{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T15:35:52Z","timestamp":1765294552823,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2012,12,7]],"date-time":"2012-12-07T00:00:00Z","timestamp":1354838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An infrared ceiling sensor network system is reported in this study to realize behavior analysis and fall detection of a single person in the home environment. The sensors output multiple binary sequences from which we know the existence\/non-existence of persons under the sensors. The short duration averages of the binary responses are shown to be able to be regarded as pixel values of a top-view camera, but more advantageous in the sense of preserving privacy. Using the \u201cpixel values\u201d as features, support vector machine classifiers succeeded in recognizing eight activities (walking, reading, etc.) performed by five subjects at an average recognition rate of 80.65%. In addition, we proposed a martingale framework for detecting falls in this system. The experimental results showed that we attained the best performance of 95.14% (F1 value), the FAR of 7.5% and the FRR of 2.0%. This accuracy is not sufficient in general but surprisingly high with such low-level information. In summary, it is shown that this system has the potential to be used in the home environment to provide personalized services and to detect abnormalities of elders who live alone.<\/jats:p>","DOI":"10.3390\/s121216920","type":"journal-article","created":{"date-parts":[[2012,12,7]],"date-time":"2012-12-07T11:07:28Z","timestamp":1354878448000},"page":"16920-16936","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":65,"title":["Privacy-Preserved Behavior Analysis and Fall Detection by an Infrared Ceiling Sensor Network"],"prefix":"10.3390","volume":"12","author":[{"given":"Shuai","family":"Tao","sequence":"first","affiliation":[{"name":"Division of Computer Science, Hokkaido University, Kita 8 Nishi 5, Kita-ku, Sapporo 060-0808, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mineichi","family":"Kudo","sequence":"additional","affiliation":[{"name":"Division of Computer Science, Hokkaido University, Kita 8 Nishi 5, Kita-ku, Sapporo 060-0808, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hidetoshi","family":"Nonaka","sequence":"additional","affiliation":[{"name":"Division of Computer Science, Hokkaido University, Kita 8 Nishi 5, Kita-ku, Sapporo 060-0808, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,12,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1109\/34.868683","article-title":"W4: Real-Time surveillance of people and their activities","volume":"22","author":"Haritaoglu","year":"2000","journal-title":"IEEE Trans. Patt. Anal. Mach. Int"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.cviu.2004.02.005","article-title":"Video-Based event recognition: Activity representation and probabilistic recognition methods","volume":"96","author":"Hongeng","year":"2004","journal-title":"Comput. Vis. Image Understand"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1007\/978-3-642-23678-5_13","article-title":"Person Localization and Soft Authentication Using an Infrared Ceiling Sensor Network","volume":"6855","author":"Real","year":"2011","journal-title":"Computer Analysis of Images and Patterns"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/978-3-642-17832-0_15","article-title":"People Localization in a Camera Network Combining Background Subtraction and Scene-Aware Human Detection","volume":"6523","author":"Lee","year":"2011","journal-title":"Advances in Multimedia Modeling"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s10044-008-0119-9","article-title":"Soft authentication using an infrared ceiling sensor network","volume":"12","author":"Hosokawa","year":"2009","journal-title":"Pattern Anal. Appl"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Shankar, M., Burchett, J., Hao, Q., Guenther, B., and Brady, D. (2006). Human-Tracking systems using pyroelectric infrared detectors. Opt. Eng.","DOI":"10.1117\/1.2360948"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tao, S., Kudo, M., Nonaka, H., and Toyama, J. (2011, January 8\u201310). Recording the Activities of Daily Living Based on Person Localization Using an Infrared Ceiling Sensor Network. Kaohsiung, Taiwan.","DOI":"10.1109\/GRC.2011.6122673"},{"key":"ref_8","unstructured":"Noury, N. (2002, January 2\u20134). A Smart Sensor for the Remote Follow up of Activity and Fall Detection of the Elderly. Madison, WI, USA."},{"key":"ref_9","unstructured":"Jones, D. (2005). Report on Seniors\u2019 Falls in Canada [Electronic Resource], Division of Aging and Seniors."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.cviu.2006.08.002","article-title":"A survey of advances in vision-based human motion capture and analysis","volume":"104","author":"Moeslund","year":"2006","journal-title":"Comput. Vis. Image Understand"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1016\/j.imavis.2009.11.014","article-title":"A survey on vision-based human action recognition","volume":"28","author":"Poppe","year":"2010","journal-title":"Image Vision Comput"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"10873","DOI":"10.1016\/j.eswa.2012.03.005","article-title":"A review on vision techniques applied to human behaviour analysis for ambient-assisted living","volume":"39","author":"Chaaraoui","year":"2012","journal-title":"Expert Syst. Appl"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1007\/BF02351026","article-title":"Evaluation of a fall detector based on accelerometers: A pilot study","volume":"43","author":"Lindemann","year":"2005","journal-title":"Med. Biol. Eng. Comput"},{"key":"ref_14","unstructured":"Mathie, M., Basilakis, J., and Celler, B. (2001, January 25\u201328). A System for Monitoring Posture and Physical Activity Using Accelerometers. Istanbul, Turkey."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Prado, M., Reina-Tosina, J., and Roa, L. (2002, January 23\u201326). Distributed Intelligent Architecture for Falling Detection and Physical Activity Analysis in the Elderly. Houston, TX, USA.","DOI":"10.1109\/IEMBS.2002.1053088"},{"key":"ref_16","unstructured":"Diaz, A., Prado, M., Roa, L., Reina-Tosina, J., and S\u00e1nchez, G. (2004, January 1\u20135). Preliminary Evaluation of a Full-Time Falling Monitor for the Elderly. San Francisco, CA, USA."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kangas, M., Konttila, A., Winblad, I., and Jamsa, T. (2007, January 22\u201326). Determination of Simple Thresholds for Accelerometry-Based Parameters for Fall Detection. Lyon, France.","DOI":"10.1109\/IEMBS.2007.4352552"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.gaitpost.2006.09.012","article-title":"Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm","volume":"26","author":"Bourke","year":"2007","journal-title":"Gait Posture"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Tao, S., Kudo, M., and Nonaka, H. (2012, January 27). Privacy-Preserved Fall Detection by an Infrared Ceiling Sensor Network. Tokyo, Japan.","DOI":"10.3390\/s121216920"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.medengphy.2006.12.001","article-title":"A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor","volume":"30","author":"Bourke","year":"2008","journal-title":"Med. Eng. Phys"},{"key":"ref_21","unstructured":"Noury, N., Barralon, P., Virone, G., Boissy, P., Hamel, M., and Rumeau, P. (2003, January 17\u201321). A Smart Sensor Based on Rules and its Evaluation in Daily Routines. Cancun, Mexico."},{"key":"ref_22","unstructured":"Noury, N., Herv\u00e9, T., Rialle, V., Virone, G., Mercier, E., Morey, G., Moro, A., and Porcheron, T. (2000, January 12\u201314). Monitoring Behavior in Home Using a Smart Fall Sensor and Position Sensors. Lyon, France."},{"key":"ref_23","unstructured":"Rougier, C., Meunier, J., St-Arnaud, A., and Rousseau, J. (September, January 30). Monocular 3D Head Tracking to Detect Falls of Elderly People. New York, NY, USA."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Nait-Charif, H., and McKenna, S. (2004, January 23\u201326). Activity Summarisation and Fall Detection in a Supportive Home Environment. Cambridge, UK.","DOI":"10.1109\/ICPR.2004.1333768"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Williams, A., Ganesan, D., and Hanson, A. (2007, January 24\u201329). Aging in Place: Fall Detection and Localization in a Distributed Smart Camera Network. Augsburg, Germany.","DOI":"10.1145\/1291233.1291435"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1258\/1357633054068946","article-title":"An intelligent emergency response system: Preliminary development and testing of automated fall detection","volume":"11","author":"Lee","year":"2005","journal-title":"J. Telemed. Telecare"},{"key":"ref_27","unstructured":"Nonaka, H., Tao, S., Toyama, J., and Kudo, M. (2011, January 5\u20137). Ceiling Sensor Network for Soft Authentication and Person Tracking Using Equilibrium Line. Algarve, Portugal."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2113","DOI":"10.1109\/TPAMI.2010.48","article-title":"A martingale framework for detecting changes in data streams by testing exchangeability","volume":"32","author":"Ho","year":"2010","journal-title":"IEEE Trans. Patt. Anal. Mach. Int"},{"key":"ref_29","unstructured":"Vovk, V., Nouretdinov, I., and Gammerman, A. (2003, January 21\u201324). Testing Exchangeability On-Line. Washington, DC, USA."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Steele, J. (2000). Stochastic Calculus and Financial Applications, Springer-Verge.","DOI":"10.1007\/978-1-4684-9305-4"},{"key":"ref_31","first-page":"130","article-title":"The correlation of fall characteristics and hip fracture in community-dwelling stroke patients","volume":"2","author":"Wei","year":"2008","journal-title":"Taiwan Geriat. Gerontol"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/12\/12\/16920\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:54:07Z","timestamp":1760219647000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/12\/12\/16920"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,12,7]]},"references-count":31,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2012,12]]}},"alternative-id":["s121216920"],"URL":"https:\/\/doi.org\/10.3390\/s121216920","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2012,12,7]]}}}