A Novel Three-Dimensional Gait Analysis System

2012 ◽  
Vol 569 ◽  
pp. 352-355 ◽  
Author(s):  
Tao Liu ◽  
Yoshio Inoue ◽  
Kyoko Shibata ◽  
Kozou Shiojima ◽  
Ji Bin Yin

Three-dimensional (3D) lower limb kinematic and kinetic analysis based on ambulatory measurements is introduced in this paper. We developed a wireless sensor system composed of a mobile force plate system, 3D motion sensor units and a wireless data logger. 3D motions of body segment and triaxial ground reaction force (GRF) could be simultaneously measured using the system, and the data obtained from sensor units on thighs, shanks and feet could be transferred to a personal computer by wireless local area network (LAN). An inverse dynamics method was adopted to calculate triaxial joint moments. The accuracy of kinematics and kinetics (joint moments) assessment is validated against results obtained from the stationary measurement system based on camera movement analysis and force plates.

Author(s):  
Chaithra. H. U ◽  
Vani H.R

Now a days in Wireless Local Area Networks (WLANs) used in different fields because its well-suited simulator and higher flexibility. The concept of WLAN  with  advanced 5th Generation technologies, related to a Internet-of-Thing (IOT). In this project, representing the Network Simulator (NS-2) used linked-level simulators for Wireless Local Area Networks and still utilized IEEE 802.11g/n/ac with advanced IEEE 802.11ah/af technology. Realization of the whole Wireless Local Area Networking linked-level simulators inspired by the recognized Vienna Long Term Evolution- simulators. As a outcome, this is achieved to link together that simulator to detailed performances of Wireless Local Area Networking with Long Term Evolution, operated in the similar RF bands. From the advanced 5th Generation support cellular networking, such explore is main because different coexistences scenario can arise linking wireless communicating system to the ISM and UHF bands.


Jurnal Teknik ◽  
2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Heru Abrianto

Microstrip antenna which designed with dual feeding at 2.4 GHz and 5.8 GHz can meet WLAN (Wireless Local Area Network) application.Antenna fabrication use PCB FR4 double layer with thickness 1.6 mm and dielectric constant value 4.4. The length of patch antenna according to calculation 28.63 mm, but to get needed parameter length of patch should be optimized to 53 mm. After examination, this antenna has VSWR 1.212 at 2.42 GHz and 1.502 at 5.8 GHz, RL -13.94 dB at 2.42 GHz and -20.357 dB at 5.8 GHz, gain of antenna 6.16 dB at 2.42 GHz and 6.91 dB at 5.8 GHz, the radiation pattern is bidirectional. Keywords : microstrip antenna, wireless LAN, dual polarization, single feeding technique


2018 ◽  
Author(s):  
Kiramat

IEEE 802.11 is a set of media access control (MAC) and physical layer (PHY) specifications for implementing wireless local area network (WLAN) computer communications. Maintained by the Institute of Electrical and Electronics Engineers (IEEE) LAN/MAN Standards Committee (IEEE 802). This document highlights the main features of IEEE 802.11n variant such as MIMO, frame aggregation and beamforming along with the problems in this variant and their solutions


2020 ◽  
Vol 1550 ◽  
pp. 032078
Author(s):  
Kaigang Fan ◽  
Xin Chen ◽  
Biao Zhao ◽  
Jiale Wang ◽  
Wenbin Cui ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2000
Author(s):  
Marius Laska ◽  
Jörg Blankenbach

Location-based services (LBS) have gained increasing importance in our everyday lives and serve as the foundation for many smartphone applications. Whereas Global Navigation Satellite Systems (GNSS) enable reliable position estimation outdoors, there does not exist any comparable gold standard for indoor localization yet. Wireless local area network (WLAN) fingerprinting is still a promising and widely adopted approach to indoor localization, since it does not rely on preinstalled hardware but uses the existing WLAN infrastructure typically present in buildings. The accuracy of the method is, however, limited due to unstable fingerprints, etc. Deep learning has recently gained attention in the field of indoor localization and is also utilized to increase the performance of fingerprinting-based approaches. Current solutions can be grouped into models that either estimate the exact position of the user (regression) or classify the area (pre-segmented floor plan) or a reference location. We propose a model, DeepLocBox (DLB), that offers reliable area localization in multi-building/multi-floor environments without the prerequisite of a pre-segmented floor plan. Instead, the model predicts a bounding box that contains the user’s position while minimizing the required prediction space (size of the box). We compare the performance of DLB with the standard approach of neural network-based position estimation and demonstrate that DLB achieves a gain in success probability by 9.48% on a self-collected dataset at RWTH Aachen University, Germany; by 5.48% for a dataset provided by Tampere University of Technology (TUT), Finland; and by 3.71% for the UJIIndoorLoc dataset collected at Jaume I University (UJI) campus, Spain.


2011 ◽  
Author(s):  
Deepak Malik ◽  
Ankur Singhal ◽  
R. B. Patel ◽  
B. P. Singh

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