Mahalanobis-Taguchi-Fukuda Approach to Human Motion Control

2019 ◽  
Author(s):  
Shuichi Fukuda
Keyword(s):  
Tacit Knowledge ◽  
Motion Control ◽  
Mahalanobis Distance ◽  
Quantitative Measurement ◽  
Network Formation ◽  
Human Motion ◽  
Team Formation ◽  
Adaptive Network ◽  
Soft Robots ◽  
Or Team

Abstract Learning from failures approach how to control human motion is developed by extending Mahalanobis Taguchi System. It enables quantitative measurement of how the learner is improving in his or her learning, It helps to acquire tacit knowledge such as swimming, for which we do not have valid approach. Since Mahalanobis Distance is a unitless measure for multi-dimensional variables, this approach can be extended to many adaptive network formation and management, because this approach let the learner recognize how he or she can coordinate their body pars to adapt to the changing situations. Thus, the approach ca be applied to development and operation of soft robots and adaptive network or team formation and management in the IoT connected society.

scholarly journals sEMG-Based Continuous Estimation of Finger Kinematics via Large-Scale Temporal Convolutional Network

2021 ◽  
Vol 11 (10) ◽  
pp. 4678
Author(s):  
Chao Chen ◽  
Weiyu Guo ◽  
Chenfei Ma ◽  
Yongkui Yang ◽  
Zheng Wang ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Motion Control ◽  
Large Scale ◽  
Human Motion ◽  
Kernel Size ◽  
Continuous Motion ◽  
Convolutional Network ◽  
Continuous Estimation ◽  
Discrete Motion ◽  
Precision Rate

Since continuous motion control can provide a more natural, fast and accurate man–machine interface than that of discrete motion control, it has been widely used in human–robot cooperation (HRC). Among various biological signals, the surface electromyogram (sEMG)—the signal of actions potential superimposed on the surface of the skin containing the temporal and spatial information—is one of the best signals with which to extract human motion intentions. However, most of the current sEMG control methods can only perform discrete motion estimation, and thus fail to meet the requirements of continuous motion estimation. In this paper, we propose a novel method that applies a temporal convolutional network (TCN) to sEMG-based continuous estimation. After analyzing the relationship between the convolutional kernel’s size and the lengths of atomic segments (defined in this paper), we propose a large-scale temporal convolutional network (LS-TCN) to overcome the TCN’s problem: that it is difficult to fully extract the sEMG’s temporal features. When applying our proposed LS-TCN with a convolutional kernel size of 1 × 31 to continuously estimate the angles of the 10 main joints of fingers (based on the public dataset Ninapro), it can achieve a precision rate of 71.6%. Compared with TCN (kernel size of 1 × 3), LS-TCN (kernel size of 1 × 31) improves the precision rate by 6.6%.

The NEURARM: towards a Platform for joint Neuroscience Experiments on Human Motion Control Theories

2007 ◽  
Author(s):  
Nicola Vitiello ◽  
Emanuele Cattin ◽  
Stefano Roccella ◽  
Francesco Giovacchini ◽  
Fabrizio Vecchi ◽  
...  
Keyword(s):  
Motion Control ◽  
Human Motion ◽  
Control Theories

2P1-J19 Motion control of kicking mechanism based on the analysis of human motion of kicking

2008 ◽  
Vol 2008 (0) ◽  
pp. _2P1-J19_1-_2P1-J19_2
Author(s):  
Yuusuke OYAMA ◽  
Kaname KANAMOTO ◽  
Yoshikazu ISHII ◽  
Toshinari AKIMOTO ◽  
Akihiro MATSUMOTO
Keyword(s):  
Motion Control ◽  
Human Motion

Human motion control with physically plausible foot contact models

2015 ◽  
Vol 31 (6-8) ◽  
pp. 883-891 ◽  
Author(s):  
Jongmin Kim ◽  
Hwangpil Park ◽  
Jehee Lee ◽  
Taesoo Kwon
Keyword(s):  
Motion Control ◽  
Human Motion ◽  
Contact Models

scholarly journals Micro-business entrepreneurs and bricoleurs on their way towards sustainable practice – implications for learning processes

2020 ◽  
Vol 32 (4) ◽  
pp. 89-104
Author(s):  
Anette Oxenswärdh
Keyword(s):  
Tacit Knowledge ◽  
Learning Process ◽  
Course Design ◽  
Practical Knowledge ◽  
Learning Processes ◽  
Team Leader ◽  
Sustainable Solutions ◽  
Explorative Study ◽  
Or Team ◽  
Sustainable Practice

The purpose of the study was to investigate how some micro-business entrepreneurs and bricoleurs experience their learning processes through workshops, especially with respect to sustainability issues. This qualitative and explorative study focuses on learning processes during the GreenBizz course, which are analysed on the basis of inquiries and observations of discussions among course participants and on documents describing the course design and assignments. It was found that entrepreneurs are aware and are familiar with sustainability issues but they have neither proper tools nor the knowhow for implementing sustainable changes in their businesses. To be successful, the learning process needs to sufficiently heterogeneous, should involve the transmission of tacit knowledge and provide opportunities for participants to learn about their motivations and should include both theoretical and practical elements. Participation in the course enables entrepreneurs to network with other entrepreneurs, give support and share knowledge about sustainable solutions in their businesses. The study shows that such courses not only must allow for a certain degree of flexibility but also require a course or team leader with a solid and practical knowledge in entrepreneurship and sustainability.

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