{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T22:27:43Z","timestamp":1767652063259,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T00:00:00Z","timestamp":1568332800000},"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>In this study, we developed a single leg knee joint assistance robot. Commonly used exoskeletons have a left-right pair, but when only one leg of the wearer is uncomfortable, it is effective to wear the exoskeleton on only the uncomfortable leg. The designed exoskeleton uses a lightweight material and uses a wire-driven actuator, which reduces the weight of the driving section that is attached on the knee directly. Therefore, proposed exoskeleton reduces the force of inertia that the wearer experiences. In addition, the lower frame length of the exoskeleton can be changed to align with the complex movement of the knee. Furthermore, the length between the knee center of rotation and the ankle (LBKA) is measured by using this structure, and the LBKA values are used as the data for intention detection. These value helps to detect the intention because it changes faster than a motor encoder value. A neural network was trained using the motor encoder values, and LBKA values. Neural network detects the intention of three motions (stair ascending, stair descending, and walking), Training results showed that intention detection was good in various environments.<\/jats:p>","DOI":"10.3390\/s19183960","type":"journal-article","created":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T10:32:41Z","timestamp":1568370761000},"page":"3960","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Development of a Single Leg Knee Exoskeleton and Sensing Knee Center of Rotation Change for Intention Detection"],"prefix":"10.3390","volume":"19","author":[{"given":"Dae-Hoon","family":"Moon","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Ajou University, Suwon 16499, Korea"}]},{"given":"Donghan","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Kyung Hee University, Yongin 17104, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6174-6442","authenticated-orcid":false,"given":"Young-Dae","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Ajou University, Suwon 16499, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1046\/j.1525-1403.2003.03017.x","article-title":"Robotic orthosis lokomat: A rehabilitation and research tool","volume":"6","author":"Jezernik","year":"2003","journal-title":"Neuromodulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"15025","DOI":"10.1038\/scsandc.2015.25","article-title":"Effects of training with the ReWalk exoskeleton on quality of life in incomplete spinal cord injury: A single case study","volume":"2","author":"Raab","year":"2016","journal-title":"Spinal Cord Ser. Cases"},{"key":"ref_3","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":"Frotzler","year":"2018","journal-title":"Spinal Cord"},{"unstructured":"Kawamoto, H., Lee, S., Kanbe, S., and Sankai, Y. (2003, January 5\u20138). Power assist method for HAL-3 using EMG-based feedback controller. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Washington, DC, USA.","key":"ref_4"},{"doi-asserted-by":"crossref","unstructured":"Walsh, C.J., Pasch, K., and Herr, H. (2006, January 9\u201315). An autonomous, underactuated exoskeleton for load-carrying augmentation. Proceedings of the 2006 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Beijing, China.","key":"ref_5","DOI":"10.1109\/IROS.2006.281932"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1016\/S0003-9993(03)00281-8","article-title":"Development of the concepts of knee kinematics","volume":"84","author":"Smith","year":"2003","journal-title":"Arch. Phys Med. Rehabil."},{"doi-asserted-by":"crossref","unstructured":"Celebi, B., Yalcin, M., and Patoglu, V. (2013, January 3\u20137). ASSISTON-KNEE: A self-aligning knee exoskeleton. Proceedings of the 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan.","key":"ref_7","DOI":"10.1109\/IROS.2013.6696472"},{"unstructured":"Kim, K.J., Kang, M.S., Choi, Y.S., Han, J., and Han, C. (July, January 29). Conceptualization of an exoskeleton continuous passive motion (cpm) device using a link structure. Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland.","key":"ref_8"},{"doi-asserted-by":"crossref","unstructured":"Ergin, M.A., and Patoglu, V. (July, January 29). A self-adjusting knee exoskeleton for robotassisted treatment of knee injuries. Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland.","key":"ref_9","DOI":"10.1109\/IROS.2011.6048834"},{"key":"ref_10","first-page":"050802","article-title":"Misalignment compensation for full human-exoskeleton kinematic compatibility: State of the art and evaluation","volume":"70","author":"Junius","year":"2019","journal-title":"Appl. Mech. Rev."},{"doi-asserted-by":"crossref","unstructured":"Bartenbach, V., Wyss, D., Seuret, D., and Riener, R. (2015, January 11\u201314). A lower limb exoskeleton research platform to investigate human-robot interaction. Proceedings of the 2015 IEEE International Conference on Rehabilitation Robotics, Singapore.","key":"ref_11","DOI":"10.1109\/ICORR.2015.7281266"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1268","DOI":"10.1109\/TMECH.2013.2278207","article-title":"Adaptive knee joint exoskeleton based on biological geometries","volume":"19","author":"Wang","year":"2014","journal-title":"IEEE\/ASME Trans. Mechatron."},{"doi-asserted-by":"crossref","unstructured":"Yap, H.K., Lim, J.H., Nasrallah, F., Goh, J., and Yeow, R. (2015, January 26\u201330). A soft exoskeleton for hand assistive and rehabilitation application using pneumatic actuators with variable stiffness. Proceedings of the 2015 IEEE International Conference on Robotics and Automation, Seattle, WA, USA.","key":"ref_13","DOI":"10.1109\/ICRA.2015.7139889"},{"unstructured":"Kwamoto, H., Noorden, J., Missel, M., Craig, T., Pratt, J., and Neuhaus, P. (2009, January 12\u201317). Development of the IHMC mobility assist exoskeleton. Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan.","key":"ref_14"},{"unstructured":"Xin, J., Xiang, C., and Agrawal, S.K. (2015, January 26\u201330). Design of a cable-driven active leg exoskeleton (C-ALEX) and gait training experiments with human subjects. Proceedings of the 2015 IEEE International Conference on Robotics and Automation, Seattle, WA, USA.","key":"ref_15"},{"doi-asserted-by":"crossref","unstructured":"Kawamoto, H., Hayashi, T., Sakurai, T., Eguchi, K., and Sankai, Y. (2009, January 3\u20136). Development of single leg version of HAL for hemiplegia. Proceedings of the 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, USA.","key":"ref_16","DOI":"10.1109\/IEMBS.2009.5333698"},{"unstructured":"Kawamoto, H., and Sankai, A. (2002, January 6\u20139). Comfortable power assist control method for walking aid by HAL-3. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Yasmine Hammamet, Tunisia.","key":"ref_17"},{"doi-asserted-by":"crossref","unstructured":"Jang, J., Kim, K., Lee, J., Lim, B., and Shim, Y. (Octomber, January 28). Online gait task recognition algorithm for hip exoskeleton. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany.","key":"ref_18","DOI":"10.1109\/IROS.2015.7354129"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1109\/TMECH.2006.878550","article-title":"Design and control of an exoskeleton for the elderly and patients","volume":"11","author":"Kong","year":"2006","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2776","DOI":"10.3390\/s140202776","article-title":"Online phase detection using wearable sensors for walking with a robotic prosthesis","volume":"14","author":"Kamnik","year":"2014","journal-title":"Sensor"},{"unstructured":"Kong, K., and Tomizuka, M. (2008, January 19\u201323). Smooth and continuous human gait phase detection based on foot pressure patterns. Proceedings of the 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA.","key":"ref_21"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1186\/1475-925X-9-41","article-title":"Surface EMG pattern recognition for real-time control of a wrist exoskeleton","volume":"9","author":"Khokhar","year":"2010","journal-title":"Biomed. Eng. Online"},{"unstructured":"Kendall, H.O., Kendall, F.P., and Wadswonh, G.E. (1971). Muscles: Testing and Function, Williams & Wilkins. [2nd ed.].","key":"ref_23"},{"doi-asserted-by":"crossref","unstructured":"Schiele, A., Letier, P., van der Linde, R., and van der Helm, F. (2006, January 9\u201315). Bowden cable actuator for force-feedback exoskeletons. Proceedings of the 2006 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Beijing, China.","key":"ref_24","DOI":"10.1109\/IROS.2006.281712"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1086\/428577","article-title":"Can routine laboratory tests discriminate between severe acute respiratory syndrome and other causes of community acquired pneumonia?","volume":"40","author":"Muller","year":"2005","journal-title":"Clin. Infect. 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