Recognizing whether sensors are on the same body

Pervasive and Mobile Computing

Volumn 8, Issue 6, 2012, Pages 822-836

  Cornelius, Cory T ^a   Kotz, David F ^b  

^a Dartmouth College   (United States)

^b DARTMOUTH COLLEGE   (United States)

Author keywords

Body area networks; mHealth security; Personal health sensing; Same body authentication

Indexed keywords

TELEPHONE SETS;

BODY AREA NETWORK; CELL PHONE; MOBILE HEALTH (M-HEALTH); PERSONAL HEALTH; SENSING SYSTEMS;

MHEALTH;

EID: 84869109363     PISSN: 15741192     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pmcj.2012.06.005     Document Type: Article

References (18)

1. Fitbit, Inc., Fitbit. http://www.fitbit.com/, 2010.
2. Apex Fitness, BodyBugg. http://www.bodybugg.com/, 2010.
3. C. Cornelius, D. Kotz, On usable authentication for wireless body area networks, in: Proceedings of the USENIX Workshop on Health Security and Privacy, HealthSec, pp. 1-2.
4. Freescale Semiconductor, Freescale Xtrinsic accelerometers optimize resolution and battery life in consumer devices, 2010. Press release available at: http://media.freescale.com/phoenix.zhtml?c=196520&p=irol- newsArticle&ID=1470583.
5. L. Bao, S.S. Intille, Activity recognition from user-annotated acceleration data, in: Proceedings of the International Conference on Pervasive Computing, Pervasive, pp. 1-17.
6. T. Brezmes, J.-L. Gorricho, J. Cotrina, Activity recognition from accelerometer data on a mobile phone, in: Proceedings of the International Work-Conference on Artificial Neural Networks, IWANN, pp. 796-799.
7. J. Lester, B. Hannaford, G. Borriello, Are You with Me? - using accelerometers to determine if two devices are carried by the same person, in: Proceedings of the International Conference on Pervasive Computing, Pervasive, pp. 33-50.
8. U. Maurer, A. Smailagic, D.P. Siewiorek, M. Deisher, Activity recognition and monitoring using multiple sensors on different body positions, in: Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks, BSN, pp. 113-116.
9. N. Ravi, N. Dandekar, P. Mysore, M.L. Littman, Activity recognition from accelerometer data, in: Proceedings of the National Conference on Artificial Intelligence, AAAI, pp. 1541-1546.
10. C.-C. Chang, C.-J. Lin, LIBSVM: a library for support vector machines. Software available at: http://www.csie.ntu.edu.tw/~cjlin/libsvm, 2001.
11. SparkFun Electronics, WiTilt v2.5. Data sheet available at: http://www.sparkfun.com/datasheets/Sensors/WiTiltV25.pdf, 2010.
12. Shimmer Research, Shimmer. http://www.shimmer-research.com/, 2011.
13. Z. He, Z. Liu, L. Jin, L.-X. Zhen, J.-C. Huang, Weightlessness feature - a novel feature for single tri-axial accelerometer based activity recognition, in: Proceedings of the International Conference on Pattern Recognition, ICPR, pp. 1-4.
14. R. Mayrhofer, and H. Gellersen Shake well before use: intuitive and secure pairing of mobile devices IEEE Transactions on Mobile Computing 2009 792 806
15. K.S. Kunze, P. Lukowicz, H. Junker, G. Tröster, Where am I: recognizing on-body positions of wearable sensors, in: Proceedings of the International Workshop on Location- and Context-Awareness, LoCa, pp. 264-275.
16. K.S. Kunze, P. Lukowicz, Dealing with sensor displacement in motion-based onbody activity recognition systems, in: Proceedings of the International Conference on Ubiquitous Computing, UbiComp, pp. 20-29.
17. J.C. Sriram, M. Shin, T. Choudhury, D. Kotz, Activity-aware ECG-based patient authentication for remote health monitoring, in: Proceedings of the International Conference on Multimodal Interfaces, ICMI, pp. 297-304.
18. A.T. Barth, M.A. Hanson Jr., Harry C. Powell, D. Unluer, S.G. Wilson, J. Lach, Body-coupled communication for body sensor networks, in: Proceedings of the ICST international Conference on Body Area Networks BodyNets, pp. 1-4.