{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:57:10Z","timestamp":1743105430543,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030390976"},{"type":"electronic","value":"9783030390983"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-39098-3_15","type":"book-chapter","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T06:05:28Z","timestamp":1579673128000},"page":"199-212","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Quantifying Quality of Actions Using Wearable Sensor"],"prefix":"10.1007","author":[{"given":"Mohammad","family":"Al-Naser","sequence":"first","affiliation":[]},{"given":"Takehiro","family":"Niikura","sequence":"additional","affiliation":[]},{"given":"Sheraz","family":"Ahmed","sequence":"additional","affiliation":[]},{"given":"Hiroki","family":"Ohashi","sequence":"additional","affiliation":[]},{"given":"Takuto","family":"Sato","sequence":"additional","affiliation":[]},{"given":"Mitsuhiro","family":"Okada","sequence":"additional","affiliation":[]},{"given":"Katsuyuki","family":"Nakamura","sequence":"additional","affiliation":[]},{"given":"Andreas","family":"Dengel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,1,23]]},"reference":[{"key":"15_CR1","unstructured":"AXIS Neuron. https:\/\/neuronmocap.com\/content\/axis-neuron-software"},{"key":"15_CR2","unstructured":"Perception Neuron. https:\/\/www.noitom.com\/solutions\/perception-neuron"},{"key":"15_CR3","doi-asserted-by":"publisher","unstructured":"Anand, A., Sharma, M., Srivastava, R., Kaligounder, L., Prakash, D.: Wearable motion sensor based analysis of swing sports. In: 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 261\u2013267, December 2017. https:\/\/doi.org\/10.1109\/ICMLA.2017.0-149","DOI":"10.1109\/ICMLA.2017.0-149"},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Ba\u010di\u0107, B.: Towards the next generation of exergames: flexible and personalised assessment-based identification of tennis swings (2018)","DOI":"10.1109\/IJCNN.2018.8489602"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Borghesi, A., Bartolini, A., Lombardi, M., Milano, M., Benini, L.: Anomaly detection using autoencoders in high performance computing systems. CoRR abs\/1811.05269 (2018)","DOI":"10.1016\/j.suscom.2018.05.007"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Carreira, J., Zisserman, A.: Quo Vadis, action recognition? A new model and the kinetics dataset. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4724\u20134733 (2017)","DOI":"10.1109\/CVPR.2017.502"},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Doughty, H., Damen, D., Mayol-Cuevas, W.W.: Who\u2019s better? Who\u2019s best? Pairwise deep ranking for skill determination. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6057\u20136066 (2018)","DOI":"10.1109\/CVPR.2018.00634"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Doughty, H., Mayol-Cuevas, W.W., Damen, D.: The pros and cons: rank-aware temporal attention for skill determination in long videos. CoRR abs\/1812.05538 (2018)","DOI":"10.1109\/CVPR.2019.00805"},{"issue":"5","key":"15_CR9","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1109\/THMS.2014.2377111","volume":"45","author":"S Gaglio","year":"2015","unstructured":"Gaglio, S., Re, G.L., Morana, M.: Human activity recognition process using 3-D posture data. IEEE Trans. Hum.-Mach. Syst. 45(5), 586\u2013597 (2015)","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"15_CR10","unstructured":"Jordao, A., Nazare Jr., A.C., de Souza, J.S., Schwartz, W.R.: Human activity recognition based on wearable sensor data: a standardization of the state-of-the-art. CoRR abs\/1806.05226 (2018). http:\/\/arxiv.org\/abs\/1806.05226"},{"key":"15_CR11","doi-asserted-by":"publisher","first-page":"36","DOI":"10.3390\/jimaging4020036","volume":"4","author":"BR Kiran","year":"2018","unstructured":"Kiran, B.R., Thomas, D.M., Parakkal, R.: An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos. J. Imaging 4, 36 (2018)","journal-title":"J. Imaging"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Ladha, C., Hammerla, N.Y., Olivier, P., Pl\u00f6tz, T.: ClimbAX: skill assessment for climbing enthusiasts. In: UbiComp (2013)","DOI":"10.1145\/2493432.2493492"},{"issue":"6","key":"15_CR13","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1109\/THMS.2017.2700630","volume":"47","author":"M Li","year":"2017","unstructured":"Li, M., Wei, J., Zheng, X., Bolton, M.L.: A formal machine-learning approach to generating human-machine interfaces from task models. IEEE Trans. Hum.-Mach. Syst. 47(6), 822\u2013833 (2017). https:\/\/doi.org\/10.1109\/THMS.2017.2700630","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"issue":"6","key":"15_CR14","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1109\/THMS.2017.2693242","volume":"47","author":"S Lv","year":"2017","unstructured":"Lv, S., Lu, Y., Dong, M., Wang, X., Dou, Y., Zhuang, W.: Qualitative action recognition by wireless radio signals in human-machine systems. IEEE Trans. Hum.-Mach. Syst. 47(6), 789\u2013800 (2017). https:\/\/doi.org\/10.1109\/THMS.2017.2693242","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"15_CR15","doi-asserted-by":"publisher","unstructured":"M\u00fcller, A., et al.: GymSkill: a personal trainer for physical exercises. In: 2012 IEEE International Conference on Pervasive Computing and Communications, pp. 213\u2013220, March 2012. https:\/\/doi.org\/10.1109\/PerCom.2012.6199869","DOI":"10.1109\/PerCom.2012.6199869"},{"issue":"8","key":"15_CR16","doi-asserted-by":"publisher","first-page":"2485","DOI":"10.3390\/s18082485","volume":"18","author":"Hiroki Ohashi","year":"2018","unstructured":"Ohashi, H., Al-Naser, M., Ahmed, S., Nakamura, K., Sato, T., Dengel, A.: Attributes\u2019 importance for zero-shot pose-classification based on wearable sensors. Sensors 18(8) (2018). Article no. 2485. https:\/\/doi.org\/10.3390\/s18082485","journal-title":"Sensors"},{"key":"15_CR17","doi-asserted-by":"crossref","unstructured":"Parisi, G.I., Magg, S., Wermter, S.: Human motion assessment in real time using recurrent self-organization. In: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 71\u201376 (2016)","DOI":"10.1109\/ROMAN.2016.7745093"},{"key":"15_CR18","doi-asserted-by":"publisher","unstructured":"Parmar, P., Morris, B.T.: Learning to score Olympic events (2017). https:\/\/doi.org\/10.1109\/CVPRW.2017.16","DOI":"10.1109\/CVPRW.2017.16"},{"key":"15_CR19","unstructured":"Parmar, P., Morris, B.T.: Learning to score Olympic events. CoRR abs\/1611.05125 (2016). http:\/\/arxiv.org\/abs\/1611.05125"},{"key":"15_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1007\/978-3-319-10599-4_36","volume-title":"Computer Vision \u2013 ECCV 2014","author":"H Pirsiavash","year":"2014","unstructured":"Pirsiavash, H., Vondrick, C., Torralba, A.: Assessing the quality of actions. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 556\u2013571. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10599-4_36"},{"key":"15_CR21","doi-asserted-by":"publisher","unstructured":"Velloso, E., Bulling, A., Gellersen, H.: MotionMA: motion modelling and analysis by demonstration. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI 2013, pp. 1309\u20131318. ACM, New York (2013). https:\/\/doi.org\/10.1145\/2470654.2466171","DOI":"10.1145\/2470654.2466171"},{"key":"15_CR22","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.patrec.2018.02.010","volume":"119","author":"J Wang","year":"2018","unstructured":"Wang, J., Chen, Y., Hao, S., Peng, X., Hu, L.: Deep learning for sensor-based activity recognition: a survey. Pattern Recogn. Lett. 119, 3\u201311 (2018)","journal-title":"Pattern Recogn. Lett."},{"key":"15_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1007\/978-3-642-22822-3_27","volume-title":"Computer Vision \u2013 ACCV 2010 Workshops","author":"K Wnuk","year":"2011","unstructured":"Wnuk, K., Soatto, S.: Analyzing diving: a dataset for judging action quality. In: Koch, R., Huang, F. (eds.) ACCV 2010. LNCS, vol. 6468, pp. 266\u2013276. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-22822-3_27"},{"key":"15_CR24","doi-asserted-by":"publisher","unstructured":"Zhang, W., Qin, L., Zhong, W., Guo, X., Wang, G.: Framework of sequence chunking for human activity recognition using wearables. In: Proceedings of the 2019 International Conference on Image, Video and Signal Processing. IVSP 2019, pp. 93\u201398. ACM, New York (2019). https:\/\/doi.org\/10.1145\/3317640.3317647","DOI":"10.1145\/3317640.3317647"},{"key":"15_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1007\/978-3-319-24553-9_53","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"A Zia","year":"2015","unstructured":"Zia, A., Sharma, Y., Bettadapura, V., Sarin, E.L., Clements, M.A., Essa, I.: Automated assessment of surgical skills using frequency analysis. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9349, pp. 430\u2013438. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24553-9_53"}],"container-title":["Lecture Notes in Computer Science","Advanced Analytics and Learning on Temporal Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-39098-3_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T23:04:02Z","timestamp":1737500642000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-39098-3_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030390976","9783030390983"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-39098-3_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"23 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AALTD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Advanced Analysis and Learning on Temporal Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"W\u00fcrzburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","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":"20 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aaltd2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/project.inria.fr\/aaltd19\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2-3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}