{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T16:02:51Z","timestamp":1780502571952,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819520978","type":"print"},{"value":"9789819520985","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-2098-5_27","type":"book-chapter","created":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T12:00:15Z","timestamp":1761480015000},"page":"309-321","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A CNN\u2013LSTM-Based Prediction Method of\u00a0Lower-Limb Parameters Across Multiple Locomotion Modes"],"prefix":"10.1007","author":[{"given":"Wenke","family":"Lu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoran","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yichen","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wujing","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianquan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"issue":"8","key":"27_CR1","doi-asserted-by":"publisher","first-page":"4794","DOI":"10.3390\/app13084794","volume":"13","author":"TT Alemayoh","year":"2023","unstructured":"Alemayoh, T.T., Lee, J.H., Okamoto, S.: Leg-joint angle estimation from a single inertial sensor attached to various lower-body links during walking motion. Appl. Sci. 13(8), 4794 (2023)","journal-title":"Appl. Sci."},{"key":"27_CR2","doi-asserted-by":"publisher","first-page":"106970","DOI":"10.1016\/j.knosys.2021.106970","volume":"223","author":"SK Yadav","year":"2021","unstructured":"Yadav, S.K., Tiwari, K., Pandey, H.M., Akbar, S.A.: A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions. Knowl.-Based Syst. 223, 106970 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"27_CR3","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1109\/TNSRE.2016.2529581","volume":"25","author":"E Zheng","year":"2017","unstructured":"Zheng, E., Wang, Q.: Noncontact capacitive sensing-based locomotion transition recognition for amputees with robotic transtibial prostheses. IEEE Trans. Neural Syst. Rehabil. Eng. 25, 161\u2013170 (2017)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"8","key":"27_CR4","doi-asserted-by":"publisher","first-page":"2727","DOI":"10.3390\/s21082727","volume":"21","author":"H Prasanth","year":"2021","unstructured":"Prasanth, H., Caban, M., Keller, U., Courtine, G., Ijspeert, A., Vallery, H., von Zitzewitz, J.: Wearable sensor-based real-time gait detection: a systematic review. Sensors 21(8), 2727 (2021)","journal-title":"Sensors"},{"key":"27_CR5","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/1743-0003-9-9","volume":"9","author":"A K\u00f6se","year":"2012","unstructured":"K\u00f6se, A., Cereatti, A., Della Croce, U.: Bilateral step length estimation using a single inertial measurement unit attached to the pelvis. J. Neuroeng. Rehabil. 9, 9 (2012)","journal-title":"J. Neuroeng. Rehabil."},{"key":"27_CR6","doi-asserted-by":"crossref","unstructured":"Bennett, T., Jafari, R., Gans, N.: An extended Kalman filter to estimate human gait parameters and walking distance. In: Proceedings of the American Control Conference, p. 17 (2013)","DOI":"10.1109\/ACC.2013.6579926"},{"key":"27_CR7","unstructured":"Aswadh Khumar, G.S., Barath Kumar, J.K.: SVM based multiclass classifier for gait phase classification using shank IMU sensor. In: Proceedings of PSG College of Technology (2023)"},{"issue":"11","key":"27_CR8","doi-asserted-by":"publisher","first-page":"4242","DOI":"10.3390\/s22114242","volume":"22","author":"A Rattanasak","year":"2022","unstructured":"Rattanasak, A., et al.: Real-time gait phase detection using wearable sensors for transtibial prosthesis based on a KNN algorithm. Sensors 22(11), 4242 (2022)","journal-title":"Sensors"},{"key":"27_CR9","doi-asserted-by":"crossref","unstructured":"Hollinger, D., Jr Schall, M.C., Chen, H., Zabala, M.: The effect of sensor feature inputs on joint angle prediction across simple movements. Sens. (Basel) 24(11), 3657 (2024)","DOI":"10.3390\/s24113657"},{"issue":"9","key":"27_CR10","doi-asserted-by":"publisher","first-page":"2866","DOI":"10.3390\/s21082866","volume":"21","author":"H Huang","year":"2021","unstructured":"Huang, H., Zhou, P., Li, Y., Sun, F.: A lightweight attention-based CNN model for efficient gait recognition with wearable IMU sensors. Sensors 21(9), 2866 (2021)","journal-title":"Sensors"},{"issue":"21","key":"27_CR11","doi-asserted-by":"publisher","first-page":"8226","DOI":"10.3390\/s22218226","volume":"22","author":"MZ Arshad","year":"2022","unstructured":"Arshad, M.Z., Jamsrandorj, A., Kim, J., Mun, K.-R.: Gait events prediction using hybrid CNN-RNN-based deep learning models through a single waist-worn wearable sensor. Sensors 22(21), 8226 (2022)","journal-title":"Sensors"},{"key":"27_CR12","doi-asserted-by":"publisher","first-page":"10123","DOI":"10.1007\/s00521-023-08459-3","volume":"35","author":"G Iglesias","year":"2023","unstructured":"Iglesias, G., Talavera, E., Gonz\u00e1lez-Prieto, \u00c1., et al.: Data augmentation techniques in time series domain: a survey and taxonomy. Neural Comput. Appl. 35, 10123\u201310145 (2023)","journal-title":"Neural Comput. Appl."},{"key":"27_CR13","doi-asserted-by":"publisher","first-page":"107124","DOI":"10.1016\/j.compbiomed.2023.107124","volume":"163","author":"Q Song","year":"2023","unstructured":"Song, Q., Ma, X., Liu, Y.: Continuous online prediction of lower limb joints angles based on sEMG signals by deep learning approach. Comput. Biol. Med. 163, 107124 (2023)","journal-title":"Comput. Biol. Med."},{"key":"27_CR14","doi-asserted-by":"crossref","unstructured":"Zhou, H., et al.: Informer: beyond efficient transformer for long sequence time-series forecasting. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 11106\u201311115 (2021)","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"27_CR15","unstructured":"Shi, X., Chen, Z., Wang, H., Yeung, D.-Y., Wong, W.K., Woo, W.C.: Convolutional LSTM network: a machine learning approach for precipitation nowcasting. In: Advances in Neural Information Processing Systems 28 (NIPS 2015). Advances in Neural Information Processing Systems, vol. 28, pp. 802\u2013810 (2015)"},{"key":"27_CR16","doi-asserted-by":"publisher","first-page":"1032","DOI":"10.1109\/TNSRE.2019.2909585","volume":"27","author":"B-Y Su","year":"2019","unstructured":"Su, B.-Y., Wang, J., Liu, S.-Q., Sheng, M., Jiang, J., Xiang, K.: A CNN-based method for intent recognition using inertial measurement units and intelligent lower limb prosthesis. IEEE Trans. Neural Syst. Rehabil. Eng. 27, 1032\u20131042 (2019)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"27_CR17","doi-asserted-by":"publisher","first-page":"53540","DOI":"10.1109\/ACCESS.2021.3070646","volume":"9","author":"Y Shavit","year":"2021","unstructured":"Shavit, Y., Klein, I.: Boosting inertial-based human activity recognition with transformers. IEEE Access 9, 53540\u201353547 (2021)","journal-title":"IEEE Access"}],"container-title":["Lecture Notes in Computer Science","Intelligent Robotics and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-2098-5_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T12:00:20Z","timestamp":1761480020000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-2098-5_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"ISBN":["9789819520978","9789819520985"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-2098-5_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"27 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Robotics and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Okayama","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icira2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icira2025.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}