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On account of the periodicity of the walking motion and sensitivity of gyroscopes the proposed algorithm extracts the frequency domain features from three-dimensional 3D angular velocities of a smartphone. This paper evaluates common walk detection WD and step counting SC algorithms applied to smartphone sensor data.
Xiaomin Kang Baoqi Huang and Guodong Qi.
Walk detection and step counting on unconstrained smartphones. Well pedometry works when applied to smartphones in typi-cal unconstrained use. This paper evaluates common walk detection WD and step counting SC algorithms applied to smartphone sensor data. Using a large dataset 27 people 130 walks 6 smartphone placements optimal algorithm parameters are provided and applied to the data.
The results favour the use of standard. However there is currently no detailed understanding of how well pedometry works when applied to smartphones in typical unconstrained use. This paper evaluates common walk detection WD and step counting SC algorithms applied to smartphone sensor data.
Using a large dataset 27 people 130 walks 6 smartphone placements optimal algorithm parameters are provided and applied to the data. The results favour the use of standard deviation thresholding WD and windowed peak detection. This paper evaluates common walk detection WD and step counting SC algorithms applied to smartphone sensor data.
Using a large dataset 27 people 130 walks 6 smartphone. Smartphone pedometry offers the possibility of ubiquitous health monitoring context awareness and indoor location tracking through Pedestrian Dead Reckoning PDR systems. However there is currently no detailed understanding of how well pedometry works when applied to smartphones in typical unconstrained use.
This paper evaluates common walk detection WD and step counting SC. Walk detection and step counting on unconstrained smartphones articleBrajdic2013WalkDA titleWalk detection and step counting on unconstrained smartphones authorA. Harle journalProceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing year2013.
In this paper a novel algorithm is proposed to simultaneously detect walking motion and count steps through unconstrained smartphones in the sense that the smartphone placement is. Walk detection WD and step counting SC tasks have received much prior attention but were often studied under laboratory conditions and tested on a relatively small number of subjects. Moreover there is currently no detailed understanding of how well WC and SC algorithms work when applied to smartphones in typical unconstrained use.
In this paper a novel algorithm is proposed to simultaneously detect walking motion and count steps through unconstrained smartphones in the sense that the smartphone placement is not only arbitrary but also alterable. On account of the periodicity of the walking motion and sensitivity of gyroscopes the proposed algorithm extracts the frequency domain features from three-dimensional 3D angular velocities of a smartphone. Future work Try some other algorithms Use different or additional sensor Q A Introduction What is the topic Why we need this Why What Dose pedometer works well when applied to smartphones.
Medical Security Walk Detection and Step Counting on Unconstrained Smartphones. Research data supporting Walk detection and step counting on unconstrained smartphones The dataset contains time-annotated sensor traces obtained from smartphones in typical unconstrained use while walking. 27 participants were asked to walk a route at three different walk paces.
Starting with normal followed by fast and ending with slow. Recently with the development of artificial intelligence technologies and the popularity of mobile devices walking detection and step counting have gained much attention since they play an important role in the fields of equipment positioning saving energy behavior recognition etc. In this paper a novel algorithm is proposed to simultaneously detect walking motion and count steps through unconstrained smartphones in the sense that the smartphone.
Brajdic A Harle R. Walk detection and step counting on unconstrained smartphones. Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing pp.
ACM 2013 Google Scholar. The dataset contains time-annotated sensor traces obtained from smartphones in typical unconstrained use while walking. 27 participants were asked to walk a route at three different walk paces.
Starting with normal followed by fast and ending with slow. Each participant walked the same distance and changed herhis speed at markers installed on the path. In this paper we proposed a novel walking detection and step counting method for users with unconstrained smartphones.
Differently from most existing studies the proposed method adopted the gyroscope data and extracted critical walking features in the frequency domain. Moreover an indirect step counting method was reported by multiplying the walking frequency and the walking duration. Walk detection and step counting on unconstrained smartphones Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing.
Salvi Dario Carmelo Velardo Jamieson Brynes and Lionel Tarassenko. An optimised algorithm for accurate steps counting from smart-phone accelerometry In 2018 40th Annual International Conference of the IEEE. A Novel Walking Detection and Step Counting Algorithm Using Unconstrained Smartphones.
Xiaomin Kang Baoqi Huang and Guodong Qi. College of Computer Science Inner Mongolia University Hohhot 010021 China. A Novel Walking Detection and Step Counting Algorithm Using Unconstrained Smartphones.
We propose a robust heading estimation system adapting to the unconstrained use of smartphones. A novel detection and classification method is developed to detect the three motion states timely and discriminate them accurately. For normal working the user heading is estimated by a PCA-based approach.
If a user turn occurs it is estimated by adding horizontal heading change to previous user.