A Motion Recognition Method Using Foot Pressure Sensors
作者： Ayumi Ohnishi , Tsutomu Terada , Masahiko Tsukamoto
关键词: Foot pressure 、 Posture recognition 、 Motion recognition 、 Pattern recognition 、 Gesture 、 Thumb 、 Computer science 、 Pressure sensing 、 Pressure sensor 、 Gesture recognition 、 Artificial intelligence
摘要: This paper proposes a method for recognizing postures and gestures using foot pressure sensors, we investigate optimal positions sensors on soles are the best motion recognition. In experiments, recognition accuracies of 22 kinds daily were evaluated from foot-pressure sensor values. Furthermore, optimum measurement points high accuracy examined by evaluating combinations two areas round-robin basis. As result, when selecting user, was about 93.6% average. Although individual differences seen, each subject largely divided into major patterns. When chosen, near thenar, which is located thumb ball, heel or point outside middle highly recognized. Of points, one commonly thenar subjects. By taking three data covering these combinations, it will be possible to cope with differences. The averaged all subjects classified an 91.0% On basis results, types sensing shoes developed.
acm.org
sci-hub.se 参考文章(14)
Kazuya Murao, Ryuichi Matsukura, Ai Yano, Tsutomu Terada, Tsutomu Terada, Evaluating Sensor Placement and Gesture Selection for Mobile Devices Journal of Information Processing. ,vol. 8, pp. 1154- 1165 ,(2013) , 10.11185/IMT.8.1154
Edward Sazonov, Nagaraj Hegde, Raymond C. Browning, Edward L. Melanson, Nadezhda A. Sazonova, Posture and Activity Recognition and Energy Expenditure Estimation in a Wearable Platform IEEE Journal of Biomedical and Health Informatics. ,vol. 19, pp. 1339- 1346 ,(2015) , 10.1109/JBHI.2015.2432454
M. Sousa, A. Techmer, A. Steinhage, C. Lauterbach, P. Lukowicz, Human tracking and identification using a sensitive floor and wearable accelerometers ieee international conference on pervasive computing and communications. pp. 166- 171 ,(2013) , 10.1109/PERCOM.2013.6526728
Koumei Fukahori, Daisuke Sakamoto, Takeo Igarashi, Exploring Subtle Foot Plantar-based Gestures with Sock-placed Pressure Sensors human factors in computing systems. pp. 3019- 3028 ,(2015) , 10.1145/2702123.2702308
Hiroki Watanabe, Tsutomu Terada, Masahiko Tsukamoto, Ultrasound-based movement sensing, gesture-, and context-recognition international symposium on wearable computers. pp. 57- 64 ,(2013) , 10.1145/2493988.2494335
Iván González, Jesús Fontecha, Ramón Hervás, José Bravo, An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles Sensors. ,vol. 15, pp. 16589- 16613 ,(2015) , 10.3390/S150716589
T. Starner, J. Auxier, D. Ashbrook, M. Gandy, The gesture pendant: a self-illuminating, wearable, infrared computer vision system for home automation control and medical monitoring international symposium on wearable computers. pp. 87- 94 ,(2000) , 10.1109/ISWC.2000.888469
Kentaro Tsubaki, Tsutomu Terada, Masahiko Tsukamoto, An Activity Recognition Method by Measuring Circumference of Body Parts augmented human international conference. pp. 13- ,(2016) , 10.1145/2875194.2875220
Guillermo Talavera, Joan Garcia, John Rösevall, Cristina Rusu, Carlos Carenas, Fanny Breuil, Elisenda Reixach, Holger Arndt, Stefan Burkard, Richie Harte, Liam Glynn, Jordi Carrabina, Fully-Wireless Sensor Insole as Non-invasive Tool for Collecting Gait Data and Analyzing Fall Risk ambient intelligence. pp. 15- 25 ,(2015) , 10.1007/978-3-319-26508-7_2
Christopher Moufawad El Achkar, Constanze Lenoble-Hoskovec, Anisoara Paraschiv-Ionescu, Kristof Major, Christophe Büla, Kamiar Aminian, None, Physical Behavior in Older Persons during Daily Life: Insights from Instrumented Shoes Sensors. ,vol. 16, pp. 1225- ,(2016) , 10.3390/S16081225