{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:06:28Z","timestamp":1787029588144,"version":"build-2736575974"},"reference-count":81,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T00:00:00Z","timestamp":1628467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"College of Information Technology, United Arab Emirates University","award":["31T136"],"award-info":[{"award-number":["31T136"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The recent growth of the elderly population has led to the requirement for constant home monitoring as solitary living becomes popular. This protects older people who live alone from unwanted instances such as falling or deterioration caused by some diseases. However, although wearable devices and camera-based systems can provide relatively precise information about human motion, they invade the privacy of the elderly. One way to detect the abnormal behavior of elderly residents under the condition of maintaining privacy is to equip the resident\u2019s house with an Internet of Things system based on a non-invasive binary motion sensor array. We propose to concatenate external features (previous activity and begin time-stamp) along with extracted features with a bi-directional long short-term memory (Bi-LSTM) neural network to recognize the activities of daily living with a higher accuracy. The concatenated features are classified by a fully connected neural network (FCNN). The proposed model was evaluated on open dataset from the Center for Advanced Studies in Adaptive Systems (CASAS) at Washington State University. The experimental results show that the proposed method outperformed state-of-the-art models with a margin of more than 6.25% of the F1 score on the same dataset.<\/jats:p>","DOI":"10.3390\/s21165371","type":"journal-article","created":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T09:03:53Z","timestamp":1628499833000},"page":"5371","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Binary Sensors-Based Privacy-Preserved Activity Recognition of Elderly Living Alone Using an RNN"],"prefix":"10.3390","volume":"21","author":[{"given":"Tan-Hsu","family":"Tan","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, National Taipei University of Technology, Taipei 10617, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luubaatar","family":"Badarch","sequence":"additional","affiliation":[{"name":"Department of Electronics, School of Information and Communication Technology, Mongolian University of Science and Technology, Ulaanbaatar 13341, Mongolia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei-Xiang","family":"Zeng","sequence":"additional","affiliation":[{"name":"Wistron Corporation, Taipei 11469, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6613-7435","authenticated-orcid":false,"given":"Munkhjargal","family":"Gochoo","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, National Taipei University of Technology, Taipei 10617, Taiwan"},{"name":"Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al-Ain P.O. Box 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6102-3765","authenticated-orcid":false,"given":"Fady S.","family":"Alnajjar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al-Ain P.O. Box 15551, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun-Wei","family":"Hsieh","sequence":"additional","affiliation":[{"name":"College of AI, National Chiao Tung University, Hsinchu 30010, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,9]]},"reference":[{"key":"ref_1","unstructured":"United Nations Department of Economic and Social Affairs (2019). World Population Prospects 2019, United Nations."},{"key":"ref_2","unstructured":"Jean-Pierre, M., Lynn, B.B., Martin Finbarr, C., and Walston Jeremy, D. (2017). Population ageing in Europe. Oxford Textbook of Geriatric Medicine, Oxford University Press."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/S0140-6736(14)60569-9","article-title":"Causes of international increases in older age life expectancy","volume":"385","author":"Mathers","year":"2015","journal-title":"Lancet"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1257\/jep.20.3.97","article-title":"The determinants of mortality","volume":"20","author":"Cutler","year":"2006","journal-title":"J. Econ. Perspect."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1257\/jep.23.4.175","article-title":"Mortality inequality","volume":"23","author":"Peltzman","year":"2009","journal-title":"J. Econ. Perspect."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1080\/00324728.1975.10410201","article-title":"Population investigation committee the changing relation Between mortality and level of economic development","volume":"29","author":"Preston","year":"1975","journal-title":"Popul. Stud."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1017\/S0144686X19001818","article-title":"Interventions to improve the health and wellbeing of older people living alone: A mixed-methods systematic review of effectiveness and accessibility","volume":"41","author":"Johnstone","year":"2021","journal-title":"Ageing Soc."},{"key":"ref_8","first-page":"0046958018774177","article-title":"Social relationships and suicidal ideation among the elderly who live alone in Republic of Korea: A logistic model","volume":"55","author":"Kwon","year":"2018","journal-title":"Inq. J. Health Care Organ. Provis. Financ."},{"key":"ref_9","first-page":"582","article-title":"Loneliness, fear of falling, and quality of life in community-dwelling older women who live alone and live with others","volume":"43","author":"Zali","year":"2017","journal-title":"Educ. Gerontol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1080\/03071022.2017.1256093","article-title":"The rise of living alone and loneliness in history","volume":"42","author":"Snell","year":"2017","journal-title":"Soc. Hist."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1111\/padr.12149","article-title":"Living alone in later life: A global perspective","volume":"44","author":"Reher","year":"2018","journal-title":"Popul. Dev. Rev."},{"key":"ref_12","unstructured":"Stepler, R. (2017, January 07). Smaller Share of Women Ages 65 and Older Are Living Alone. Available online: http:\/\/www.pewsocialtrends.org\/2016\/02\/18\/smaller-share-of-women-ages-65-and-older-are-living-alone\/."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lee, S.M., and Edmonston, B. (2019). Living alone among older adults in Canada and the U.S. Healthcare, 7.","DOI":"10.3390\/healthcare7020068"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1017\/S1041610216001654","article-title":"Causes of nursing home placement for older people with dementia: A systematic review and meta-analysis","volume":"29","author":"Toot","year":"2017","journal-title":"Int. Psychogeriatr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1097\/PSY.0000000000000386","article-title":"Feelings of loneliness and living alone as predictors of mortality in the elderly: The PAQUID study","volume":"78","author":"Stoykova","year":"2016","journal-title":"Psychosom. Med."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Jokanovic, B., Amin, M., and Ahmad, F. (2016, January 2\u20136). Radar fall motion detection using deep learning. Proceedings of the 2016 IEEE Radar Conference (RadarConf), Philadelphia, PA, USA.","DOI":"10.1109\/RADAR.2016.7485147"},{"key":"ref_17","first-page":"71","article-title":"Human behaviour modelling for welfare technology using hidden Markov models","volume":"137","author":"Lysaker","year":"2019","journal-title":"Pattern Recognit. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.biosystemseng.2017.09.007","article-title":"Internet of things in agriculture, recent advances and future challenges","volume":"164","author":"Tzounis","year":"2017","journal-title":"Biosyst. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ansari, S., Aslam, T., Poncela, J., Otero, P., and Ansari, A. (2019). Internet of Things-Based Healthcare Applications, IGI Global.","DOI":"10.4018\/978-1-7998-1253-1.ch001"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1454","DOI":"10.1016\/j.jclepro.2016.10.006","article-title":"A review of internet of things for smart home: Challenges and solutions","volume":"140","author":"Trivodaliev","year":"2017","journal-title":"J. Clean. Prod."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1109\/MITP.2016.42","article-title":"The internet of things in healthcare: Potential applications and challenges","volume":"18","author":"Laplante","year":"2016","journal-title":"IT Prof."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"7192","DOI":"10.1109\/JIOT.2019.2915095","article-title":"Novel IoT-based privacy-preserving yoga posture recognition system using low-resolution infrared sensors and deep learning","volume":"6","author":"Gochoo","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Maskeliunas, R., Dama\u0161evicius, R., and Segal, S. (2019). A review of internet of things technologies for ambient assisted living environments. Futur. Internet, 11.","DOI":"10.3390\/fi11120259"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Padikkapparambil, J., Ncube, C., Singh, K.K., and Singh, A. (2020). Internet of Things technologies for elderly health-care applications. Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach, Academic Press.","DOI":"10.1016\/B978-0-12-819593-2.00008-X"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s10916-019-1365-7","article-title":"A systematic review of wearable sensors and IoT-based monitoring applications for older adults\u2014A focus on ageing population and independent living","volume":"43","author":"Baig","year":"2019","journal-title":"J. Med. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Khan, I., Amaro, A.C., and Oliveira, L. (2019, January 19\u201322). IoT-based systems for improving older adults\u2032 wellbeing: A systematic review. Proceedings of the 2019 14th Iberian Conference on Information Systems and Technologies (CISTI), Coimbra, Portugal.","DOI":"10.23919\/CISTI.2019.8760866"},{"key":"ref_27","first-page":"9302328","article-title":"Helping elderly users report pain levels: A study of user experience with mobile and wearable interfaces","volume":"2017","author":"Cajamarca","year":"2017","journal-title":"Mob. Inf. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wang, Z., Yang, Z., and Dong, T. (2017). A review of wearable technologies for elderly care that can accurately track indoor position, recognize physical activities and monitor vital signs in real time. Sensors, 17.","DOI":"10.3390\/s17020341"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Jalal, A., Quaid, M.A.K., and Hasan, A.S. (2018, January 17\u201319). Wearable sensor-based human behavior understanding and recognition in daily life for smart environments. Proceedings of the 2018 International Conference on Frontiers of Information Technology, FIT, Islamabad, Pakistan.","DOI":"10.1109\/FIT.2018.00026"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1007\/s11517-015-1357-9","article-title":"Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different","volume":"54","author":"Brodie","year":"2016","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"893816","DOI":"10.1155\/2017\/8934816","article-title":"Classification of daily activities for the elderly using wearable sensors","volume":"2017","author":"Liu","year":"2017","journal-title":"J. Healthc. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"8553","DOI":"10.1109\/JIOT.2019.2920283","article-title":"IoT wearable sensor and deep learning: An integrated approach for personalized human activity recognition in a smart home environment","volume":"6","author":"Bianchi","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1080\/0144929X.2015.1114145","article-title":"Users\u2032 psychological perception and perceived readability of wearable devices for elderly people","volume":"35","author":"Fang","year":"2016","journal-title":"Behav. Inf. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"\u00d6zdemir, A.T. (2016). An analysis on sensor locations of the human body for wearable fall detection devices: Principles and practice. Sensors, 16.","DOI":"10.3390\/s16081161"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"11","DOI":"10.2147\/PPA.S119177","article-title":"Involvement of the end user: Exploration of older people\u2032s needs and preferences for a wearable fall detection device\u2013A qualitative descriptive study","volume":"11","author":"Thilo","year":"2017","journal-title":"Patient Prefer. Adherence"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"24681","DOI":"10.1007\/s11042-018-7134-7","article-title":"Remote health monitoring of elderly through wearable sensors","volume":"78","author":"Baker","year":"2019","journal-title":"Multimed. Tools Appl."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e0183989","DOI":"10.1371\/journal.pone.0183989","article-title":"Wearable sensors objectively measure gait parameters in Parkinson\u2032s disease","volume":"12","author":"Schlachetzki","year":"2017","journal-title":"PLoS ONE"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.patrec.2019.03.016","article-title":"Positive technology for elderly well-being: A review","volume":"137","author":"Grossi","year":"2019","journal-title":"Pattern Recognit. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.cmpb.2017.10.008","article-title":"The usefulness and actual use of wearable devices among the elderly population","volume":"153","author":"Kekade","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_40","first-page":"e9832","article-title":"The use of wearable activity trackers among older adults: Focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change","volume":"7","author":"Kononova","year":"2019","journal-title":"J. Med. Internet Res."},{"key":"ref_41","unstructured":"Habibipour, A., Padyab, A., and St\u00e5hlbr\u00f6st, A. (2019, January 15\u201317). Social, ethical and ecological issues in wearable technologies. Proceedings of the 25th Americas Conference on Information Systems, Cancun, Mexico."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Papagiannaki, A., Zacharaki, E.I., Kalouris, G., Kalogiannis, S., Deltouzos, K., Ellul, J., and Megalooikonomou, V. (2019). Recognizing physical activity of older people from wearable sensors and inconsistent data. Sensors, 19.","DOI":"10.3390\/s19040880"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.eswa.2018.03.056","article-title":"Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges","volume":"105","author":"Nweke","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1007\/s10916-018-0948-z","article-title":"Human activity recognition from body sensor data using deep learning","volume":"42","author":"Hassan","year":"2018","journal-title":"J. Med. Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"4528","DOI":"10.1109\/JSEN.2019.2898891","article-title":"Activity-aware fall detection and recognition based on wearable sensors","volume":"19","author":"Hussain","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.image.2017.01.005","article-title":"Efficient motion estimation methods for fast recognition of activities of daily living","volume":"53","author":"Poularakis","year":"2017","journal-title":"Signal Process. Image Commun."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/978-3-540-92781-5_4","article-title":"Monitoring activities of daily living (ADLs) of elderly based on 3D key human postures","volume":"5329","author":"Zouba","year":"2008","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Gabrielli, M., Leo, P., Renzi, F., and Bergamaschi, S. (2019, January 19\u201321). Action recognition to estimate Activities of Daily Living (ADL) of elderly people. Proceedings of the 2019 IEEE 23rd International Symposium on Consumer Technologies (ISCT), Ancona, Italy.","DOI":"10.1109\/ISCE.2019.8900995"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.patrec.2020.04.031","article-title":"Real time human action recognition using triggered frame extraction and a typical CNN heuristic","volume":"135","author":"Mishra","year":"2020","journal-title":"Pattern Recognit. Lett."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1109\/JBHI.2018.2808281","article-title":"Deep learning for fall detection: Three-dimensional CNN Combined with LSTM on video kinematic data","volume":"23","author":"Lu","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1049\/iet-cvi.2017.0062","article-title":"Skeleton-based human activity recognition for elderly monitoring systems","volume":"12","author":"Hbali","year":"2017","journal-title":"IET Comput. Vis."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Park, Y.J., Ro, H., Lee, N.K., and Han, T.D. (2019). Deep-cARe: Projection-based home care augmented reality system with deep learning for elderly. Appl. Sci., 9.","DOI":"10.3390\/app9183897"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"13583","DOI":"10.1007\/s10586-018-2010-9","article-title":"Posture based health monitoring and unusual behavior recognition system for elderly using dynamic Bayesian network","volume":"22","author":"Anitha","year":"2019","journal-title":"Clust. Comput."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Caine, K., \u015cabanovi\u0107, S., and Carter, M. (2012, January 5\u20138). The effect of monitoring by cameras and robots on the privacy enhancing behaviors of older adults. Proceedings of the HRI\u203212-Proceedings of the 7th Annual ACM\/IEEE International Conference on Human-Robot Interaction, Boston, MA, USA.","DOI":"10.1145\/2157689.2157807"},{"key":"ref_55","first-page":"390","article-title":"Device-free non-privacy invasive classification of elderly travel patterns in a smart house using PIR sensors and DCNN","volume":"18","author":"Gochoo","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"428","DOI":"10.4017\/gt.2013.11.3.001.00","article-title":"Willingness of older adults to share data and privacy concerns after exposure to unobtrusive home monitoring","volume":"11","author":"Boise","year":"2013","journal-title":"Gerontechnology"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"041003","DOI":"10.1117\/1.JEI.25.4.041003","article-title":"Behavior analysis for elderly care using a network of low-resolution visual sensors","volume":"25","author":"Eldib","year":"2016","journal-title":"J. Electron. Imaging"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Gochoo, M., Tan, T.H., Batjargal, T., Seredin, O., and Huang, S.C. (2018, January 7\u201310). Device-free non-privacy invasive indoor human posture recognition using low-resolution infrared sensor-based wireless sensor networks and DCNN. Proceedings of the Proceedings-2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC, Miyazaki, Japan.","DOI":"10.1109\/SMC.2018.00397"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1007\/s42835-018-00012-w","article-title":"Depth maps-based human segmentation and action recognition using full-body plus body color cues via recognizer engine","volume":"14","author":"Jalal","year":"2019","journal-title":"J. Electr. Eng. Technol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2567","DOI":"10.1007\/s42835-019-00278-8","article-title":"Vision-based human activity recognition system using depth silhouettes: A smart home system for monitoring the residents","volume":"14","author":"Kim","year":"2019","journal-title":"J. Electr. Eng. Technol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s12652-016-0412-1","article-title":"Towards improving feature extraction and classification for activity recognition on streaming data","volume":"8","author":"Yala","year":"2017","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_62","first-page":"693","article-title":"Unobtrusive activity recognition of elderly people living alone using anonymous binary sensors and DCNN","volume":"23","author":"Gochoo","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Susnea, I., Dumitriu, L., Talmaciu, M., Pecheanu, E., and Munteanu, D. (2019). Unobtrusive monitoring the daily activity routine of elderly people living alone, with low-cost binary sensors. Sensors, 19.","DOI":"10.3390\/s19102264"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.pmcj.2012.07.003","article-title":"Activity recognition on streaming sensor data","volume":"10","author":"Krishnan","year":"2014","journal-title":"Pervasive Mob. Comput."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Diraco, G., Leone, A., and Siciliano, P. (2017). A radar-based smart sensor for unobtrusive elderly monitoring in ambient assisted living applications. Biosensors, 7.","DOI":"10.20944\/preprints201710.0115.v1"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"5460","DOI":"10.3390\/s130505460","article-title":"Activity recognition using hybrid generative\/discriminative models on home environments using binary sensors","volume":"13","author":"Sanchis","year":"2013","journal-title":"Sensors"},{"key":"ref_67","first-page":"1","article-title":"Key feature identification for recognition of activities performed by a smart-home resident","volume":"11","author":"Tahir","year":"2019","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.patrec.2018.02.010","article-title":"Deep learning for sensor-based activity recognition: A survey","volume":"119","author":"Wang","year":"2019","journal-title":"Pattern Recognit. Lett."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"111012","DOI":"10.1109\/ACCESS.2019.2933994","article-title":"Predicting sensor events, activities, and time of occurrence using binary sensor data from homes with older adults","volume":"7","author":"Casagrande","year":"2019","journal-title":"IEEE Access"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.procs.2017.06.121","article-title":"Activity recognition and abnormal behaviour detection with recurrent neural networks","volume":"110","author":"Arifoglu","year":"2017","journal-title":"Procedia Comput. Sci."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Guo, J., Li, Y., Hou, M., Han, S., and Ren, J. (2020). Recognition of daily activities of two residents in a smart home based on time clustering. Sensors, 20.","DOI":"10.3390\/s20051457"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"7575","DOI":"10.1109\/JSEN.2019.2915026","article-title":"Activity recognition using binary sensors for elderly people living alone: Scanpath trend analysis approach","volume":"19","author":"Yatbaz","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_73","unstructured":"Singh, D., Merdivan, E., Psychoula, I., Kropf, J., Hanke, S., Geist, M., and Holzinger, A. (September, January 29). Human activity recognition using recurrent neural networks. Proceedings of the International Cross-Domain Conference for Machine Learning and Knowledge Extraction, Regio, Italy."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1975","DOI":"10.1007\/s10462-019-09724-5","article-title":"Non-intrusive human activity recognition and abnormal behavior detection on elderly people: A review","volume":"53","author":"Lentzas","year":"2020","journal-title":"Artif. Intell. Rev."},{"key":"ref_75","first-page":"1","article-title":"Learning setting-generalized activity models for smart spaces","volume":"99","author":"Cook","year":"2010","journal-title":"IEEE Intell. Syst."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/MC.2012.328","article-title":"CASAS: A smart home in a box","volume":"46","author":"Cook","year":"2012","journal-title":"Computer"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"2933","DOI":"10.1109\/TCSVT.2017.2764868","article-title":"Activity recognition in sensor data streams for active and assisted living environments","volume":"28","author":"MacHot","year":"2017","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"MacHot, F.A., Ranasinghe, S., Plattner, J., and Jnoub, N. (2018, January 19\u201323). Human activity recognition based on real life scenarios. Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, (PerCom Workshops), Athens, Greece.","DOI":"10.1109\/PERCOMW.2018.8480138"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Gochoo, M., Tan, T.H., Huang, S.C., Liu, S.H., and Alnajjar, F.S. (2017, January 21\u201323). DCNN-based elderly activity recognition using binary sensors. Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Ras Al Khaimah, United Arab Emirates.","DOI":"10.1109\/ICECTA.2017.8252040"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/MIE.2017.2703603","article-title":"Wireless high-performance communications: The challenges and opportunities of a new target","volume":"11","author":"Pang","year":"2017","journal-title":"IEEE Ind. Electron. Mag."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: Synthetic minority over-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artif. Intell. Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5371\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:42:56Z","timestamp":1760164976000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5371"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,9]]},"references-count":81,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["s21165371"],"URL":"https:\/\/doi.org\/10.3390\/s21165371","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,9]]}}}