LDR | | 00000nmm u2200205 4500 |
001 | | 000000330847 |
005 | | 20241105132614 |
008 | | 181129s2017 ||| | | | eng d |
020 | |
▼a 9780438126336 |
035 | |
▼a (MiAaPQ)AAI10903027 |
035 | |
▼a (MiAaPQ)umichrackham:001120 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
049 | 1 |
▼f DP |
082 | 0 |
▼a 621 |
100 | 1 |
▼a Koller, Jeffrey R. |
245 | 10 |
▼a Adaptive Controllers for Assistive Robotic Devices. |
260 | |
▼a [S.l.] :
▼b University of Michigan.,
▼c 2017 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2017 |
300 | |
▼a 130 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
500 | |
▼a Advisers: Daniel P. Ferris |
502 | 1 |
▼a Thesis (Ph.D.)--University of Michigan, 2017. |
520 | |
▼a Lower extremity assistive robotic devices, such as exoskeletons and prostheses, have the potential to improve mobility for millions of individuals, both healthy and disabled. These devices are designed to work in conjunction with the user to enh |
520 | |
▼a To address the current obstacles associated with device control and tuning, I have developed novel tools that overcome some of these issues through the design of control architectures that autonomously adapt to the user based upon real-time phys |
520 | |
▼a The framework of my research has been broken down into four major projects. First, I investigated how current standards of processing and analyzing physiological measures could be improved upon. Specifically, I focused on how to analyze non-stea |
590 | |
▼a School code: 0127. |
650 | 4 |
▼a Mechanical engineering. |
650 | 4 |
▼a Robotics. |
690 | |
▼a 0548 |
690 | |
▼a 0771 |
710 | 20 |
▼a University of Michigan.
▼b Mechanical Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0127 |
791 | |
▼a Ph.D. |
792 | |
▼a 2017 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000532
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자
▼b 관리자 |