Human behavior cognition using smartphone sensors

Sensors (Switzerland)

Volumn 13, Issue 2, 2013, Pages 1402-1424

  Pei, Ling ^a   Guinness, Robert ^a   Chen, Ruizhi ^a,b   Liu, Jingbin ^a   Kuusniemi, Heidi ^a   Chen, Yuwei ^a   Chen, Liang ^a   Kaistinen, Jyrki ^c  

^a FINNISH GEODETIC INSTITUTE   (Finland)

^b TEXAS A AND M UNIVERSITY CORPUS CHRISTI   (United States)

^c UNIVERSITY OF HELSINKI   (Finland)

Author keywords

Cognitive phone; Human behavior modeling; Location; LS SVM; Motion recognition; Sensing

Indexed keywords

COGNITIVE PHONE; HUMAN BEHAVIOR MODELING; LS-SVM; MOTION RECOGNITION; SENSING;

LOCATION; SENSORS; SUPPORT VECTOR MACHINES; TELEPHONE SETS;

SOCIAL SCIENCES;

AMBULATORY MONITORING; ARTICLE; BEHAVIOR; EQUIPMENT; HUMAN; MOBILE PHONE; MOTION; MOVEMENT (PHYSIOLOGY); POWER SUPPLY; SUPPORT VECTOR MACHINE;

BEHAVIOR; CELLULAR PHONE; ELECTRIC POWER SUPPLIES; HUMANS; MONITORING, AMBULATORY; MOTION; MOVEMENT; SUPPORT VECTOR MACHINES;

EID: 84875153186     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s130201402     Document Type: Article

References (53)

1. Hu, D.H.; Zhang, X.X.; Yin, J.; Zheng, V.W.; Yang, Q. Abnormal Activity Recognition Based on Hdp-Hmm Models. In Proceedings of the 21st International Joint Conference on Artifical Intelligence, California, CA, USA, 11-17 July 2009; pp. 1715-1720.
2. Pei, L.; Chen, R.; Chen, Y.; Leppäkoski, H.; Perttula, A. Indoor/Outdoor Seamless Positioning Technologies Integrated on Smart Phone. In Proceedings of the International Conference on Advances in Satellite and Space Communications, Colmar, France, 20-25 July 2009; pp. 141-145.
3. Kraemer, I.; Eissfeller, B. A-GNSS: A different approach. Inside GNSS 2009, 4, 52-61.
4. Syrjärinne, J. Studies on Modern Techniques for Personal Positioning. Ph.D. Thesis, Tampere University of Technology, Tampere, Finland, March 2001.
5. Laura, K.; Perala, T.; ich, R. Indoor Positioning Using Wlan Coverage Area Estimates. In IEEE Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN), Zurich, Switzerland, 15-17 September 2010; pp. 1-7.
6. Pei, L.; Chen, R.; Liu, J.; Kuusniemi, H.; Tenhunen, T.; Chen, Y. Using inquiry-based Bluetooth RSSI probability distributions for indoor positioning. J. Glob. Position. Syst. 2010, 9, 122-130.
7. Priyantha, N.B.; Chakraborty, A.; Balakrishnan, H. The Cricket Location-Support System. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, Boston, MA, USA, 6-11 August 2000; pp. 32-43.
8. Bahl, P.; Padmanabhan, V.N. Radar: An In-Building RF Based User Location and Tracking System. In Proceedings of Infocom-Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Tel-Aviv, Israel, 26-30 March 2000; pp. 775-784.
9. Pei, L.; Chen, R.; Liu, J.; Tenhunen, T.; Kuusniemi, H.; Chen, Y. Inquiry-Based Bluetooth Indoor Positioning via RSSI Probability Distributions. In Proceedings of the Second International Conference on Advances in Satellite and Space Communications (SPACOMM 2010), Athens, Greece, 13-19 June 2010; pp. 151-156.
10. Gomes, G.; Sarmento, H. Indoor Location System Using ZigBee Technology. In Proceedings of Third International Conference on Sensor Technologies and Applications, Athens/Glyfada, Greece, 18-23 June 2009; pp. 152-157.
11. Chen, L.; Pei, L.; Kuusniemi, H.; Chen, Y.; Kröger, T.; Chen, R. Bayesian fusion for indoor positioning using bluetooth fingerprints. Wirel. Pers. Commun. 2012, 67, 1-11.
12. Ni, L.M.; Liu, Y.; Lau, Y.C.; Patil, A.P. Landmarc: Indoor location sensing using active RFID. Wirel. Netw. 2004, 10, 701-710.
13. Pei, L.; Chen, R.; Liu, J.; Chen, W.; Kuusniemi, H.; Tenhunen, T.; Kröger, T.; Chen, Y.; Leppäkoski, H.; Takala, J. Motion Recognition Assisted Indoor Wireless Navigation on a Mobile Phone. In Proceedings of the 23rd International Technical Meeting of The Satellite Division of the Institute of Navigation, Portland, OR, USA, 21-24 September 2010; pp. 3366-3375.
14. Liu, J.; Chen, R.; Chen, Y.; Pei, L.; Chen, L. iParking: An intelligent indoor location-based smartphone parking service. Sensors 2012, 12, 14612-14629.
15. Pei, L.; Liu, J.; Guinness, R.; Chen, Y.; Kuusniemi, H.; Chen, R. Using LS-SVM based motion recognition for smartphone indoor wireless positioning. Sensors 2012, 12, 6155-6175.
16. Ruotsalainen, L.; Kuusniemi, H.; Chen, R. Visual-aided Two-dimensional pedestrian indoor navigation with a smartphone. J. Glob. Position. Syst. 2011, 10, 11-18.
17. Mulloni, A.; Wagner, D.; Schmalstieg, D.; Barakonyi, I. Indoor positioning and navigation with camera phones. Pervasive Comput. 2009, 8, 22-31.
18. IndoorAtlas Ltd. Oulu, Finland. Available online: http://www.indooratlas.com (accessed on 22 October 2012).
19. Liu, J.; Chen, R.; Pei, L.; Chen, W.; Tenhunen, T.; Kuusniem, H.; Kröger, T.; Chen, Y. Accelerometer Assisted Wireless Signals Robust Positioning Based on Hidden Markov Model. In Proceedings of the IEEE/ION Position, Location and Navigation Symposium (PLANS) 2010, Indian Wells, CA, USA, 3-6 May 2010; pp. 488-497.
20. Liu, J.; Chen, R.; Pei, L.; Guinness, R.; Kuusniemi, H. Hybrid smartphone indoor positioning solution for mobile LBS. Sensors 2012, 12, 17208-17233.
21. Kuusniemi, H.; Liu, J.; Pei, L.; Chen, Y.; Chen, L.; Chen, R. Reliability considerations of multi-sensor multi-network pedestrian navigation. Radar Sonar Navig. IET 2012, 6, 157-164.
22. Poppe, R. Vision-based human motion analysis: An overview. Comput. Vis. Image Understand 2007, 108, 4-18.
23. Chung, T.-Y.; Chen, Y.-M.; Hsu, C.-H. Adaptive momentum-based motion detection approach and its application on handoff in wireless networks. Sensors 2009, 9, 5715-5739.
24. Fong, D.T.-P.; Chan, Y.-Y. The use of wearable inertial motion sensors in human lower limb biomechanics studies: A systematic review. Sensors 2010, 10, 11556-11565.
25. Yang, C.-C.; Hsu, Y.-L. A Review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 2010, 10, 7772-7788.
26. Zeng, H.; Zhao, Y. Sensing movement: Microsensors for body motion measurement. Sensors 2011, 11, 638-660.
27. Musleh, B.; García, F.; Otamendi, J.; Armingol, J.M.; De la Escalera, A. Identifying and tracking pedestrians based on sensor fusion and motion stability predictions. Sensors 2010, 10, 8028-8053.
28. Kavanagh, J.J.; Menz, H.B. Accelerometry: A technique for quantifying movement patterns during walking. Gait Posture 2008, 28, 1-15.
29. Baek, J.; Lee, G.; Park, W.; Yun, B. Accelerometer signal processing for user activity detection. Knowl. Based Intell. Inform. Eng. Syst. 2004, 3215, 610-617.
30. Chen, W.; Fu, Z.; Chen, R.; Chen, Y.; Andrei, O.; Kröger, T; Wang, J. An Integrated GPS and Multi-Sensor Pedestrian Positioning System for 3D Urban Navigation. In Proceedings of Joint Urban Remote Sensing Event, Shanghai, China, 20-22 May 2009; pp. 1-6.
31. Yang, J. Toward Physical Activity Diary: Motion Recognition Using Simple Acceleration Features with Mobile Phones. In Proceedings of the 1st International Workshop on Interactive Multimedia for Consumer Electronics (IMCE), Beijing, China, 19-23 October 2009; pp. 1-10.
32. Frank, K.; Nadales, M.J.V.; Robertson, P.; Angermann, M. Reliable Real-Time Recognition of Motion Related Human Activities Using MEMS Inertial Sensors. In Proceedings of the 23rd International Technical Meeting of the Satellite Division of the Institute of Navigation, Portland, OR, USA, 21-24 September 2010; pp. 2906-2912.
33. Susi, M.; Borio, D.; Lachapelle, G. Accelerometer Signal Features and Classification Algorithms for Positioning Applications. In Proceedings of International Technical Meeting of the Institute of Navigation, San Diego, CA, USA, 24-26 January 2011.
34. Pei, L.; Chen, R.; Liu, J.; Kuusniemi, H.; Chen, Y.; Tenhunen, T. Using Motion-Awareness for the 3D Indoor Personal Navigation on a Smartphone. In Proceedings of the 24rd International Technical Meeting of the Satellite Division of the Institute of Navigation, Portland, OR, USA, 19-23 September 2011; pp. 2906-2912.
35. Eagle, N.; Pentland, A. Reality mining: Sensing complex social systems. Pers. Ubiquitous Comput. 2006, 10, 255-268.
36. Adams, B.; Phung, D.; Venkatesh, S. Sensing and using social context. ACM Trans. Multimed. Comput. Commun. Appl. 2008, 5, 1-27.
37. Anderson, I.; Maitland, J.; Sherwood, S.; Barkhuus, L.; Chalmers, M.; Hall, M.; Muller, H. Shakra: Tracking and sharing daily activity levels with unaugmented mobile phones. Mob. Netw. Appl. 2007, 12, 185-199.
38. Choudhury, T.; Pentland, A. Sensing and Modeling Human Networks Using the Sociometer. In Proceedings of the 7th IEEE International Symposium on Wearable Computers (ISWC2003), Washington D.C., WA, US, October 2003; pp. 216-222.
39. Choudhury, T.; Philipose, M.; Wyatt, D.; Lester, J. Towards activity databases: using sensors and statistical models to summarize people's lives. Data Eng. Bull. 2006, 29, 49-58.
40. Lane, N.D.; Miluzzo, E.; Lu, H.; Peebles, D.; Choudhury, T.; Campbell, A.T. A survey of mobile phone sensing. Commun. Mag. 2010, 48, 140-150.
41. Campbell, A.; Choudhury, T. From smart to cognitive phones. Pervasive Comput. 2012, 11, 7-11.
42. Pei, L.; Chen, R.; Liu, J.; Liu, Z.; Kuusniemi, H.; Chen, Y.; Zhu, L. Sensor Assisted 3D Personal Navigation on A Smart Phone in GPS Degraded Environments. In Proceedings of 2011 19th International Conference on Geoinformatics, Shanghai, China, 24-26 June 2011; pp. 1-6.
43. Kaplan, E.D.; Hegarty, C.J. Understanding GPS: Principles and Applications; Artech House Publishers: Norwood, MA, USA, 2006.
44. Li, B.; Quader, I.J.; Dempster, A.G. On outdoor positioning with Wi-Fi. J. Glob. Position Syst. 2008, 7, 18-26.
45. Youssef, M.; Agrawala, A.; Shankar, A.U. WLAN Location Determination via Clustering and Probability Distributions. In Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom 2003), Fort-Worth, TX, USA, 23-26 March 2003; pp. 143-150.
46. Roos, T.; Myllymaki, P.; Tirri, H.; Misikangas, P.; Sievänen, J. A probabilistic approach to WLAN user location estimation. Int. J. Wirel. Inform. Netw. 2002, 9, 155-164.
47. Guyon, I.; Elisseeff, A. An introduction to variable and feature selection. J. Mach. Learn. Res. 2003, 3, 1157-1182.
48. Hall, M.A. Correlation-Based Feature Selection for Machine Learning. Ph.D. Thesis, The University of Waikato, Hamilton, New Zealand, April 1999.
49. Jain, A.; Zongker, D. Feature selection: Evaluation, application, and small sample performance. Pattern Anal. Mach. Intell. 1997, 19, 153-158.
50. Hospodar, G.; Gierlichs, B.; Mulder, E.D.; Verbauwhede, I.; Vandewalle, J. Machine learning in side-channel analysis: A first study. J. Cryptogr. Eng. 2011, 1, 293-302.
51. Luts, J.; Ojeda, F.; Van de Plas, R.; De Moor, B.; Van Huffel, S.; Suykens, J.A.K. A tutorial on support vector machine-based methods for classification problems in chemometrics. Anal. Chim. Acta 2010, 665, 129-145.
52. Suykens, J.A.K.; Vandewalle, J. Least squares support vector machine classifiers. Neur. Process. Lett. 1999, 9, 293-300.
53. Pei, L.; Liu, J.; Guinness, R.; Chen, Y.; Kröger, T.; Chen, R.; Chen, L. The Evaluation of WiFi Positioning in a Bluetooth and WiFi Coexistence Environment. In Proceedings of 2nd International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service (UPINLBS 2012), Helsinki, Finland, 2-5 October 2012.