti Swarup Ray Bo Zhou Sungho Suh and Paul Lukowicz. 2025. OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Models. In ICASSP 2025 - 2025 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP). 1--5. doi:10.1109\/ICASSP49660.2025.10890689","DOI":"10.1109\/ICASSP49660.2025.10890689"},{"key":"e_1_2_2_57_1","volume-title":"Embodied hands: Modeling and capturing hands and bodies together. arXiv preprint arXiv:2201.02610","author":"Romero Javier","year":"2022","unstructured":"Javier Romero, Dimitrios Tzionas, and Michael J Black. 2022. Embodied hands: Modeling and capturing hands and bodies together. arXiv preprint arXiv:2201.02610 (2022)."},{"key":"e_1_2_2_58_1","first-page":"4537","article-title":"Concurrent Validity Evidence for Pressure-Sensing Walkways Measuring Spatiotemporal Features of Gait","volume":"24","author":"Sanders Ozell","year":"2024","unstructured":"Ozell Sanders, Bin Wang, and Kimberly Kontson. 2024. Concurrent Validity Evidence for Pressure-Sensing Walkways Measuring Spatiotemporal Features of Gait: A Systematic Review and Meta-Analysis. Sensors 24, 14 (2024), 4537.","journal-title":"A Systematic Review and Meta-Analysis. Sensors"},{"key":"e_1_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_32"},{"key":"e_1_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447226"},{"key":"e_1_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07883-1"},{"key":"e_1_2_2_62_1","volume-title":"Network Security and Data Sciences: Select Proceedings of 3rd International Conference on MIND","author":"Soni Vaibhav","year":"2023","unstructured":"Vaibhav Soni, Himanshu Yadav, Vijay Bhaskar Semwal, Bholanath Roy, Dilip Kumar Choubey, and Dheeresh K Mallick. 2023. A novel smartphone-based human activity recognition using deep learning in health care. In Machine Learning, Image Processing, Network Security and Data Sciences: Select Proceedings of 3rd International Conference on MIND 2021. Springer, 493--503."},{"key":"e_1_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2021.3053434"},{"key":"e_1_2_2_64_1","volume-title":"GRAB: A dataset of whole-body human grasping of objects. In Computer Vision-ECCV 2020: 16th European Conference","author":"Taheri Omid","year":"2020","unstructured":"Omid Taheri, Nima Ghorbani, Michael J Black, and Dimitrios Tzionas. 2020. GRAB: A dataset of whole-body human grasping of objects. In Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part IV 16. Springer, 581--600."},{"key":"e_1_2_2_65_1","volume-title":"Juliette Love, et al.","author":"Team Gemma","year":"2024","unstructured":"Gemma Team, Thomas Mesnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivi\u00e8re, Mihir Sanjay Kale, Juliette Love, et al. 2024. Gemma: Open models based on gemini research and technology. arXiv preprint arXiv:2403.08295 (2024)."},{"key":"e_1_2_2_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3494995"},{"key":"e_1_2_2_67_1","doi-asserted-by":"publisher","DOI":"10.15837\/ijccc.2019.6.3618"},{"key":"e_1_2_2_68_1","first-page":"6","article-title":"AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing","volume":"1","author":"Tsuchida Shuhei","year":"2019","unstructured":"Shuhei Tsuchida, Satoru Fukayama, Masahiro Hamasaki, and Masataka Goto. 2019. AIST Dance Video Database: Multi-Genre, Multi-Dancer, and Multi-Camera Database for Dance Information Processing.. In ISMIR, Vol. 1. 6.","journal-title":"ISMIR"},{"key":"e_1_2_2_69_1","volume-title":"Nurul Amin Choudhury, and Badal Soni","author":"Vamsi Repuri Mohan","year":"2024","unstructured":"Repuri Mohan Vamsi, Neha Adapa, Dinesh Yelamanchili, Nurul Amin Choudhury, and Badal Soni. 2024. An Efficient and Optimized CNN-LSTM Framework for Complex Human Activity Recognition System Using Surface EMG Physiological Sensors and Feature Engineering. In 2024 IEEE Students Conference on Engineering and Systems (SCES). IEEE, 1--6."},{"key":"e_1_2_2_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489106"},{"key":"e_1_2_2_71_1","volume-title":"Mex: Multi-modal exercises dataset for human activity recognition. arXiv preprint arXiv:1908.08992","author":"Wijekoon Anjana","year":"2019","unstructured":"Anjana Wijekoon, Nirmalie Wiratunga, and Kay Cooper. 2019. Mex: Multi-modal exercises dataset for human activity recognition. arXiv preprint arXiv:1908.08992 (2019)."},{"key":"e_1_2_2_72_1","doi-asserted-by":"publisher","DOI":"10.1145\/3654777.3676418"},{"key":"e_1_2_2_73_1","doi-asserted-by":"publisher","DOI":"10.1145\/3610927"},{"key":"e_1_2_2_74_1","doi-asserted-by":"publisher","DOI":"10.1145\/3659612"},{"key":"e_1_2_2_75_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13677-023-00552-1"},{"key":"e_1_2_2_76_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2016.2553038"},{"key":"e_1_2_2_77_1","volume-title":"Video-llama: An instruction-tuned audio-visual language model for video understanding. arXiv preprint arXiv:2306.02858","author":"Zhang Hang","year":"2023","unstructured":"Hang Zhang, Xin Li, and Lidong Bing. 2023. Video-llama: An instruction-tuned audio-visual language model for video understanding. arXiv preprint arXiv:2306.02858 (2023)."},{"key":"e_1_2_2_78_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01415"},{"key":"e_1_2_2_79_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20068-7_11"},{"key":"e_1_2_2_80_1","volume-title":"Meta-transformer: A unified framework for multimodal learning. arXiv preprint arXiv:2307.10802","author":"Zhang Yiyuan","year":"2023","unstructured":"Yiyuan Zhang, Kaixiong Gong, Kaipeng Zhang, Hongsheng Li, Yu Qiao, Wanli Ouyang, and Xiangyu Yue. 2023. Meta-transformer: A unified framework for multimodal learning. arXiv preprint arXiv:2307.10802 (2023)."},{"key":"e_1_2_2_81_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.202107758"},{"key":"e_1_2_2_82_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cej.2021.128649"},{"key":"e_1_2_2_83_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3534610","article-title":"Quali-mat: Evaluating the quality of execution in body-weight exercises with a pressure sensitive sports mat","volume":"6","author":"Zhou Bo","year":"2022","unstructured":"Bo Zhou, Sungho Suh, Vitor Fortes Rey, Carlos Andres Velez Altamirano, and Paul Lukowicz. 2022. Quali-mat: Evaluating the quality of execution in body-weight exercises with a pressure sensitive sports mat. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6, 2 (2022), 1--45.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_2_2_84_1","doi-asserted-by":"publisher","DOI":"10.1109\/ABC61795.2024.10652200"}],"container-title":["Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3732001","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T12:25:48Z","timestamp":1755865548000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3732001"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,9]]},"references-count":84,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,6,9]]}},"alternative-id":["10.1145\/3732001"],"URL":"https:\/\/doi.org\/10.1145\/3732001","relation":{},"ISSN":["2474-9567"],"issn-type":[{"type":"electronic","value":"2474-9567"}],"subject":[],"published":{"date-parts":[[2025,6,9]]},"assertion":[{"value":"2025-06-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}