Knit Stretch Sensor Placement for Body Movement Sensing

Author(s):  
An Liang ◽  
Rebecca Stewart ◽  
Rachel Freire ◽  
Nick Bryan-Kinns
2012 ◽  
Author(s):  
Riitta Keskinen Rosenqvist ◽  
Gabriele Biguet ◽  
Adrienne Levy-Berg
Keyword(s):  

Author(s):  
Sinto Robindo ◽  
Melda Rumia Rosmeri Simorangkir

ABSTRACT All aspects of development are very important in a person's life where the development of cognition, affection and psychomotor is well developed in accordance with its development, these three aspects can be said to be good and successful if the three aspects develop well. Like wise with the psychomotor aspect where between gross motor and fine motor are also balanced. Motoric is the development of coordinated body movement control between nerves, brain, and spinal cord (spinal cord or spinal cord). Child's gross motorization can be optimized by improving his motor movement coordination skills through physical activity in the form of coordination of body movements. Like throwing, catching, kicking, running, melopat, and maintaining balance. The condition of a Down Syndrome child who experiences weakness in the ability to think will affect in all aspects of his life. Down syndrome children have problems in cognitive abilities, effective and self-care abilities. This results in them needing special education. Basically, the educational goals that children with Down Syndrome want to achieve are not different from those of education in general. Because Down Syndrome children themselves are born in the midst of society. Keywords: football sports, gross motoric, down syndrome


2020 ◽  
Vol 2020 (17) ◽  
pp. 2-1-2-6
Author(s):  
Shih-Wei Sun ◽  
Ting-Chen Mou ◽  
Pao-Chi Chang

To improve the workout efficiency and to provide the body movement suggestions to users in a “smart gym” environment, we propose to use a depth camera for capturing a user’s body parts and mount multiple inertial sensors on the body parts of a user to generate deadlift behavior models generated by a recurrent neural network structure. The contribution of this paper is trifold: 1) The multimodal sensing signals obtained from multiple devices are fused for generating the deadlift behavior classifiers, 2) the recurrent neural network structure can analyze the information from the synchronized skeletal and inertial sensing data, and 3) a Vaplab dataset is generated for evaluating the deadlift behaviors recognizing capability in the proposed method.


2020 ◽  
Vol 14 (1) ◽  
pp. 69-81
Author(s):  
C.H. Li ◽  
Q.W. Yang

Background: Structural damage identification is a very important subject in the field of civil, mechanical and aerospace engineering according to recent patents. Optimal sensor placement is one of the key problems to be solved in structural damage identification. Methods: This paper presents a simple and convenient algorithm for optimizing sensor locations for structural damage identification. Unlike other algorithms found in the published papers, the optimization procedure of sensor placement is divided into two stages. The first stage is to determine the key parts in the whole structure by their contribution to the global flexibility perturbation. The second stage is to place sensors on the nodes associated with those key parts for monitoring possible damage more efficiently. With the sensor locations determined by the proposed optimization process, structural damage can be readily identified by using the incomplete modes yielded from these optimized sensor measurements. In addition, an Improved Ridge Estimate (IRE) technique is proposed in this study to effectively resist the data errors due to modal truncation and measurement noise. Two truss structures and a frame structure are used as examples to demonstrate the feasibility and efficiency of the presented algorithm. Results: From the numerical results, structural damages can be successfully detected by the proposed method using the partial modes yielded by the optimal measurement with 5% noise level. Conclusion: It has been shown that the proposed method is simple to implement and effective for structural damage identification.


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