164
Internet of Things (IoT)
Bagnasco, A., et al. (2011, October). Design, implementation and experimental evaluation of a wireless fall detector. In Proceedings of the 4th International Symposium on Applied Sciences in Biomedical
and Communication Technologies, p. 65. ACM, San Diego, CA.
Benghazi, K., et al. (2012), Enabling correct design and formal analysis of Ambient Assisted Living
systems. The Journal of Systems and Software 85: 498–510.
Botia, A. J., et al. (2012). Ambient assisted living system in home monitoring of healthy independent
elders. Expert Systems with Applications 39: 8136–8148.
Bourke, A. K., et al. (2010). Evaluation of waist-mounted tri-axial accelerometer based fall-detection
algorithms during scripted and continuous unscripted activities. Journal of Biomechanics 43(15):
3051–3057.
Chung, P. C., and Liu, C. D. (2008). A daily behavior enabled hidden Markov model for human
behavior understanding. Pattern Recognition 41(5): 1572–1580.
Ciuti, G., Ricotti, L., Menciassi, A., and Dario, P., (2015), MEMS Sensor Technologies for Human Centred
Applications in Health Care, Physical Activities, Safty and Environmental Sensing: A Review on
Research Activities in Italy, Sensors, 15, pp. 6441–6468. MDPI, Switzerland.
Cook, J. D., et al. (2009). Ambient intelligence: Technologies, applications and opportunities. Pervasive
and Mobile Computing 5: 277–298.
De Capua, C., et al. (2010). A smart ECG measurement system based on web-service-oriented architecture for telemedicine applications. IEEE Transactions on Instrumentation and Measurement
59(10): 2530–2538.
Demiris, G., Rantz, M. J., Aud, M. A., Marek, K. D.,Tyrer, H. W., Skubic, M., and Hussam, A. A.
(2004). Older adults attitude towards and perceptions of smart home technologies: A pilot
study, Medical Informatics and the Internet in Medicine 29(2): 87–94.
Demiris, G., et al. (2008). Senior residents’ perceived need of and preferences for “smart home”
sensor technologies. International Journal of Technology Assessment in Health Care 24(1): 120–124.
DOI: 10.1017/S0266462307080154.
Demiris, G., and Hensel, B. K. (2008). Technologies for an Aging Society: A systematic Review of
Smart Home Applications. IMIA Year Book of Medical Informatics 3: 33–40.
Doukas, C., and Maglogiannis, I. (2008, January). Advanced patient or elder fall detection based
on movement and sound data. In 2008 Second International Conference on Pervasive Computing
Technologies for Healthcare, pp. 103–107. IEEE, Piscataway, NJ.
Giansanti, D., et al. (2008). Toward the design of a wearable system for the remote monitoring of
epileptic crisis. Telemedicine and e-Health 14(10): 1130–1135.
Grassi, M., et al. (2010). A multisensor system for high reliability people fall detection in home environment. In P. Malcovati, A. Baschirotto, A. D`Amico and C. Natale (Eds.), Sensors and Microsystems.
and Vol. 54, Lecture Notes in Electrical Engineering, pp. 391–394. Springer, The Netherlands.
Hein, A., et al. (2009). A service oriented platform for health services and ambient assisted Living.
In Proceedings of the International Conference on Advanced Information Networking and Applications
Workshops, IEEE Computer Society, Washington, DC, pp. 531–537.
http://saviance.com/whitepapers/internet-health-industry
https://www.healthcatalyst.com/healthcare-analytics-best-practices
I.A. Group. (2001). Scenarios for Ambient Intelligence in 2010. European Commission, CORDIS, IST,
Belgium.
Ivanov, P., Nagoer, Z., Pshenokova, I., and Tokmakova, D. (2015). Forming the multi-modal situation
content in Ambient Intelligent Systems on the Basis of Self Organizing Cognitive architectures. In 5th World Congress on Information and Communication Technologies (WICT), Marrakesh Morocco, December 14–16, pp. 7–12.
Jakkula, V., et al. (2007). Knowledge discovery in entity based smart environment resident data using
temporal relations based data mining. In Proceeding of the ICDM Workshop on Spatial and Spatio—
Temporal Data Mining. IEEE, Piscataway, NJ.
Jalal, A., et al. (2011, June). Daily human activity recognition using depth silhouettes and mathcal {R}
transformation for smart home. In International Conference on Smart Homes and Health Telematics,
pp. 25–32. Springer, Berlin, Heidelberg.
Internet of Things (IoT)
Bagnasco, A., et al. (2011, October). Design, implementation and experimental evaluation of a wireless fall detector. In Proceedings of the 4th International Symposium on Applied Sciences in Biomedical
and Communication Technologies, p. 65. ACM, San Diego, CA.
Benghazi, K., et al. (2012), Enabling correct design and formal analysis of Ambient Assisted Living
systems. The Journal of Systems and Software 85: 498–510.
Botia, A. J., et al. (2012). Ambient assisted living system in home monitoring of healthy independent
elders. Expert Systems with Applications 39: 8136–8148.
Bourke, A. K., et al. (2010). Evaluation of waist-mounted tri-axial accelerometer based fall-detection
algorithms during scripted and continuous unscripted activities. Journal of Biomechanics 43(15):
3051–3057.
Chung, P. C., and Liu, C. D. (2008). A daily behavior enabled hidden Markov model for human
behavior understanding. Pattern Recognition 41(5): 1572–1580.
Ciuti, G., Ricotti, L., Menciassi, A., and Dario, P., (2015), MEMS Sensor Technologies for Human Centred
Applications in Health Care, Physical Activities, Safty and Environmental Sensing: A Review on
Research Activities in Italy, Sensors, 15, pp. 6441–6468. MDPI, Switzerland.
Cook, J. D., et al. (2009). Ambient intelligence: Technologies, applications and opportunities. Pervasive
and Mobile Computing 5: 277–298.
De Capua, C., et al. (2010). A smart ECG measurement system based on web-service-oriented architecture for telemedicine applications. IEEE Transactions on Instrumentation and Measurement
59(10): 2530–2538.
Demiris, G., Rantz, M. J., Aud, M. A., Marek, K. D.,Tyrer, H. W., Skubic, M., and Hussam, A. A.
(2004). Older adults attitude towards and perceptions of smart home technologies: A pilot
study, Medical Informatics and the Internet in Medicine 29(2): 87–94.
Demiris, G., et al. (2008). Senior residents’ perceived need of and preferences for “smart home”
sensor technologies. International Journal of Technology Assessment in Health Care 24(1): 120–124.
DOI: 10.1017/S0266462307080154.
Demiris, G., and Hensel, B. K. (2008). Technologies for an Aging Society: A systematic Review of
Smart Home Applications. IMIA Year Book of Medical Informatics 3: 33–40.
Doukas, C., and Maglogiannis, I. (2008, January). Advanced patient or elder fall detection based
on movement and sound data. In 2008 Second International Conference on Pervasive Computing
Technologies for Healthcare, pp. 103–107. IEEE, Piscataway, NJ.
Giansanti, D., et al. (2008). Toward the design of a wearable system for the remote monitoring of
epileptic crisis. Telemedicine and e-Health 14(10): 1130–1135.
Grassi, M., et al. (2010). A multisensor system for high reliability people fall detection in home environment. In P. Malcovati, A. Baschirotto, A. D`Amico and C. Natale (Eds.), Sensors and Microsystems.
and Vol. 54, Lecture Notes in Electrical Engineering, pp. 391–394. Springer, The Netherlands.
Hein, A., et al. (2009). A service oriented platform for health services and ambient assisted Living.
In Proceedings of the International Conference on Advanced Information Networking and Applications
Workshops, IEEE Computer Society, Washington, DC, pp. 531–537.
http://saviance.com/whitepapers/internet-health-industry
https://www.healthcatalyst.com/healthcare-analytics-best-practices
I.A. Group. (2001). Scenarios for Ambient Intelligence in 2010. European Commission, CORDIS, IST,
Belgium.
Ivanov, P., Nagoer, Z., Pshenokova, I., and Tokmakova, D. (2015). Forming the multi-modal situation
content in Ambient Intelligent Systems on the Basis of Self Organizing Cognitive architectures. In 5th World Congress on Information and Communication Technologies (WICT), Marrakesh Morocco, December 14–16, pp. 7–12.
Jakkula, V., et al. (2007). Knowledge discovery in entity based smart environment resident data using
temporal relations based data mining. In Proceeding of the ICDM Workshop on Spatial and Spatio—
Temporal Data Mining. IEEE, Piscataway, NJ.
Jalal, A., et al. (2011, June). Daily human activity recognition using depth silhouettes and mathcal {R}
transformation for smart home. In International Conference on Smart Homes and Health Telematics,
pp. 25–32. Springer, Berlin, Heidelberg.