{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:21:54Z","timestamp":1762431714243,"version":"3.40.3"},"publisher-location":"Cham","reference-count":61,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030279493"},{"type":"electronic","value":"9783030279509"}],"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\/978-3-030-27950-9_9","type":"book-chapter","created":{"date-parts":[[2019,8,27]],"date-time":"2019-08-27T01:02:56Z","timestamp":1566867776000},"page":"158-179","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Towards Industrial Assistance Systems: Experiences of Applying Multi-sensor Fusion in Harsh Environments"],"prefix":"10.1007","author":[{"given":"Michael","family":"Haslgr\u00fcbler","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bendikt","family":"Gollan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alois","family":"Ferscha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,14]]},"reference":[{"issue":"4","key":"9_CR1","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1016\/j.aei.2015.03.001","volume":"29","author":"R Akhavian","year":"2015","unstructured":"Akhavian, R., Behzadan, A.H.: Construction equipment activity recognition for simulation input modeling using mobile sensors and machine learning classifiers. Adv. Eng. Inform. 29(4), 867\u2013877 (2015). \n                    https:\/\/doi.org\/10.1016\/j.aei.2015.03.001\n                    \n                  . \n                    http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1474034615000282\n                    \n                  , collective Intelligence Modeling, Analysis, and Synthesis for Innovative Engineering Decision Making Special Issue of the 1st International Conference on Civil and Building Engineering Informatics","journal-title":"Adv. Eng. Inform."},{"key":"9_CR2","doi-asserted-by":"publisher","unstructured":"Al-Naser, M., et al.: Hierarchical model for zero-shot activity recognition using wearable sensors. In: Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, pp. 478\u2013485. INSTICC, SciTePress (2018). \n                    https:\/\/doi.org\/10.5220\/0006595204780485","DOI":"10.5220\/0006595204780485"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Amrouche, S., Gollan, B., Ferscha, A., Heftberger, J.: Activity segmentation and identification based on eye gaze features. In: PErvasive Technologies Related to Assistive Environments (PETRA), Jun 2018. Accepted for publishing in June 2018","DOI":"10.1145\/3197768.3197775"},{"issue":"3","key":"9_CR4","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1007\/s11042-008-0240-1","volume":"41","author":"S Asteriadis","year":"2009","unstructured":"Asteriadis, S., Tzouveli, P., Karpouzis, K., Kollias, S.: Estimation of behavioral user state based on eye gaze and head pose\u2014application in an e-learning environment. Multimed. Tools Appl. 41(3), 469\u2013493 (2009)","journal-title":"Multimed. Tools Appl."},{"key":"9_CR5","doi-asserted-by":"publisher","unstructured":"Avrahami, D., Patel, M., Yamaura, Y., Kratz, S.: Below the surface: unobtrusive activity recognition for work surfaces using RF-radar sensing. In: 23rd International Conference on Intelligent User Interfaces, IUI 2018, pp. 439\u2013451. ACM, New York (2018). \n                    https:\/\/doi.org\/10.1145\/3172944.3172962\n                    \n                  , \n                    http:\/\/doi.acm.org\/10.1145\/3172944.3172962","DOI":"10.1145\/3172944.3172962"},{"issue":"3","key":"9_CR6","first-page":"241","volume":"10","author":"Z Baloch","year":"2018","unstructured":"Baloch, Z., Shaikh, F.K., Unar, M.A.: A context-aware data fusion approach for health-IoT. Int. J. Inf. Technol. 10(3), 241\u2013245 (2018)","journal-title":"Int. J. Inf. Technol."},{"key":"9_CR7","unstructured":"Behrmann, E., Rauwald, C.: Mercedes boots robots from the production line (2016). Accessed Feb 01 2017"},{"issue":"6","key":"9_CR8","doi-asserted-by":"publisher","first-page":"0127769","DOI":"10.1371\/journal.pone.0127769","volume":"10","author":"G Bleser","year":"2015","unstructured":"Bleser, G., et al.: Cognitive learning, monitoring and assistance of industrial workflows using egocentric sensor networks. PLoS ONE 10(6), 0127769 (2015)","journal-title":"PLoS ONE"},{"issue":"9","key":"9_CR9","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1109\/JSEN.2010.2045498","volume":"10","author":"A Burns","year":"2010","unstructured":"Burns, A., et al.: Shimmer\u2122\u2013a wireless sensor platform for noninvasive biomedical research. IEEE Sens. J. 10(9), 1527\u20131534 (2010)","journal-title":"IEEE Sens. J."},{"issue":"2","key":"9_CR10","doi-asserted-by":"publisher","first-page":"373","DOI":"10.3758\/BRM.40.2.373","volume":"40","author":"M Camilli","year":"2008","unstructured":"Camilli, M., Nacchia, R., Terenzi, M., Di Nocera, F.: ASTEF: a simple tool for examining fixations. Behav. Res. Methods 40(2), 373\u2013382 (2008)","journal-title":"Behav. Res. Methods"},{"key":"9_CR11","unstructured":"Campbell, T., Harper, J., Hartmann, B., Paulos, E.: Towards digital apprenticeship: wearable activity recognition in the workshop setting. Technical report, University of California, Berkeley (2015)"},{"issue":"1","key":"9_CR12","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/MCOM.2017.1600410CM","volume":"55","author":"M Chen","year":"2017","unstructured":"Chen, M., Ma, Y., Li, Y., Wu, D., Zhang, Y., Youn, C.H.: Wearable 2.0: enabling human-cloud integration in next generation healthcare systems. IEEE Commun. Mag. 55(1), 54\u201361 (2017)","journal-title":"IEEE Commun. Mag."},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Cheng, C.F., Rashidi, A., Davenport, M.A., Anderson, D.: Audio signal processing for activity recognition of construction heavy equipment. In: ISARC Proceedings of the International Symposium on Automation and Robotics in Construction, vol. 33, p. 1 (2016)","DOI":"10.22260\/ISARC2016\/0078"},{"issue":"8","key":"9_CR14","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.1523\/JNEUROSCI.20-08-03033.2000","volume":"20","author":"HD Critchley","year":"2000","unstructured":"Critchley, H.D., Elliott, R., Mathias, C.J., Dolan, R.J.: Neural activity relating to generation and representation of galvanic skin conductance responses: a functional magnetic resonance imaging study. J. Neurosci. 20(8), 3033\u20133040 (2000)","journal-title":"J. Neurosci."},{"issue":"2","key":"9_CR15","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1016\/j.physbeh.2012.01.020","volume":"106","author":"Marieke van Dooren","year":"2012","unstructured":"van Dooren, M., de Vries, J.J.G.G.J., Janssen, J.H.: Emotional sweating across the body: comparing 16 different skin conductance measurement locations. Physiol. Behav. 106(2), 298\u2013304 (2012). \n                    https:\/\/doi.org\/10.1016\/j.physbeh.2012.01.020","journal-title":"Physiology & Behavior"},{"key":"9_CR16","unstructured":"Empatica: comparison procomp vs empatica E3 skin conductance signal (2016). \n                    https:\/\/empatica.app.box.com\/s\/a53t8mnose4l3331529r1ma3fbzmxtcb"},{"key":"9_CR17","unstructured":"Fedor, S., Picard, R.W.: Ambulatory EDA: comparisons of bilateral forearm and calf locations, September 2014"},{"issue":"1","key":"9_CR18","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/0301-0511(83)90064-9","volume":"17","author":"CD Frith","year":"1983","unstructured":"Frith, C.D., Allen, H.A.: The skin conductance orienting response as an index of attention. Biol. Psychol. 17(1), 27\u201339 (1983)","journal-title":"Biol. Psychol."},{"issue":"1","key":"9_CR19","doi-asserted-by":"publisher","first-page":"123","DOI":"10.3758\/s13414-010-0015-4","volume":"73","author":"S Gabay","year":"2011","unstructured":"Gabay, S., Pertzov, Y., Henik, A.: Orienting of attention, pupil size, and the norepinephrine system. Atten. Percept. Psychophys. 73(1), 123\u2013129 (2011)","journal-title":"Atten. Percept. Psychophys."},{"issue":"5\u20138","key":"9_CR20","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1007\/s00170-015-8032-z","volume":"85","author":"X Gao","year":"2016","unstructured":"Gao, X., Sun, Y., You, D., Xiao, Z., Chen, X.: Multi-sensor information fusion for monitoring disk laser welding. Int. J. Adv. Manuf. Technol. 85(5\u20138), 1167\u20131175 (2016)","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"9_CR21","unstructured":"Gollan, B., Ferscha, A.: Modeling pupil dilation as online input for estimation of cognitive load in non-laboratory attention-aware systems. In: COGNITIVE 2016-The Eighth International Conference on Advanced Cognitive Technologies and Applications (2016)"},{"key":"9_CR22","doi-asserted-by":"publisher","unstructured":"Gollan, B., Haslgr\u00fcbler, M., Ferscha, A., Heftberger, J.: Making sense: Experiences with multi-sensor fusion in industrial assistance systems. In: Proceedings of the 5th International Conference on Physiological Computing Systems, PhyCS 2018, Seville, Spain, 19\u201321 September 2018, pp. 64\u201374 (2018). \n                    https:\/\/doi.org\/10.5220\/0007227600640074","DOI":"10.5220\/0007227600640074"},{"key":"9_CR23","doi-asserted-by":"crossref","unstructured":"Gradl, S., Kugler, P., Lohm\u00fcller, C., Eskofier, B.: Real-time ECG monitoring and arrhythmia detection using android-based mobile devices. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2452\u20132455. IEEE (2012)","DOI":"10.1109\/EMBC.2012.6346460"},{"key":"9_CR24","first-page":"3","volume":"8","author":"FK Graham","year":"1992","unstructured":"Graham, F.K.: Attention: the heartbeat, the blink, and the brain. Int. J. Adv. Manuf. Technol. 8, 3\u201329 (1992)","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"9_CR25","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.inffus.2016.09.005","volume":"35","author":"R Gravina","year":"2017","unstructured":"Gravina, R., Alinia, P., Ghasemzadeh, H., Fortino, G.: Multi-sensor fusion in body sensor networks: state-of-the-art and research challenges. Inf. Fusion 35, 68\u201380 (2017)","journal-title":"Inf. Fusion"},{"key":"9_CR26","series-title":"Cognitive Systems Monographs","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/978-3-642-10403-9_15","volume-title":"Human Centered Robot Systems","author":"M Hahn","year":"2009","unstructured":"Hahn, M., Kr\u00fcger, L., W\u00f6hler, C., Kummert, F.: 3D action recognition in an industrial environment: cognition, interaction, technology. In: Ritter, H., Sagerer, G., Dillmann, R., Buss, M. (eds.) Human Centered Robot Systems. Cognitive Systems Monographs, vol. 6, pp. 141\u2013150. Springer, Heidelberg (2009). \n                    https:\/\/doi.org\/10.1007\/978-3-642-10403-9_15"},{"key":"9_CR27","doi-asserted-by":"crossref","unstructured":"Haslgr\u00fcbler, M., Fritz, P., Gollan, B., Ferscha, A.: Getting through: modality selection in a multi-sensor-actuator industrial IoT environment. In: Proceedings of the Seventh International Conference on the Internet of Things. ACM (2017)","DOI":"10.1145\/3131542.3131561"},{"issue":"1","key":"9_CR28","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1108\/SR-06-2016-0107","volume":"37","author":"S Jovic","year":"2017","unstructured":"Jovic, S., Anicic, O., Jovanovic, M.: Adaptive neuro-fuzzy fusion of multi-sensor data for monitoring of CNC machining. Sens. Rev. 37(1), 78\u201381 (2017)","journal-title":"Sens. Rev."},{"key":"9_CR29","volume-title":"Attention and Effort","author":"D Kahneman","year":"1973","unstructured":"Kahneman, D.: Attention and Effort, vol. 1063. Prentice-Hall Enlegwood Cliffs, Upper Saddle River (1973)"},{"key":"9_CR30","doi-asserted-by":"crossref","unstructured":"Kassner, M., Patera, W., Bulling, A.: Pupil: an open source platform for pervasive eye tracking and mobile gaze-based interaction. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, pp. 1151\u20131160. ACM (2014)","DOI":"10.1145\/2638728.2641695"},{"key":"9_CR31","doi-asserted-by":"publisher","unstructured":"Koskimaki, H., Huikari, V., Siirtola, P., Laurinen, P., Roning, J.: Activity recognition using a wrist-worn inertial measurement unit: a case study for industrial assembly lines. In: 2009 17th Mediterranean Conference on Control and Automation, pp. 401\u2013405, June 2009. \n                    https:\/\/doi.org\/10.1109\/MED.2009.5164574","DOI":"10.1109\/MED.2009.5164574"},{"key":"9_CR32","doi-asserted-by":"crossref","unstructured":"Kramer, A.F.: Physiological metrics of mental workload: a review of recent progress. In: Multiple-Task Performance, pp. 279\u2013328 (1991)","DOI":"10.21236\/ADA223701"},{"key":"9_CR33","unstructured":"Kr\u00f6ger, M., Sauer-Greff, W., Urbansky, R., Lorang, M., Siegrist, M.: Performance evaluation on contour extraction using hough transform and RANSAC for multi-sensor data fusion applications in industrial food inspection. In: Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2016, pp. 234\u2013237. IEEE (2016)"},{"key":"9_CR34","unstructured":"Lacey, J.I.: Somatic response patterning and stress: some revisions of activation theory. In: Appley, M.H., Trumbull, R. (eds.) Psychological Stress: Some Issues in Research, Appleton-Century-Crofts, New York (1967)"},{"key":"9_CR35","doi-asserted-by":"publisher","unstructured":"Lenz, C., et al.: Human workflow analysis using 3D occupancy grid hand tracking in a human-robot collaboration scenario. In: 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 3375\u20133380, September 2011. \n                    https:\/\/doi.org\/10.1109\/IROS.2011.6094570","DOI":"10.1109\/IROS.2011.6094570"},{"key":"9_CR36","doi-asserted-by":"crossref","unstructured":"Leykin, A., Hammoud, R.: Real-time estimation of human attention field in LWIR and color surveillance videos. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2008, pp. 1\u20136. IEEE (2008)","DOI":"10.1109\/CVPRW.2008.4563059"},{"issue":"1","key":"9_CR37","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/s11276-015-1133-7","volume":"23","author":"X Li","year":"2017","unstructured":"Li, X., Li, D., Wan, J., Vasilakos, A.V., Lai, C.F., Wang, S.: A review of industrial wireless networks in the context of industry 4.0. Wirel. Netw. 23(1), 23\u201341 (2017)","journal-title":"Wirel. Netw."},{"key":"9_CR38","doi-asserted-by":"publisher","unstructured":"Maekawa, T., Nakai, D., Ohara, K., Namioka, Y.: Toward practical factory activity recognition: unsupervised understanding of repetitive assembly work in a factory. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, pp. 1088\u20131099. ACM, New York (2016). \n                    https:\/\/doi.org\/10.1145\/2971648.2971721\n                    \n                  , \n                    http:\/\/doi.acm.org\/10.1145\/2971648.2971721","DOI":"10.1145\/2971648.2971721"},{"issue":"3","key":"9_CR39","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/0167-9457(90)90005-X","volume":"9","author":"RA Magill","year":"1990","unstructured":"Magill, R.A., Hall, K.G.: A review of the contextual interference effect in motor skill acquisition. Hum. Mov. Sci. 9(3), 241\u2013289 (1990)","journal-title":"Hum. Mov. Sci."},{"key":"9_CR40","doi-asserted-by":"publisher","unstructured":"Makantasis, K., Doulamis, A., Doulamis, N., Psychas, K.: Deep learning based human behavior recognition in industrial workflows. In: 2016 IEEE International Conference on Image Processing (ICIP), pp. 1609\u20131613, September 2016. \n                    https:\/\/doi.org\/10.1109\/ICIP.2016.7532630","DOI":"10.1109\/ICIP.2016.7532630"},{"key":"9_CR41","unstructured":"Malais\u00e9, A., Maurice, P., Colas, F., Charpillet, F.c., Ivaldi, S.: Activity recognition with multiple wearable sensors for industrial applications. In: ACHI 2018 - Eleventh International Conference on Advances in Computer-Human Interactions, Rome, Italy, March 2018. \n                    https:\/\/hal.archives-ouvertes.fr\/hal-01701996"},{"key":"9_CR42","doi-asserted-by":"publisher","first-page":"16","DOI":"10.17705\/1CAIS.04016","volume":"40","author":"M Marabelli","year":"2017","unstructured":"Marabelli, M., Hansen, S., Newell, S., Frigerio, C.: The light and dark side of the black box: sensor-based technology in the automotive industry. CAIS 40, 16 (2017)","journal-title":"CAIS"},{"key":"9_CR43","unstructured":"Maurtua, I., Kirisci, P.T., Stiefmeier, T., Sbodio, M.L., Witt, H.: A wearable computing prototype for supporting training activities in automotive production. In: 4th International Forum on Applied Wearable Computing 2007, pp. 1\u201312, March 2007"},{"key":"9_CR44","unstructured":"Otto, M.M., Agethen, P., Geiselhart, F., Rietzler, M., Gaisbauer, F., Rukzio, E.: Presenting a holistic framework for scalable, marker-less motion capturing: skeletal tracking performance analysis, sensor fusion algorithms and usage in automotive industry. J. Virtual R. Broadcast. 13(3) (2016)"},{"issue":"5","key":"9_CR45","doi-asserted-by":"publisher","first-page":"e93","DOI":"10.1111\/j.1528-1167.2012.03444.x","volume":"53","author":"MZ Poh","year":"2012","unstructured":"Poh, M.Z., et al.: Convulsive seizure detection using a wrist-worn electrodermal activity and accelerometry biosensor. Epilepsia 53(5), e93\u2013e97 (2012). \n                    https:\/\/doi.org\/10.1111\/j.1528-1167.2012.03444.x","journal-title":"Epilepsia"},{"key":"9_CR46","doi-asserted-by":"crossref","unstructured":"Potter, L.E., Araullo, J., Carter, L.: The leap motion controller: a view on sign language. In: Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, pp. 175\u2013178. ACM (2013)","DOI":"10.1145\/2541016.2541072"},{"key":"9_CR47","doi-asserted-by":"publisher","unstructured":"Reining, C., Schlangen, M., Hissmann, L., ten Hompel, M., Moya, F., Fink, G.A.: Attribute representation for human activity recognition of manual order picking activities. In: Proceedings of the 5th International Workshop on Sensor-Based Activity Recognition and Interaction, iWOAR 2018, pp. 10\u20131. ACM, New York (2018). \n                    https:\/\/doi.org\/10.1145\/3266157.3266214\n                    \n                  , \n                    http:\/\/doi.acm.org\/10.1145\/3266157.3266214","DOI":"10.1145\/3266157.3266214"},{"issue":"3","key":"9_CR48","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1016\/j.ifacol.2015.06.159","volume":"48","author":"DJ Rude","year":"2015","unstructured":"Rude, D.J., Adams, S., Beling, P.A.: A benchmark dataset for depth sensor based activity recognition in a manufacturing process. IFAC-PapersOnLine 48(3), 668\u2013674 (2015). \n                    https:\/\/doi.org\/10.1016\/j.ifacol.2015.06.159\n                    \n                  . \n                    http:\/\/www.sciencedirect.com\/science\/article\/pii\/S2405896315003985\n                    \n                  , 15th IFAC Symposium onInformation Control Problems inManufacturing","journal-title":"IFAC-PapersOnLine"},{"issue":"2","key":"9_CR49","doi-asserted-by":"publisher","first-page":"3","DOI":"10.3390\/jpm7020003","volume":"7","author":"A Shcherbina","year":"2017","unstructured":"Shcherbina, A.: Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. J. Pers. Med. 7(2), 3 (2017)","journal-title":"J. Pers. Med."},{"key":"9_CR50","doi-asserted-by":"crossref","unstructured":"Smith, K.C., Ba, S.O., Odobez, J.M., Gatica-Perez, D.: Tracking attention for multiple people: wandering visual focus of attention estimation. Tech. rep., IDIAP (2006)","DOI":"10.1145\/1180995.1181048"},{"key":"9_CR51","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1016\/j.jclepro.2014.04.036","volume":"88","author":"M Srbinovska","year":"2015","unstructured":"Srbinovska, M., Gavrovski, C., Dimcev, V., Krkoleva, A., Borozan, V.: Environmental parameters monitoring in precision agriculture using wireless sensor networks. J. Clean. Prod. 88, 297\u2013307 (2015)","journal-title":"J. Clean. Prod."},{"key":"9_CR52","doi-asserted-by":"publisher","unstructured":"Stiefmeier, T., Ogris, G., Junker, H., Lukowicz, P., Troster, G.: Combining motion sensors and ultrasonic hands tracking for continuous activity recognition in a maintenance scenario. In: 2006 10th IEEE International Symposium on Wearable Computers, pp. 97\u2013104, October 2006. \n                    https:\/\/doi.org\/10.1109\/ISWC.2006.286350","DOI":"10.1109\/ISWC.2006.286350"},{"issue":"2","key":"9_CR53","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1109\/MPRV.2008.40","volume":"7","author":"Thomas Stiefmeier","year":"2008","unstructured":"Stiefmeier, T., Roggen, D., Ogris, G., Lukowicz, P., Tr\u00f6ster, G.: Wearable activity tracking in car manufacturing. IEEE Pervasive Comput. 7(2) (2008). \n                    https:\/\/doi.org\/10.1109\/MPRV.2008.40","journal-title":"IEEE Pervasive Computing"},{"key":"9_CR54","doi-asserted-by":"crossref","unstructured":"Suriya-Prakash, M., John-Preetham, G., Sharma, R.: Is heart rate variability related to cognitive performance in visuospatial working memory? PeerJ PrePrints (2015)","DOI":"10.7287\/peerj.preprints.1377"},{"key":"9_CR55","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1016\/j.promfg.2018.07.152","volume":"26","author":"W Tao","year":"2018","unstructured":"Tao, W., Lai, Z.H., Leu, M.C., Yin, Z.: Worker activity recognition in smart manufacturing using IMU and semg signals with convolutional neural networks. Procedia Manuf. 26, 1159\u20131166 (2018). \n                    https:\/\/doi.org\/10.1016\/j.promfg.2018.07.152\n                    \n                  . \n                    http:\/\/www.sciencedirect.com\/science\/article\/pii\/S235197891830828X\n                    \n                  , 46th SME North American Manufacturing Research Conference, NAMRC 46, Texas, USA","journal-title":"Procedia Manuf."},{"key":"9_CR56","unstructured":"Thatcher, R.W., John, E.R.: Functional neuroscience: I. Foundations of cognitive processes. Lawrence Erlbaum (1977)"},{"key":"9_CR57","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1007\/978-3-642-19315-6_16","volume-title":"Computer Vision \u2013 ACCV 2010","author":"G Veres","year":"2011","unstructured":"Veres, G., Grabner, H., Middleton, L., Van Gool, L.: Automatic workflow monitoring in industrial environments. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010. LNCS, vol. 6492, pp. 200\u2013213. Springer, Heidelberg (2011). \n                    https:\/\/doi.org\/10.1007\/978-3-642-19315-6_16"},{"key":"9_CR58","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/978-3-642-15819-3_71","volume-title":"Artificial Neural Networks \u2013 ICANN 2010","author":"A Voulodimos","year":"2010","unstructured":"Voulodimos, A., Grabner, H., Kosmopoulos, D., Van Gool, L., Varvarigou, T.: Robust workflow recognition using holistic features and outlier-tolerant fused hidden markov models. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds.) ICANN 2010. LNCS, vol. 6352, pp. 551\u2013560. Springer, Heidelberg (2010). \n                    https:\/\/doi.org\/10.1007\/978-3-642-15819-3_71"},{"issue":"5","key":"9_CR59","doi-asserted-by":"publisher","first-page":"6380","DOI":"10.3390\/s130506380","volume":"13","author":"F Weichert","year":"2013","unstructured":"Weichert, F., Bachmann, D., Rudak, B., Fisseler, D.: Analysis of the accuracy and robustness of the leap motion controller. Sensors 13(5), 6380\u20136393 (2013)","journal-title":"Sensors"},{"issue":"3","key":"9_CR60","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.aei.2016.04.009","volume":"30","author":"J Yang","year":"2016","unstructured":"Yang, J., Shi, Z., Wu, Z.: Vision-based action recognition of construction workers using dense trajectories. Adv. Eng. Inform. 30(3), 327\u2013336 (2016). \n                    https:\/\/doi.org\/10.1016\/j.aei.2016.04.009\n                    \n                  . \n                    http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1474034616300842","journal-title":"Adv. Eng. Inform."},{"key":"9_CR61","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/978-3-540-77690-1_2","volume-title":"Wireless Sensor Networks","author":"P Zappi","year":"2008","unstructured":"Zappi, P., et al.: Activity recognition from on-body sensors: accuracy-power trade-off by dynamic sensor selection. In: Verdone, R. (ed.) EWSN 2008. LNCS, vol. 4913, pp. 17\u201333. Springer, Heidelberg (2008). \n                    https:\/\/doi.org\/10.1007\/978-3-540-77690-1_2"}],"container-title":["Lecture Notes in Computer Science","Physiological Computing Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-27950-9_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,27]],"date-time":"2019-08-27T13:03:02Z","timestamp":1566910982000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-27950-9_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030279493","9783030279509"],"references-count":61,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-27950-9_9","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":"14 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PhyCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Physiological Computing Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Seville","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"phycs2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.phycs.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}