Empathic computing

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3864 LNAI, Issue , 2006, Pages 67-85

  Cai, Yang ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMBIENT INTELLIGENCE; CASE STUDIES; EMBEDDED PROCESSORS; MACHINE-LEARNING ALGORITHMS; MULTI RESOLUTIONS; POWER LAWS; SEMANTIC DIFFERENTIAL; SENSOR WEBS; WIRELESS AD-HOC NETWORKS; EMPATHIC COMPUTING; POWER-LAW; SENSOR WEB;

AD HOC NETWORKS; ARTIFICIAL INTELLIGENCE; AVALANCHES (SNOWSLIDES); HEALTH; INFORMATION THEORY; LEARNING ALGORITHMS; LEARNING SYSTEMS; SENSOR NETWORKS; SENSORS; SNOW; TELECOMMUNICATION NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS; AMBIENT INTELLIGENCE; INVERSE PROBLEMS; SEMANTICS; WEARABLE COMPUTERS; WEARABLE TECHNOLOGY; WIRELESS AD HOC NETWORKS;

WIRELESS SENSOR NETWORKS; WEARABLE SENSORS;

EID: 33847061777     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11825890_3     Document Type: Conference Paper

References (96)

1. Aarts, E and Marzano, S. The new everyday: views on Ambient Intelligence, 010 Publishers Rotterdam; 2003
2. Akgul, Y.S., et at.: Automatic Extraction and Tracking of the Tongue Contours. IEEE Trans. on Medical Imaging. Vol.18, No. 10, October, 1999
3. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Networks: A Survey (2001)
4. Albowicz, Joe, Chen, Alvin, Zhang, Lixia: Recursive Position Estimation in Sensor Networks. UCLA Internet Research Laboratory.
5. Anderson, K., Qiu, Y., Whittaker, A.R., Lucas, Margaret: Breath sounds, asthma, and the mobile phone. Lancet. 358:1343-44. (2001)
6. Backhaus, W., Kliegle, R. and Werner, J. (eds): Color Vision, Walter de Gruyter, Berlin, New York, 1998
7. Biship, Christopher M.: Neural Networks for Pattern Recognition. Oxford: Oxford UP, 1995.
8. Bodymedia: www.bodymedia.com
9. Bossert, W. H. (1963): Chemical communication among animals. Recent Progress in Hormone Research 19, 673-716.
10. Cai, Y et al,: Ambient Diagnostics, in Y. Cai (ed.) Ambient Intelligence for Scientific Discovery, LNAI 3345, pp. 248-262, 2005
11. Cai, Y. and Milcent, G.: Video-On-Demand Network Throughput Control, Proceedings of Ambient Intelligence for Everyday Life, San Sebastian, Spain, July, 2005
12. Chan, M., Hariton, C., Ringeard, P., Campo, E.: Smart House Automation System for the Elderly and the Disabled. Systems, Man and Cybernetics, 1995. 'Intelligent Systems for the 21st Century'., IEEE International Conference.
13. Chaney, G.R.: Do you Snore? http://www.garnetchaney.com/help for snoring.shtml
14. Chen, S., Cowan, C.F.N., and Grant, P.M.: Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on Neural Networks, Vol.2, no.2, March. (1991) 302-309
15. Chong, Chee-Yee, and Kumar, Srikanta P.: Sensor Networks: Evolution, Opportunity, an Challenges (2003)
16. Crossbow: MOTE-KIT 5×4×. 2005. Crossbow Technology Inc.
17. Dewsburry, Guy, Taylor, Bruce, Edge, Martin: Designing Safe Smart Home Systems for Vulnerable People.
18. ELIZA demo: http://www-ai.ijs.si/cgi-bin/eliza/eliza_script
19. Environmental Studies with the Sensor Web: Principles and Practice, by Kevin A. Delin, Shannon P. Jackson, David W. Johnson, Scott C. Burleigh, Richard R. Woodrow, J. Michael McAuley, James M. Dohm, Felipe Ip, Ty P.A. Ferré, Dale F. Rucker, and Victor R. Baker, Sensors, Vol. 5, 2005, pp. 103-117
20. Farringdon, Jonathan, and Sarah Nashold: Continuous Body Monitoring. Ambient Intelligence for Scientific Discovery (2005): 202-223.
21. Figueiredo, M, et al: Expanding NASA's Data Processing to Spacecraft, Computer, June, 1999
22. Galstyan, A.: Distributed online Localization in sensor networks using a moving target. University of Southern California. 2004
23. Gist, Y. J., and Lisa I. Hetzel. Department of Commerce: We are the People: Aging in the United States. N.p.: n.p., 2004.
24. Gunarathne, G.P. Presmasiri, Gunarathne, Tharaka R.: Arterial Blood-Volume Pulse Analyser. IEEE, Instrumentation and Measurement Technology Conference, AK, USA, May. (2002) 1249-1254
25. Hayes, P.J. and Ford, K.M. (1995): Turing Test Considered Harmful, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI-95), pp. 972-977, Montreal.
26. Herzog, A., and Lind, L.: Network Solutions for Home Health Care Applications. Linkoping University (2003)
27. HomeLab: http://www.research.philips.com/technologies/misc/homelab/
28. HomeNet: http://homenet.hcii.cs.cmu.edu/http://www.coe.berkeley.edu/ labnotes/1101smartbuildings.html http://www7.nationalacademies.org/cstb/ wp_digitaldivide.pdf
29. Hu, Y., B. Lin and Y. Cai: Determination of sea surface wind speed and temperature using TMI data: A General Regression Neural Network Approach. Submitted to Remote Sensing of Environment.
30. Jang, J.H., Kim,J.E., Park.K.M., Park.S.O., Chang.Y.S., Kim,B.Y.: Development of the Digital Tongue Inspection System with Image Analysis. Proceedings of the Second Joint EMBS/BMES Conference. Houston, TX, USA. October 23-26. (2002)
31. Kaiser, R.: Smart toilet a sure sign of future technology. Chicago Tribune. Saturday December 23. (2000)
32. Kaiser, W J., and G J. Pottie.: Wireless Integrated Network Sensors. Communica-tion of the ACM May 2000: 51-58.
33. Kohonen, T.: Self-organization and Associative Memory. 2nd edition, Springer, Berlin. (1988)
34. Kohonen, Teuvo, Barna, Gyorgy, Chrisley, Ronald: Statistical Pattern Recognition with Neural Networks: Benchmarking Studies. Helsinki University of Technology.
35. Lansing, F., L. Lemmerman, A. Walton, G. Bothwell, K. Bhasin and G. Prescott, 2002: Needs for Communication and Onboard Processing in the Vision Era. 2002 IGARSS conference proceeding.
36. Legg, Gary. ZigBee: Wireless Technology for Low-Power Sensor Networks. 6 May 2004. TachOnLine.
37. Lewin, M.E., and Altman, S., eds. America's Health Care Safety Net: Intact but Endangered, Institute of Medicine, 2000.
38. Li, Q., Rosa, Michael De, Rus, Daniela: Distributed Algorithms for Guiding Navigation across a Sensor Network. Dartmouth Department of Computer Science (2003)
39. Li, W.B.: Ergonomics for Interior and Furniture Design, China Forestry Press, 2001
40. LiveNet: http://hd.media.mit.edu/livenet/
41. Mainwaring, Alan, Polastre, Joseph, Szewczyk, Robert, Culler, David, Anderson, John: Wireless Sensor Networks for Habitat Monitoring. (2002).
42. McClintock, M.K. (1984). Estrous synchrony: modulation of ovarian cycle length by female pheromones. Physiological Behavior 32, 701-705
43. McDermott, M.M. et al: Functional Decline in Peripheral Arterial Disease: Associations With the Ankle Brachial Index and Leg Symptoms. JAMA, July. 292:453-461 (2004)
44. McNabb, R.: The Paradox of Empathy, Philosophy Now, No.52, 2005
45. Meribout M., Nakanishi M.; Ogura T., A parallel algorithm for real-time object recognition, Pattern Recognition, Sept. 2002, vol. 35, no. 9
46. Michell, T.: Machine Learning, The McGraw-Hill Companies, 1997
47. Moore, G.: Cramming more components onto integrated circuits. Electronics, Vol. 38, No. 8, April 19. (1965)
48. Ordonez, J.: The Web Chat That Saved Mom's Life, Newsweek, November 28, 2005
49. Pasterkamp, H., Kraman, S.,S., Wodicka, G.R.: Respiratory sounds: advances beyond the stethoscope. American Journal of Respiratory Critical Care Medicine. 156:974-87 (1997)
50. Pathirana, P.N.: Node Localization using mobile robots in delay-tolerant sensor networks, July 2005
51. Perrig, P., R. Szewczyk, J.D., T.V. Wen, D. E. Culler, SPINS: Security Protocols for Sensor Networks, Wireless Networks, Volume 8, Issue 5, Sep 2002, Pages 521 - 534
52. Picton, P.: Neural Networks. 2nd edition, Palgrave, Basingstoke. (2000)
53. Popple, A.V.: The Turing Test as a Scientific Experiment. Psychology, 7(15), 1996
54. Rinberg, D. and Davidowitz, H. Do cockroaches 'know' about fluid dynamics? Nature 2000 Jul 27;406(6794):368
55. Rodgers, C.D., Inverse Methods for Atmospheric Sounding, World Scientific. 2002.
56. Schnorrenberger, C. and Schnorrenberger, B. Pocket Atlas of Tongue Diagnosis, Thieme, Stuttgart, New York, 2005
57. Sensor Web at JPL: http://sensorwebs.jpl.nasa.gov/
58. Shah, Rahul C., Rabaey, Jan M.: Energy Aware Routing for Low Energy Ad Hoc Sensor Networks. University of California Berkley 2002.
59. Silverstrim, J.E, H. Eric W, C. Kent: Method and Apparatus for Multi-Waveform Wireless Sensor Network. Patent WO2004US33051 (5-12-2005).
60. Sinha, Amit, Chandrakasan, Anantha: Dynamic Power Management in Wireless Sensor Networks. IEEE Design & Test of Computers pg 62-74 (2001)
61. Smith, R.: Alarm signals in fishes. Rev Fish Biol Fish 2:33-63, 1992
62. Spath, H.: Cluster analysis algorithms. Ellis Horwood Ltd., Chichester. (1980)
63. Spiteri, M.A., Cook, D.G., Clarke, S.W.: Reliabilty of eliciting physical signs in examination of the chest. Lancet. 2:873-75. (1988)
64. Starner, T.: Interview with Thad Starner, by Peter Thomas. New Scientist. http://www.media.mit.edu/wearables/lizzy/newsci.html (1995)
65. Sung, M. and A. Pentland, MIThril LiveNet: Health and Lifestyle Networking, Workshop on Applications of Mobile Embedded Systems (WAMES'04) at Mobisys'04, Boston, MA, June, 2004
66. Sung, M. and Pentland, A. Minimally-Invasive Physiological Sensing for Human-Aware Interfaces, HCI International 2005, HCII'05
67. Sung, M., A. Pentland, Minimally-Invasive Physiological Sensing for Human-Aware Interfaces, HCI International 2005, (HCII'05)
68. Sung, M., C. Marci, A. Pentland: Wearable Infrastructure and Sensing for Real-time clinical Feedback Systems for Rehabilitation, Journal of NeuroEngineering and Rehabilitation, (JNER'05)
69. Tanz, O and Shaffer, J.: Wireless Local Area Network Positioning, in Y. Cai (ed.) Ambient Intelligence for Scientific Discovery, LNAI3345, pp. 248-262, 2005
70. Taylor, C.: Simultaneous Localization, Calibration, and Tracking in an ad Hoc Sensor Network.. MIT April 2005
71. Tessier, R. et al: Reconfigurable Computing for digital signal processing: A survey, The Journal of VLSI Signal Processing, May, 2001, vol. 28, no. 1 and 2.
72. Tredennick, N. Get ready for reconfigurable computing, Computer Design, pp 55-63, 1998.
73. Turing, A.M.: Computing Machinery and Intelligence. Mind, 59: 433-460, 1950
74. Vann, L. and Y. Hu: A Neural Network Inversion System for Atmospheric Remote-Sensing Measurements. 2002 IEEE IMTC
75. Wang, J. J.; Katz, R. B.: Plants, W. C., SRAM Based Re-Programmable FPGA for Space Applications. IEEE trans. on nuclear science, 1999, vol. 46, no. 6p1, pp. 1728
76. Wasserman, P.D.: Advanced methods in neural computing. New York, Nostrand Reinhold. (1993)
77. Watsuji, T., Arita, S., Shinohara, S., Kitade,T.: Medical Application of Fuzzy Theory to the Diagnostic System of Tongue Inspection in Traditional Chinese Medicine. IEEE International Fuzzy Systems Conference Proceedings. (1999) 145-148
78. Watt, S.N.K.: Naive Psychology and the Inverted Turing Test. Psychology, 7(14), 1996
79. Weizenbaum, J. Computer Power and Human Reason: From Judgment To Calculation, San Francisco: W. H. Freeman, 1976 ISBN 0-7167-0463-1
80. Weizenbaum, J.: ELIZA - A Computer Program for the Study of Natural Language Communication between Man and Machine, Communications of the Association for Computing Machinery 9 (1966): 36-45.
81. West, Brent W., Flikkema, Paul G., Sisk, Thomas, Koch, George W.: Wireless Sensor Networks for Dense Spatio-temporal Monitoring of the Environment: A Case for Integrated Circuit, System, and Network Design. Northern Arizona University.
82. White paper of The National Academy of Sciences. Exploring the digital divide: Charting the terrain of technology access and opportunity.
83. Wikipedia: Kevin Warwich, http://en.wikipedia.org/wiki/Kevin_Warwick
84. Williams, J. A., Dawood, A. S. and Visser, S. J.: FPGA-Based Cloud Detection for Real-Time Onboard Remote Sensing, IEEE ICFPT 2002, Hong Kong
85. Winston, R. (editor-in-chief): Human, DK Publishing, Inc. 2004
86. Wu, H., Siegel, M. and Khosla,P.: Vehicle Sound Signature Recognition by Frequency Principle Component Analysis. The Proceedings of IMTC 1998 , selected in the IEEE Transaction on Instrumentation and Measurement Vol. 48, No. 5, ISSN 0018-9456. October. (1999) 1005-1009
87. Wu, H., Siegel, M., Stiefelhagen, R., and Yang, J.: Sensor Fusion Using Dempster-Shafer Theory. The Proceedings of IMTC 2002. Anchorage, AK, USA, May 21-23.
88. Wyatt, Tristram D. (2003). Pheromones and Animal Behaviour: Communication by Smell and Taste. Cambridge: Cambridge University Press. ISBN 0521485266.
89. Xilinx Products, 2003
90. Xu, L., et al.: Segmentation of skin cancer images. Image and Vision Computing 17. (1999) 65-74
91. Yao, P.: Comparison of TCM Tongue Images with Gastroscopy Images. Shangdong S&T Publisher, ISBN 7-5331-1849-9. in Chinese. (1996)
92. Yu, Zhanshou: Feed-Forward Neural Network. 2005.
93. Zbibowski, R.: Fly like a fly, IEEE Spectrum, November, 2005
94. Zhang, E.: Diagnostics of Traditional Chinese Medicine. Publishing House of Shanghai University of Traditional Chinese Medicine, ISBN 7-81010-125-0. in both Chinese and English. (1990)
95. Zhao, Jerry, Govindan, Ramesh: Understanding Packet Delivery Performance In Dense Wireless Sensor Networks. University of Southern California Computer Science Department (2003)
96. Zhou, X.S., Rui, Y., and Huang, T.S. (2003): Exploration of Visual Data, Kluwer Academic Publishers