{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:57:54Z","timestamp":1740099474854,"version":"3.37.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030275310"},{"type":"electronic","value":"9783030275327"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-27532-7_2","type":"book-chapter","created":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T18:02:59Z","timestamp":1564682579000},"page":"15-25","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Angular Velocity Estimation of Knee Joint Based on MMG Signals"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4597-8585","authenticated-orcid":false,"given":"Chenlei","family":"Xie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4060-4234","authenticated-orcid":false,"given":"Daqing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7149-9580","authenticated-orcid":false,"given":"Haifeng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8653-5633","authenticated-orcid":false,"given":"Lifu","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,2]]},"reference":[{"issue":"4","key":"2_CR1","first-page":"267","volume":"67","author":"DT Barry","year":"1986","unstructured":"Barry, D.T., Leonard, J.A., Gitter, A.J., Ball, R.D.: Acoustic myography as a control signal for an externally powered prosthesis. Arch. Phys. Med. Rehabil. 67(4), 267\u2013269 (1986)","journal-title":"Arch. Phys. Med. Rehabil."},{"issue":"2","key":"2_CR2","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1088\/0967-3334\/24\/2\/307","volume":"24","author":"R Boostani","year":"2003","unstructured":"Boostani, R., Moradi, M.H.: Evaluation of the forearm EMG signal features for the control of a prosthetic hand. Physiol. Meas. 24(2), 309\u2013319 (2003)","journal-title":"Physiol. Meas."},{"unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines (2001). \n                      http:\/\/www.csie.ntu.edu.tw\/scjlin\/libsvm","key":"2_CR3"},{"key":"2_CR4","doi-asserted-by":"publisher","first-page":"50","DOI":"10.3389\/fnbot.2018.00050","volume":"12","author":"MA Dzulkifli","year":"2018","unstructured":"Dzulkifli, M.A., Hamzaid, N.A., Davis, G.M.O., Hasnan, N.: Neural network-based muscle torque estimation using mechanomyography during electrically-evoked knee extension and standing in spinal cord injury. Front. Neurorobot. 12, 50 (2018)","journal-title":"Front. Neurorobot."},{"issue":"6","key":"2_CR5","doi-asserted-by":"publisher","first-page":"691","DOI":"10.1016\/j.clinbiomech.2014.04.003","volume":"29","author":"MO Ibitoye","year":"2014","unstructured":"Ibitoye, M.O., Hamzaid, N.A., Zuniga, J.M., Wahab, A.K.A.: Mechanomyography and muscle function assessment: a review of current state and prospects. Clin. Biomech. 29(6), 691\u2013704 (2014)","journal-title":"Clin. Biomech."},{"doi-asserted-by":"crossref","unstructured":"John, A., Vijayan, A.E., Sudheer, A.P.: Electromyography based control of robotic arm using entropy and zero crossing rate. In: Proceedings of the 2015 Conference on Advances in Robotics \u2013 Air 2015, Goa, India, 02\u201304 July 2015, pp. 1\u20136. ACM Press (2015)","key":"2_CR6","DOI":"10.1145\/2783449.2783519"},{"doi-asserted-by":"crossref","unstructured":"Khezri, M., Jahed, M.: An inventive quadratic time-frequency scheme based on Wigner-Ville distribution for classification of sEMG signals. In: 2007 6th International Special Topic Conference on Information Technology Applications in Biomedicine. IEEE (2007)","key":"2_CR7","DOI":"10.1109\/ITAB.2007.4407397"},{"key":"2_CR8","first-page":"1","volume":"2017","author":"Suin Kim","year":"2017","unstructured":"Kim, S., Ro, K., Bae, J.: Estimation of individual muscular forces of the lower limb during walking using a wearable sensor system. J. Sens. 2017 (2017)","journal-title":"Journal of Sensors"},{"doi-asserted-by":"crossref","unstructured":"Kosaki, T., Tochiki, A., Li, S., Kanazawa, R.: Torque estimation of elbow joint using a mechanomyogram signal based biomechanical model. In: 2018 12th France-Japan and 10th Europe-Asia Congress on Mechatronics, pp. 260\u2013265. IEEE (2018)","key":"2_CR9","DOI":"10.1109\/MECATRONICS.2018.8495874"},{"issue":"02","key":"2_CR10","doi-asserted-by":"publisher","first-page":"1350020","DOI":"10.4015\/S1016237213500208","volume":"25","author":"KF Lei","year":"2013","unstructured":"Lei, K.F., Cheng, S.C., Lee, M.Y., Lin, W.Y.: Measurement and estimation of muscle contraction strength using mechanomyography based on artificial neural network algorithm. Biomed. Eng. Appl. Basis Commun. 25(02), 1350020 (2013)","journal-title":"Biomed. Eng. Appl. Basis Commun."},{"issue":"1","key":"2_CR11","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1109\/TCYB.2014.2386856","volume":"46","author":"Y Na","year":"2016","unstructured":"Na, Y., Choi, C., Lee, H.D., Kim, J.: A study on estimation of joint force through isometric index finger abduction with the help of SEMG peaks for biomedical applications. IEEE Trans. Cybern. 46(1), 2\u20138 (2016)","journal-title":"IEEE Trans. Cybern."},{"issue":"4","key":"2_CR12","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/1050-6411(93)90009-L","volume":"3","author":"S Nadeau","year":"1993","unstructured":"Nadeau, S., Bilodeau, M., Delisle, A.: The influence of the type of contraction on the masseter muscle EMG power spectrum. J. Electromyogr. Kinesiol. 3(4), 205\u2013213 (1993)","journal-title":"J. Electromyogr. Kinesiol."},{"doi-asserted-by":"crossref","unstructured":"Park, J., Kim, S.J., Na, Y., Kim, J.: Custom optoelectronic force sensor based ground reaction force (GRF) measurement system for providing absolute force. In: 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp. 75\u201377. IEEE (2016)","key":"2_CR13","DOI":"10.1109\/URAI.2016.7734024"},{"key":"2_CR14","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.jelekin.2018.04.001","volume":"41","author":"K Plewa","year":"2018","unstructured":"Plewa, K., Samadani, A., Orlandi, S., Chau, T.: A novel approach to automatically quantify the level of coincident activity between EMG and MMG signals. J. Electromyogr. Kinesiol. 41, 34\u201340 (2018)","journal-title":"J. Electromyogr. Kinesiol."},{"doi-asserted-by":"crossref","unstructured":"Richman, J.S., Lake, D.E., Moorman, J.R.: Sample entropy. In: Methods in Enzymology, vol. 384, pp. 172\u2013184. Academic Press (2004)","key":"2_CR15","DOI":"10.1016\/S0076-6879(04)84011-4"},{"issue":"1","key":"2_CR16","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1080\/10803548.2015.1116817","volume":"22","author":"D Roman-Liu","year":"2016","unstructured":"Roman-Liu, D.: The influence of confounding factors on the relationship between muscle contraction level and MF and MPF values of EMG signal: a review. Int. J. Occup. Saf. Ergon. 22(1), 77\u201391 (2016)","journal-title":"Int. J. Occup. Saf. Ergon."},{"issue":"5","key":"2_CR17","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1109\/TNSRE.2009.2032640","volume":"17","author":"JW Sensinger","year":"2009","unstructured":"Sensinger, J.W., Schultz, A.E., Kuiken, T.A.: Examination of force discrimination in human upper limb amputees with reinnervated limb sensation following peripheral nerve transfer. IEEE Trans. Neural Syst. Rehabil. Eng. 17(5), 438\u2013444 (2009)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"unstructured":"Silva, J., Heim, W., Chau, T.: MMG-based classification of muscle activity for prosthesis control. In: The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 1, pp. 968\u2013971. IEEE (2004)","key":"2_CR18"},{"doi-asserted-by":"crossref","unstructured":"Takei, Y., Yoshida, M., Takeshita, T., Kobayashi, T.: Wearable muscle training and monitoring device. In: 2018 IEEE Micro Electro Mechanical Systems (MEMS), pp. 55\u201358. IEEE (2018)","key":"2_CR19","DOI":"10.1109\/MEMSYS.2018.8346480"},{"issue":"1\u201313","key":"2_CR20","first-page":"79","volume":"10","author":"I Talib","year":"2018","unstructured":"Talib, I., Sundaraj, K., Lam, C.K.: Choice of mechanomyography sensors for diverse types of muscle activities. J. Telecommun. Electron. Comput. Eng. (JTEC) 10(1\u201313), 79\u201382 (2018)","journal-title":"J. Telecommun. Electron. Comput. Eng. (JTEC)"},{"key":"2_CR21","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.jelekin.2017.10.010","volume":"38","author":"H Wu","year":"2018","unstructured":"Wu, H., Wang, D., Huang, Q., Gao, L.: Real-time continuous recognition of knee motion using multi-channel mechanomyography signals detected on clothes. J. Electromyogr. Kinesiol. 38, 94\u2013102 (2018)","journal-title":"J. Electromyogr. Kinesiol."},{"key":"2_CR22","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.jelekin.2018.07.005","volume":"42","author":"H Wu","year":"2018","unstructured":"Wu, H., Huang, Q., Wang, D., Gao, L.: A CNN-SVM combined model for pattern recognition of knee motion using mechanomyography signals. J. Electromyogr. Kinesiol. 42, 136\u2013142 (2018)","journal-title":"J. Electromyogr. Kinesiol."},{"issue":"3","key":"2_CR23","doi-asserted-by":"publisher","first-page":"25","DOI":"10.3724\/SP.J.1329.2016.03025","volume":"26","author":"QR Xie","year":"2016","unstructured":"Xie, Q.R., Jiang, Z., Luo, Q.L.: Relationship of root mean square value of electromyography and isometric torque of quadriceps in normal subjects. Rehabil. Med. 26(3), 25\u201328 (2016)","journal-title":"Rehabil. Med."},{"issue":"2","key":"2_CR24","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1016\/j.jneumeth.2010.11.003","volume":"194","author":"W Youn","year":"2011","unstructured":"Youn, W., Kim, J.: Feasibility of using an artificial neural network model to estimate the elbow flexion force from mechanomyography. J. Neurosci. Methods 194(2), 386\u2013393 (2011)","journal-title":"J. Neurosci. Methods"},{"unstructured":"Yu, Y.P.: The research of motion pattern recognition and joint moment analysis of human lower limb based on sEMG. Master\u2019s thesis, Soochow University (2016)","key":"2_CR25"}],"container-title":["Lecture Notes in Computer Science","Intelligent Robotics and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-27532-7_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T18:16:13Z","timestamp":1564683373000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-27532-7_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030275310","9783030275327"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-27532-7_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"2 August 2019","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":"Shenyang","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icira2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icira2019.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}