{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T19:47:06Z","timestamp":1771703226322,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,7]],"date-time":"2018-08-07T00:00:00Z","timestamp":1533600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Measurement system of exoskeleton robots can reflect the state of the patient. In this study, we combined an inertial measurement unit and a visual measurement unit to obtain a repeatable fusion measurement system to compensate for the deficiencies of the single data acquisition mode used by exoskeletons. Inertial measurement unit is comprised four distributed angle sensors. Triaxial acceleration and angular velocity information were transmitted to an upper computer by Bluetooth. The data sent to the control center were processed by a Kalman filter to eliminate any noise. Visual measurement unit uses camera to acquire real time images and related data information. The two data acquisition methods were fused and have its weight. Comparisons of the fusion results with individual measurement results demonstrated that the data fusion method could effectively improve the accuracy of system. It provides a set of accurate real-time measurements for patients in rehabilitation exoskeleton and data support for effective control of exoskeleton robot.<\/jats:p>","DOI":"10.3390\/s18082588","type":"journal-article","created":{"date-parts":[[2018,8,7]],"date-time":"2018-08-07T11:20:23Z","timestamp":1533640823000},"page":"2588","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Physical Extraction and Feature Fusion for Multi-Mode Signals in a Measurement System for Patients in Rehabilitation Exoskeleton"],"prefix":"10.3390","volume":"18","author":[{"given":"Canjun","family":"Yang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianxiao","family":"Wei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhangyi","family":"Ma","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaoling","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hansong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wu","family":"Fan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1109\/TRA.2003.817058","article-title":"Medical robotics in computer-integrated surgery","volume":"19","author":"Taylor","year":"2003","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Han, J., Lian, S., Guo, B., Li, X., and You, A. (2017). Active rehabilitation training system for upper limb based on virtual reality. Adv. Mech. Eng., 12.","DOI":"10.1177\/1687814017743388"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1007\/s12541-017-0081-9","article-title":"Development of real-time gait phase detection system for a lower extremity exoskeleton robot","volume":"18","author":"Lim","year":"2017","journal-title":"Int. J. Precis. Eng. Manuf."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1109\/TIE.2015.2477347","article-title":"Novel Functional Task-Based Gait Assistance Control of Lower Extremity Assistive Device for Level Walking","volume":"63","author":"Li","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1109\/TMECH.2013.2250295","article-title":"Design and Actuator Selection of a Lower Extremity Exoskeleton","volume":"19","author":"Onen","year":"2014","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Mancisidor, A., Zubizarreta, A., Cabanes, I., Portillo, E., and Jung, J.H. (2017). Virtual Sensors for Advanced Controllers in Rehabilitation Robotics. Sensors, 18.","DOI":"10.3390\/s18030785"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1179\/2045772312Y.0000000003","article-title":"Safety and tolerance of the ReWalk\u2122 exoskeleton suit for ambulation by people with complete spinal cord injury: A pilot study","volume":"35","author":"Zeilig","year":"2012","journal-title":"J. Spinal Cord Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1109\/TSMCB.2012.2185843","article-title":"An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot","volume":"42","author":"Kiguchi","year":"2012","journal-title":"IEEE Trans. Syst. Man Cybern. Part B Cybern."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1038\/s41393-017-0013-7","article-title":"Gait training after spinal cord injury: Safety, feasibility and gait function following 8 weeks of training with the exoskeletons from Ekso Bionics","volume":"56","author":"Baunsgaard","year":"2018","journal-title":"Spinal Cord"},{"key":"ref_10","unstructured":"Crowley, J.L. (1995, January 4\u20136). Mathematical foundations of navigation and perception for autonomous mobile robot. Proceedings of the International Workshop on Reasoning with Uncertainty in Robotics, Amsterdam, The Netherlands."},{"key":"ref_11","unstructured":"Park, K., Chung, D., Chung, H., and Lee, J.G. (1996, January 8\u201311). Dead Reckoning Navigation of a Mobile Robot Using an Indirect Kalman Filter. Proceedings of the IEEE International Conference on Multi-Sensor Fusion and Integration for Intelligent Systems, Washington, DC, USA."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A new approach to linear filtering and prediction problems","volume":"82","author":"Kalman","year":"1960","journal-title":"J. Basic Eng."},{"key":"ref_13","unstructured":"Welch, G., and Bishop, G. (2001, January 12\u201317). An introduction to the Kalman filter. Proceedings of the SIGGRAPH, Angeles, CA, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"011002","DOI":"10.1115\/1.4025207","article-title":"A Mobile Motion Capture System Based on Inertial Sensors and Smart Shoes","volume":"136","author":"Jung","year":"2014","journal-title":"J. Dyn. Syst. Meas. Control"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/S0167-9457(01)00050-1","article-title":"Using Skeleton-Based Tracking to Increase the Reliability of Optical Motion Capture","volume":"20","author":"Herda","year":"2001","journal-title":"Hum. Mov. Sci. J."},{"key":"ref_16","first-page":"765","article-title":"Concurrent validation of Xsens MVN measurement of lower limb joint angular kinematics","volume":"34","author":"Zhang","year":"2013","journal-title":"Inst. Phys. Eng. Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.sna.2018.06.023","article-title":"A flexible sensing system capable of sensations imitation and motion monitoring with reliable encapsulation","volume":"279","author":"Li","year":"2018","journal-title":"Sens. Actuators A Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1748","DOI":"10.1177\/0278364914543793","article-title":"Wearable soft sensing suit for human gait measurement","volume":"33","author":"Park","year":"2014","journal-title":"Int. J. Robot. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1109\/MEMB.2010.936554","article-title":"Wearable Sensors and Systems","volume":"29","author":"Bonato","year":"2010","journal-title":"IEEE Eng. Med. Biol. Mag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"111004","DOI":"10.1115\/1.4033949","article-title":"A Wireless Human Motion Monitoring System Based on Joint Angle Sensors and Smart Shoes","volume":"138","author":"Zhang","year":"2016","journal-title":"ASME J. Dyn. Syst. Meas. Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1175\/JHM495.1","article-title":"Data assimilation for estimating the terrestrial water budget using a constrained ensemble Kalman filter","volume":"7","author":"Pan","year":"2006","journal-title":"J. Hydrometeorol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Grosu, V., Grosu, S., Vanderborght, B., Lefeber, D., and Rodriguez-Guerrero, C. (2017). Multi-Axis Force Sensor for Human\u2013Robot Interaction Sensing in a Rehabilitation Robotic Device. Sensors, 17.","DOI":"10.3390\/s17061294"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/978-3-319-08338-4_25","article-title":"A Generalized Extended Kalman Filter Implementation for the Robot Operating System","volume":"302","author":"Moore","year":"2015","journal-title":"Adv. Intell. Syst. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1631\/FITEE.1500286","article-title":"Human hip joint center analysis for biomechanical design of a hip joint exoskeleton","volume":"17","author":"Yang","year":"2016","journal-title":"Front. Inf. Technol. Electron. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/5.554205","article-title":"An introduction to multi-sensor data fusion","volume":"1","author":"Hall","year":"1997","journal-title":"Proc. IEEE"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"7771","DOI":"10.3390\/s91007771","article-title":"Advances in Multi-Sensor Data Fusion: Algorithms and Applications","volume":"9","author":"Dong","year":"2009","journal-title":"Sensors"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/8\/2588\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:17:11Z","timestamp":1760195831000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/8\/2588"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,7]]},"references-count":26,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["s18082588"],"URL":"https:\/\/doi.org\/10.3390\/s18082588","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,7]]}}}