Distributed Computing and Monitoring Technologies for Older Patients
暂无分享,去创建一个
Thomas B. Moeslund | Kamal Nasrollahi | Volker Krüger | Erika G. Spaich | Juris Klonovs | Mohammad A. Haque | Karen Andersen-Ranberg | V. Krüger | T. Moeslund | Kamal Nasrollahi | E. Spaich | K. Andersen-Ranberg | M. A. Haque | Juris Klonovs
[1] A. Fleury,et al. Sound and speech detection and classification in a Health Smart Home , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[2] J. Dartigues,et al. Prevalence, awareness, treatment, and control of hypertension in the elderly: the Three City study , 2006, Journal of hypertension.
[3] Rajesh Kannan Megalingam,et al. Assistive Technology for Elders: Wireless Intelligent Healthcare Gadget , 2011, 2011 IEEE Global Humanitarian Technology Conference.
[4] F. Lorussi,et al. Textile-Based Electrogoniometers for Wearable Posture and Gesture Capture Systems , 2009, IEEE Sensors Journal.
[5] Lawrence B. Wolff,et al. Quantitative measurement of illumination invariance for face recognition using thermal infrared imagery , 2003, SPIE Optics + Photonics.
[6] N. Kubota,et al. Remote monitoring and control using smart phones and sensor networks , 2012, The 1st IEEE Global Conference on Consumer Electronics 2012.
[7] Oscar Gama,et al. Electronics in Medicine , 2011 .
[8] Gert Cauwenberghs,et al. Non-contact Low Power EEG/ECG Electrode for High Density Wearable Biopotential Sensor Networks , 2009, 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks.
[9] Z. Ignjatovic,et al. A Motion-Tracking Ultrasonic Sensor Array for Behavioral Monitoring , 2012, IEEE Sensors Journal.
[10] Misha Pavel,et al. SVM to detect the presence of visitors in a smart home environment , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[11] T. Juárez-Cedillo,et al. Anthropometric measures and nutritional status in a healthy elderly population , 2007, BMC public health.
[12] Zhongming Zhao,et al. Machine learning-based prediction of drug-drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties. , 2014, Journal of the American Medical Informatics Association : JAMIA.
[13] Gert Cauwenberghs,et al. Wireless Non-contact EEG/ECG Electrodes for Body Sensor Networks , 2010, 2010 International Conference on Body Sensor Networks.
[14] K. Crowley,et al. Sleep and Sleep Disorders in Older Adults , 2011, Neuropsychology Review.
[15] Tuomas Virtanen,et al. Acoustic event detection in real life recordings , 2010, 2010 18th European Signal Processing Conference.
[16] K W Sum,et al. Vital sign monitoring for elderly at home: development of a compound sensor for pulse rate and motion. , 2005, Studies in health technology and informatics.
[17] Diane J. Cook,et al. Handling Class Overlap and Imbalance to Detect Prompt Situations in Smart Homes , 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.
[18] Bruce H Dobkin,et al. The Promise of mHealth , 2011, Neurorehabilitation and neural repair.
[19] Y.T. Zhang,et al. Wearable medical devices for tele-home healthcare , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[20] Karen L. Courtney,et al. Defining Obtrusiveness in Home Telehealth Technologies , 2006 .
[21] M. Tinetti,et al. A population-based study of environmental hazards in the homes of older persons. , 1999, American journal of public health.
[22] S. Khawandi,et al. Applying Machine Learning Algorithm in Fall Detection Monitoring System , 2013, 2013 5th International Conference on Computational Intelligence and Communication Networks.
[23] Raymond L. Watrous,et al. A patient-adaptive neural network ECG patient monitoring algorithm , 1995, Computers in Cardiology 1995.
[24] Michael Marschollek,et al. Sensors vs. experts - A performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients , 2011, BMC Medical Informatics Decis. Mak..
[25] Xingshe Zhou,et al. Managing Elders’ Wandering Behavior Using Sensors-based Solutions: A Survey , 2014 .
[26] Heinz Jäckel,et al. SPEEDY:a fall detector in a wrist watch , 2003, Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings..
[27] S. Duun,et al. A wearable “electronic patch” for wireless continuous monitoring of chronically diseased patients , 2008, 2008 5th International Summer School and Symposium on Medical Devices and Biosensors.
[28] Matjaz Gams,et al. An Agent-Based Approach to Care in Independent Living , 2010, AmI.
[29] Yi Yang,et al. Learning to predict health status of geriatric patients from observational data , 2012, 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).
[30] A. Oguz KANSIZ,et al. Selection of Time-Domain Features for Fall Detection Based on Supervised Learning , .
[31] Ying Zhang,et al. Real-Time Development of Patient-Specific Alarm Algorithms for Critical Care , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[32] William R. Shankle,et al. Methods to improve the detection of mild cognitive impairment. , 2005 .
[33] P. Payne,et al. Environmental Conditions and Body Temperatures of Elderly Women Living Alone or in Local Authority Home , 1971, British medical journal.
[34] A M Jette,et al. The disablement process. , 1994, Social science & medicine.
[35] Alex Mihailidis,et al. A Survey on Ambient-Assisted Living Tools for Older Adults , 2013, IEEE Journal of Biomedical and Health Informatics.
[36] Kejun Wang,et al. Video-Based Abnormal Human Behavior Recognition—A Review , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[37] B. Celler,et al. Evaluation of PIR Detector Characteristics for Monitoring Occupancy Patterns of Elderly People Living Alone at Home , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[38] G. Stergiou,et al. Can validated wrist devices with position sensors replace arm devices for self-home blood pressure monitoring? A randomized crossover trial using ambulatory monitoring as reference. , 2008, American journal of hypertension.
[39] Jacques Demongeot,et al. Multi-sensors acquisition, data fusion, knowledge mining and alarm triggering in health smart homes for elderly people. , 2002, Comptes rendus biologies.
[40] Massoud Pedram,et al. Durability of Wireless Networks of Battery-Powered Devices , 2009, 2009 6th IEEE Consumer Communications and Networking Conference.
[41] D. Cook,et al. Smart Home-Based Health Platform for Behavioral Monitoring and Alteration of Diabetes Patients , 2009, Journal of diabetes science and technology.
[42] George Demiris,et al. Framing the evidence for health smart homes and home-based consumer health technologies as a public health intervention for independent aging: A systematic review , 2013, Int. J. Medical Informatics.
[43] Chris D. Nugent,et al. Towards developing effective Continence Management through wetness alert diaper: Experiences, lessons learned, challenges and future directions , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.
[44] S. Yarows,et al. Comparison of the Omron HEM-637 wrist monitor to the auscultation method with the wrist position sensor on or disabled. , 2004, American journal of hypertension.
[45] S. Shankar Sastry,et al. Physical Activity Monitoring for Assisted Living at Home , 2007, BSN.
[46] Joel J. P. C. Rodrigues,et al. An ambient assisted living framework for mobile environments , 2014, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).
[47] Paulo Novais,et al. Sensor-driven agenda for intelligent home care of the elderly , 2012, Expert Syst. Appl..
[48] J L Kelsey,et al. Home hazards and falls in the elderly: the role of health and functional status. , 1995, American journal of public health.
[49] Aboul Ella Hassanien,et al. Deep Belief Network for clustering and classification of a continuous data , 2010, The 10th IEEE International Symposium on Signal Processing and Information Technology.
[50] Igor Kononenko,et al. Machine learning for medical diagnosis: history, state of the art and perspective , 2001, Artif. Intell. Medicine.
[51] William C. Mann,et al. The Gator Tech Smart House: a programmable pervasive space , 2005, Computer.
[52] Qiang Ji,et al. Knowledge Based Activity Recognition with Dynamic Bayesian Network , 2010, ECCV.
[53] Thomas F Budinger,et al. Biomonitoring with wireless communications. , 2003, Annual review of biomedical engineering.
[54] Chad A. Phipps,et al. CareWatch: A Home Monitoring System for Use in Homes of Persons With Cognitive Impairment , 2007, Topics in geriatric rehabilitation.
[55] Hyokyoung Grace Hong,et al. Prediction of Functional Status for the Elderly Based on a New Ordinal Regression Model , 2010 .
[56] Fariba Sadri,et al. Ambient intelligence: A survey , 2011, CSUR.
[57] Arnold Baca,et al. Accuracy of an UWB-based position tracking system used for time-motion analyses in game sports , 2014, European journal of sport science.
[58] G. Delhomme,et al. Wearable Medical Devices Using Textile and Flexible Technologies for Ambulatory Monitoring , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.
[59] H. Krumholz,et al. Telemonitoring in patients with heart failure. , 2010, The New England journal of medicine.
[60] Chiew Tong Lau,et al. Automated detection of wandering patterns in people with dementia , 2014 .
[61] Mohanraj Karunanithi,et al. Monitoring technology for the elderly patient , 2007, Expert review of medical devices.
[62] Laurence T. Yang,et al. A ubiquitous smart home for elderly , 2008, Inf. Syst. Frontiers.
[63] Dermot Diamond,et al. Textile sensors to measure sweat pH and sweat-rate during exercise , 2009, 2009 3rd International Conference on Pervasive Computing Technologies for Healthcare.
[64] K. H. Namazi,et al. Assisted Living: Current Issues in Facility Management and Resident Care , 2000 .
[65] Joshua R. Smith,et al. RFID-based techniques for human-activity detection , 2005, Commun. ACM.
[66] Héctor Pomares,et al. Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition , 2014, Sensors.
[67] B. Bloem,et al. Neurological gait disorders in elderly people: clinical approach and classification , 2007, The Lancet Neurology.
[68] Hongnian Yu,et al. Elderly activities recognition and classification for applications in assisted living , 2013, Expert Syst. Appl..
[69] Evangelos E. Milios,et al. Detection of daily living activities using a two-stage Markov model , 2013, J. Ambient Intell. Smart Environ..
[70] Marc Garbey,et al. Contact-Free Measurement of Cardiac Pulse Based on the Analysis of Thermal Imagery , 2007, IEEE Transactions on Biomedical Engineering.
[71] D. Kerrigan,et al. Mobility and Gait Assessment Technologies , 2008 .
[72] Wan-Young Chung,et al. A Fusion Health Monitoring Using ECG and Accelerometer sensors for Elderly Persons at Home , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[73] J. Baeyens,et al. European working group on sarcopenia in older people. Sarcopenia: European consensus on definition and diagnosis: report of the European working group on sarcopenia in older people , 2010 .
[74] Monique Frize,et al. Preliminary results on the effect of sensor position on unobtrusive rollover detection for sleep monitoring in smart homes , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[75] Michel Vacher,et al. First steps in data fusion between a multichannel audio acquisition and an information system for home healthcare , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).
[76] P. Rubel,et al. A neural network approach for patient-specific 12-lead ECG synthesis in patient monitoring environments , 2004, Computers in Cardiology, 2004.
[77] Jens Haueisen,et al. Impedance pneumography using textile electrodes , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[78] E. Kovacs,et al. Clinical Interventions in Aging Dovepress the Aging Lung , 2022 .
[79] M. Alwan,et al. A Smart and Passive Floor-Vibration Based Fall Detector for Elderly , 2006, 2006 2nd International Conference on Information & Communication Technologies.
[80] Lawrence B. Holder,et al. Conditional random fields for activity recognition in smart environments , 2010, IHI.
[81] Daqing Zhang,et al. Unobtrusive Sleep Posture Detection for Elder-Care in Smart Home , 2010, ICOST.
[82] William C. Mann,et al. Use of Currently Available Smart Home Technology by Frail Elders: Process and Outcomes , 2007 .
[83] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[84] Raymond Y. W. Lee,et al. Detection of falls using accelerometers and mobile phone technology. , 2011, Age and ageing.
[85] J. Soriano,et al. A home telehealth program for patients with severe COPD: the PROMETE study. , 2014, Respiratory medicine.
[86] R. Harikumar,et al. Analysis of SVD Neural Networks for Classification of Epilepsy Risk Level from EEG Signals , 2013 .
[87] Dayou Liu,et al. A Computer Aided Diagnosis System for Thyroid Disease Using Extreme Learning Machine , 2012, Journal of Medical Systems.
[88] AM Sullivan,et al. Reconstruction of missing physiological signals using artificial neural networks , 2010, 2010 Computing in Cardiology.
[89] Mohanraj Karunanithi,et al. Australian Community Care Experience on the Design, Development, Deployment and Evaluation of Implementing the Smarter Safer Homes Platform , 2015, ICOST.
[90] T. Masud,et al. Epidemiology of falls. , 2001, Age and ageing.
[91] Toshiyo Tamura,et al. Home geriatric physiological measurements , 2012, Physiological measurement.
[92] Floris H. P. van Velden,et al. The organizational and clinical impact of integrating bedside equipment to an information system: A systematic literature review of patient data management systems (PDMS) , 2015, Int. J. Medical Informatics.
[93] H. Olesen,et al. ID Proof on the Go: Development of a Mobile EEG-Based Biometric Authentication System , 2012, IEEE Vehicular Technology Magazine.
[94] Gabriel Gold,et al. Older patients in the emergency department: a review. , 2010, Annals of emergency medicine.
[95] M. Pacelli,et al. Textile Piezoresistive Sensors for Biomechanical Variables Monitoring , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.
[96] Onur Dikmen,et al. Sound event detection using non-negative dictionaries learned from annotated overlapping events , 2013, 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.
[97] Natalia A. Schmid,et al. Near real-time face detection and recognition using a wireless camera network , 2012, Defense + Commercial Sensing.
[98] Dean Cvetkovic,et al. Cross-correlation of EEG frequency bands and heart rate variability for sleep apnoea classification , 2010, Medical & Biological Engineering & Computing.
[99] Andreas Krause,et al. Robust, low-cost, non-intrusive sensing and recognition of seated postures , 2007, UIST.
[100] Eva Reviriego,et al. Impact of telemonitoring home care patients with heart failure or chronic lung disease from primary care on healthcare resource use (the TELBIL study randomised controlled trial) , 2013, BMC Health Services Research.
[101] Fabien Cardinaux,et al. Video based technology for ambient assisted living: A review of the literature , 2011, J. Ambient Intell. Smart Environ..
[102] M. Obayya,et al. Data fusion for heart diseases classification using multi-layer feed forward neural network , 2008, 2008 International Conference on Computer Engineering & Systems.
[103] Pieter P. Jonker,et al. The Potential of Socially Assistive Robotics in Care for Elderly, a Systematic Review , 2010, HRPR.
[104] Fillia Makedon,et al. Automatic sensor placement in a 3D volume , 2009, PETRA '09.
[105] Martina Ziefle,et al. Future Care Floor: A Sensitive Floor for Movement Monitoring and Fall Detection in Home Environments , 2010, MobiHealth.
[106] G. Demiris,et al. Technologies for an Aging Society: A Systematic Review of “Smart Home” Applications , 2008, Yearbook of Medical Informatics.
[107] Didier Stricker,et al. Creating and benchmarking a new dataset for physical activity monitoring , 2012, PETRA '12.
[108] Christophe Kunze,et al. Introducing a low-cost ambient monitoring system for activity recognition , 2011, 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.
[109] Yong-Tae Kim,et al. A 24-hour health monitoring system in a smart house , 2008 .
[110] Jens Juul Holst,et al. Automated detection of hypoglycemia-induced EEG changes recorded by subcutaneous electrodes in subjects with type 1 diabetes--the brain as a biosensor. , 2010, Diabetes research and clinical practice.
[111] Suresh R. Devasahayam,et al. A Sensorized Glove and Ball for Monitoring Hand Rehabilitation Therapy in Stroke Patients , 2013, 2013 Texas Instruments India Educators' Conference.
[112] Jenq-Neng Hwang,et al. A Review on Video-Based Human Activity Recognition , 2013, Comput..
[113] F. C. Tian,et al. A Novel Cost-Effective Portable Electronic Nose for Indoor-/In-Car Air Quality Monitoring , 2012, 2012 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring.
[114] Shyamal Patel,et al. A review of wearable sensors and systems with application in rehabilitation , 2012, Journal of NeuroEngineering and Rehabilitation.
[115] Zhenbang Gong,et al. A novel modeling approach to fall detection and experimental validation using motion capture system , 2013, 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO).
[116] Matjaz Gams,et al. Analysis of daily-living dynamics , 2012, J. Ambient Intell. Smart Environ..
[117] Stephen J. McKenna,et al. Summarising contextual activity and detecting unusual inactivity in a supportive home environment , 2004, Pattern Analysis and Applications.
[118] Roderick Murray-Smith,et al. Hierarchical Gaussian process mixtures for regression , 2005, Stat. Comput..
[119] Y. Higashi,et al. An unconstrained monitoring system for home rehabilitation , 2005, IEEE Engineering in Medicine and Biology Magazine.
[120] Ioannis T. Pavlidis,et al. Thermistor at a Distance: Unobtrusive Measurement of Breathing , 2010, IEEE Transactions on Biomedical Engineering.
[121] Young-Koo Lee,et al. Semi-Markov conditional random fields for accelerometer-based activity recognition , 2010, Applied Intelligence.
[122] J.K. Aggarwal,et al. Human activity analysis , 2011, ACM Comput. Surv..
[123] F. Jakab,et al. Unobtrusive anomaly detection in presence of elderly in a smart-home environment , 2012, 2012 ELEKTRO.
[124] C. Schmidtke,et al. Effect of postoperative delirium on quality of life and daily activities 6 month after elective cardiac surgery in the elderly , 2013 .
[125] Yasir Malik,et al. PhonAge: Adapted SmartPhone for Aging Population , 2013, ICOST.
[126] Beriliu Ilie. Portable equipment for monitoring human functional parameters , 2010, 9th RoEduNet IEEE International Conference.
[127] David A. Clifton,et al. Gaussian Processes for Personalized e-Health Monitoring With Wearable Sensors , 2013, IEEE Transactions on Biomedical Engineering.
[128] Mark Hasegawa-Johnson,et al. Acoustic fall detection using Gaussian mixture models and GMM supervectors , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[129] D. Gavin-Dreschnack,et al. Mapping the maze of terms and definitions in dementia-related wandering , 2007, Aging & mental health.
[130] Gamze Uslu,et al. A Bayesian approach for indoor human activity monitoring , 2011, 2011 11th International Conference on Hybrid Intelligent Systems (HIS).
[131] Xinguo Yu. Approaches and principles of fall detection for elderly and patient , 2008, HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services.
[132] Michael L. Littman,et al. Activity Recognition from Accelerometer Data , 2005, AAAI.
[133] D. Mack,et al. Sleep and Sleep Assessment Technologies , 2008 .
[134] Rafik A. Goubran,et al. Measurements of Sit-to-Stand Timing and Symmetry From Bed Pressure Sensors , 2011, IEEE Transactions on Instrumentation and Measurement.
[135] T. Lüscher,et al. Accuracy of a new wrist cuff oscillometric blood pressure device: comparisons with intraarterial and mercury manometer measurements. , 1998, American journal of hypertension.
[136] Md. Atiqur Rahman Ahad,et al. Action dataset — A survey , 2011, SICE Annual Conference 2011.
[137] Konrad Paul Kording,et al. Fall Classification by Machine Learning Using Mobile Phones , 2012, PloS one.
[138] C. N. Scanaill,et al. A Review of Approaches to Mobility Telemonitoring of the Elderly in Their Living Environment , 2006, Annals of Biomedical Engineering.
[139] Miao Yu,et al. A Posture Recognition-Based Fall Detection System for Monitoring an Elderly Person in a Smart Home Environment , 2012, IEEE Transactions on Information Technology in Biomedicine.
[140] Andrew Sixsmith,et al. The Nature and Use of Surveillance Technologies in Residential Care , 2013, ICOST.
[141] Diane J. Cook,et al. CASAS: A Smart Home in a Box , 2013, Computer.
[142] D. B. Keenan,et al. Delays in Minimally Invasive Continuous Glucose Monitoring Devices: A Review of Current Technology , 2009, Journal of diabetes science and technology.
[143] T. Murphy,et al. The course of disability before and after a serious fall injury. , 2013, JAMA internal medicine.
[144] Bogdan Pogorelc,et al. Discovering the Chances of Health Problems and Falls in the Elderly Using Data Mining , 2013 .
[145] Michel Vacher,et al. SVM-Based Multimodal Classification of Activities of Daily Living in Health Smart Homes: Sensors, Algorithms, and First Experimental Results , 2010, IEEE Transactions on Information Technology in Biomedicine.
[146] A. Akça,et al. COMORBID DISEASES AND DRUG USAGE AMONG GERIATRIC PATIENTS PRESENTING WITH NEUROLOGICAL PROBLEMS AT THE EMERGENCY DEPARTMENT , 2012 .
[147] Jiankang Wu,et al. Body sensor networks for ubiquitous healthcare , 2011 .
[148] J. Broekens,et al. Assistive social robots in elderly care: a review , 2009 .
[149] Qi Zhang,et al. Understanding Link Behavior of Non-intrusive Wireless Body Sensor Networks , 2012, Wirel. Pers. Commun..
[150] Patricia Martín-Rodilla,et al. A New Adaptive Algorithm for Detecting Falls through Mobile Devices , 2011, PAAMS.
[151] Z. Andersen,et al. An indoor air filtration study in homes of elderly: cardiovascular and respiratory effects of exposure to particulate matter , 2013, Environmental Health.
[152] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[153] R H Fagard,et al. Prognostic significance of blood pressure measured in the office, at home and during ambulatory monitoring in older patients in general practice , 2005, Journal of Human Hypertension.
[154] W C Mann,et al. Elder Acceptance of Health Monitoring Devices in the Home , 2002, Care Management Journals.
[155] Burr Settles,et al. From Theories to Queries: Active Learning in Practice , 2011 .
[156] Giuseppe De Nicolao,et al. Bayesian analysis of blood glucose time series from diabetes home monitoring , 2000, IEEE Transactions on Biomedical Engineering.
[157] David G. Kerwin,et al. A wearable and flexible Bracelet computer for on-body sensing , 2011, 2011 IEEE Consumer Communications and Networking Conference (CCNC).
[158] N J Douglas,et al. Sleep · 4: Sleepiness, cognitive function, and quality of life in obstructive sleep apnoea/hypopnoea syndrome , 2004, Thorax.
[159] Eva Negri,et al. Risk Factors for Falls in Community-dwelling Older People: A Systematic Review and Meta-analysis , 2010, Epidemiology.
[160] Lex M Bouter,et al. A Classification Tree for Predicting Recurrent Falling in Community‐Dwelling Older Persons , 2003, Journal of the American Geriatrics Society.
[161] Ahmad Lotfi,et al. Behavioural Pattern Identification in a Smart Home Using Binary Similarity and Dissimilarity Measures , 2011, 2011 Seventh International Conference on Intelligent Environments.
[162] Javier Bajo,et al. Using Heterogeneous Wireless Sensor Networks in a Telemonitoring System for Healthcare , 2010, IEEE Transactions on Information Technology in Biomedicine.
[163] Line Sofie Remvig,et al. Detection of hypoglycemia associated EEG changes during sleep in type 1 diabetes mellitus. , 2012, Diabetes research and clinical practice.
[164] Francisco Herrera,et al. Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics , 2012, Expert Syst. Appl..
[165] C. Lucetti,et al. Wandering and dementia , 2014, Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society.
[166] Ko Keun Kim,et al. A Smart Health Monitoring Chair for Nonintrusive Measurement of Biological Signals , 2012, IEEE Transactions on Information Technology in Biomedicine.
[167] J. Ramon,et al. Machine learning techniques to examine large patient databases. , 2009, Best practice & research. Clinical anaesthesiology.
[168] Shuangquan Wang,et al. An Activity Transition Based Fall Detection Model on Mobile Devices , 2012 .
[169] Kenneth Sundaraj,et al. Gait disorder rehabilitation using vision and non-vision based sensors: a systematic review. , 2012, Bosnian journal of basic medical sciences.
[170] E. Ambikairajah,et al. Automated Sound Analysis System for Home Telemonitoring using Shifted Delta Cepstral Features , 2007, 2007 15th International Conference on Digital Signal Processing.
[171] M. Gams,et al. Intelligent elderly-care prototype for fall and disease detection , 2011 .
[172] Sally Wyke,et al. Multimorbidity in primary care: developing the research agenda. , 2009, Family practice.
[173] Ahmed Alahmadi,et al. A smart approach towards a mobile e-health monitoring system architecture , 2011, 2011 International Conference on Research and Innovation in Information Systems.
[174] Liljana Gavrilovska,et al. RFID and sensors enabled In-home elderly care , 2011, 2011 Proceedings of the 34th International Convention MIPRO.
[175] H. Ogawa,et al. A mobile phone-based Safety Support System for wandering elderly persons , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[176] Helge B. D. Sørensen,et al. Automatic QRS complex detection algorithm designed for a novel wearable, wireless electrocardiogram recording device , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[177] Nathalie Cislo. Undernutrition Prevention for Disabled and Elderly People in Smart Home with Bayesian Networks and RFID Sensors , 2010, ICOST.
[178] Alvin Harvey Kam,et al. An automatic acoustic bathroom monitoring system , 2005, 2005 IEEE International Symposium on Circuits and Systems.
[179] Nicolas Vuillerme,et al. Ambient Assistive Healthcare and Wellness Management - Is "The Wisdom of the Body" Transposable to One's Home? , 2013, ICOST.
[180] T. Falk,et al. Taking NIRS-BCIs Outside the Lab: Towards Achieving Robustness Against Environment Noise , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[181] Margaret A. K. Ryan,et al. Human activity monitoring using gas sensor arrays , 2014 .
[182] Wan Ling Chang,et al. Use of seal-like robot PARO in sensory group therapy for older adults with dementia , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
[183] Michel Vacher,et al. Sound Environment Analysis in Smart Home , 2012, AmI.
[184] Nicolas Vuillerme,et al. Behavioral Telemonitoring of the Elderly at Home: Detection of Nycthemeral Rhythms Drifts from Location Data , 2010, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.
[185] Stefan Rust,et al. Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups , 2012, BMC Medical Informatics and Decision Making.
[186] L. Rubenstein. Falls in older people: epidemiology, risk factors and strategies for prevention. , 2006, Age and ageing.
[187] Paolo Remagnino,et al. MONITORING BEHAVIOR WITH AN ARRAY OF SENSORS , 2007, Comput. Intell..
[188] Amedeo Cesta,et al. GiraffPlus: a system for monitoring activities and physiological parameters and promoting social interaction for elderly. , 2014 .
[189] D. Hogan,et al. The atypical presentation of infection in old age. , 1987, Age and ageing.
[190] Jian Lu,et al. Multi-User Activity Recognition in a Smart Home , 2011 .
[191] Inmaculada Plaza,et al. Challenges, issues and trends in fall detection systems , 2013, Biomedical engineering online.
[192] Mitja Lustrek,et al. Fall Detection and Activity Recognition with Machine Learning , 2009, Informatica.
[193] Dragan Gamberger,et al. Combining unsupervised and supervised machine learning in analysis of the CHD patient database , 2001 .
[194] Brian Roark,et al. Spoken Language Derived Measures for Detecting Mild Cognitive Impairment , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[195] K. S. Park,et al. Fall detection algorithm for the elderly using acceleration sensors on the shoes , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[196] N. A. Ricauda,et al. Delirium in elderly home-treated patients: a prospective study with 6-month follow-up , 2009, AGE.
[197] B. Winblad,et al. The age-dependent relation of blood pressure to cognitive function and dementia , 2005, The Lancet Neurology.
[198] C. Waszynski. How to Try This: Detecting Delirium , 2007, The American journal of nursing.
[199] Paul Panek,et al. Monitoring system for day-to-day activities of older persons living at home alone , 2012 .
[200] Silvia Coradeschi,et al. Sensor Network Infrastructure for a Home Care Monitoring System , 2014, Sensors.
[201] I. Lamster,et al. The Oral Disease Burden Faced by Older Adults , 2008 .
[202] Majd Alwan,et al. Falls, Fall Prevention, and Fall Detection Technologies , 2008 .
[203] Reinhold Haux,et al. Health-enabling technologies for the elderly - An overview of services based on a literature review , 2012, Comput. Methods Programs Biomed..
[204] Luis Paulo Reis,et al. A survey on Ambient Intelligence projects , 2012, 7th Iberian Conference on Information Systems and Technologies (CISTI 2012).
[205] Bhuvana Ramabhadran,et al. Multimodal Classification of Activities of Daily Living Inside Smart Homes , 2009, IWANN.
[206] Yingzi Lin,et al. A Natural Contact Sensor Paradigm for Nonintrusive and Real-Time Sensing of Biosignals in Human-Machine Interactions , 2011, IEEE Sensors Journal.
[207] Phyo Wai Aung Aung,et al. FBG-based smart bed system for healthcare applications , 2010 .
[208] Gwenn Englebienne,et al. Accurate activity recognition in a home setting , 2008, UbiComp.
[209] T. Jones,et al. Detection of nocturnal hypoglycemic episodes using EEG signals , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[210] Mi Jeong Kim,et al. A Critical Review of User Studies on Healthy Smart Homes , 2013 .
[211] R. A. Goubran,et al. Nonintrusive load monitoring of electrical devices in health smart homes , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.
[212] Mark Speechley,et al. Defining a fall and reasons for falling: comparisons among the views of seniors, health care providers, and the research literature. , 2006, The Gerontologist.
[213] David A. Clifton,et al. Probabilistic detection of vital sign abnormality with Gaussian process regression , 2012, 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE).
[214] L. Ferrucci,et al. Sarcopenic obesity: definition, cause and consequences , 2008, Current opinion in clinical nutrition and metabolic care.
[215] Alka R Kaushik,et al. Characterization of PIR detector for monitoring occupancy patterns and functional health status of elderly people living alone at home. , 2007, Technology and health care : official journal of the European Society for Engineering and Medicine.
[216] Kwangsuk Park,et al. Air mattress sensor system with balancing tube for unconstrained measurement of respiration and heart beat movements , 2005, Physiological measurement.
[217] Mark E Williams,et al. A new approach to assessing function in elderly people. , 2003, Transactions of the American Clinical and Climatological Association.
[218] S. Hales,et al. Climate change and human health: present and future risks , 2006, The Lancet.
[219] J. Liszka-Hackzell. Categorization of Fetal Heart Rate Patterns Using Neural Networks , 2001, Journal of Medical Systems.
[220] Adriana M. Seelye,et al. Naturalistic Assessment of Everyday Activities and Prompting Technologies in Mild Cognitive Impairment , 2013, Journal of the International Neuropsychological Society.
[221] Ling Bao,et al. Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.
[222] Enric Monte-Moreno,et al. Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques , 2011, Artif. Intell. Medicine.
[223] F. Towhidkhah,et al. Using neural network in order to predict hypotension of hemodialysis patients , 2011, 2011 19th Iranian Conference on Electrical Engineering.
[224] Matjaz Gams,et al. Detecting gait-related health problems of the elderly using multidimensional dynamic time warping approach with semantic attributes , 2013, Multimedia Tools and Applications.
[225] Judy A Stevens,et al. Falls among older adults--risk factors and prevention strategies. , 2005, Journal of safety research.
[226] Bart Vanrumste,et al. Automatic Monitoring of Activities of Daily Living based on Real-life Acoustic Sensor Data: a~preliminary study , 2013, SLPAT.
[227] S. Inouye,et al. Delirium in older persons. , 2006, New England Journal of Medicine.
[228] C. Wann-Hansson,et al. Sleep quality, use of hypnotics and sleeping habits in different age-groups among older people. , 2014, Scandinavian journal of caring sciences.
[229] Subhas Chandra Mukhopadhyay,et al. Wearable Sensors for Human Activity Monitoring: A Review , 2015, IEEE Sensors Journal.
[230] Y. Nishida,et al. Non-invasive and unrestrained monitoring of human respiratory system by sensorized environment , 2002, Proceedings of IEEE Sensors.
[231] Arif Gülten,et al. Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms , 2011, Comput. Methods Programs Biomed..
[232] Philippe Roose,et al. Toward a context-aware and automatic evaluation of elderly dependency in smart homes and cities , 2013, 2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).
[233] Thierry Troosters,et al. Validity of activity monitors in health and chronic disease: a systematic review , 2012, International Journal of Behavioral Nutrition and Physical Activity.
[234] G. Virone,et al. The health integrated smart home information system (HIS/sup 2/): rules based system for the localization of a human , 2002, 2nd Annual International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology. Proceedings (Cat. No.02EX578).
[235] María Martínez Pérez,et al. Application of RFID Technology in Patient Tracking and Medication Traceability in Emergency Care , 2012, Journal of medical systems.
[236] Matjaz Gams,et al. Automatic recognition of gait-related health problems in the elderly using machine learning , 2012, Multimedia Tools and Applications.
[237] Rong Chen,et al. Latent-Dynamic Conditional Random Fields for recognizing activities in smart homes , 2014, J. Ambient Intell. Smart Environ..
[238] Michael Cherkassky. Application of Machine Learning Methods to Medical Diagnosis , 2009 .
[239] Machiko Tomita,et al. Smart Home with Healthcare Technologies for Community-Dwelling Older Adults , 2010 .
[240] Misha Pavel,et al. Unobtrusive monitoring of the longitudinal evolution of in-home gait velocity data with applications to elder care , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[241] Prafulla N. Dawadi,et al. An approach to cognitive assessment in smart home , 2011, DMMH '11.
[242] R. Sheldon,et al. Implantable rhythm devices in the management of vasovagal syncope , 2014, Autonomic Neuroscience.
[243] Jukka Vanhala,et al. Energy Efficient Sensor Network with Service Discovery for Smart Home Environments , 2009, 2009 Third International Conference on Sensor Technologies and Applications.
[244] Gert Cauwenberghs,et al. Wireless non-contact cardiac and neural monitoring , 2010, Wireless Health.
[245] Claudio Del Percio,et al. Development and assessment of methods for detecting dementia using the human electroencephalogram , 2006, IEEE Transactions on Biomedical Engineering.
[246] K. J. Miller,et al. Smart-Home Technologies to Assist Older People to Live Well at Home , 2013 .
[247] Jean-Marc Ginoux,et al. An Ultrasonic Contactless Sensor for Breathing Monitoring , 2014, Sensors.
[248] Paul Wieneke,et al. Evaluation of the performance of a wrist blood pressure measuring device with a position sensor compared to ambulatory 24-hour blood pressure measurements. , 2002, American journal of hypertension.
[249] Subhas Chandra Mukhopadhyay,et al. Wireless sensors network based safe home to care elderly people: behaviour detection , 2011 .
[250] Prajakta Kulkarni,et al. mPHASiS: Mobile patient healthcare and sensor information system , 2011, J. Netw. Comput. Appl..
[251] Octavian Postolache,et al. Health monitoring using textile sensors and electrodes: An overview and integration of technologies , 2014, 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA).
[252] S. Rose. Mortality risk score prediction in an elderly population using machine learning. , 2013, American journal of epidemiology.
[253] S. D. de Rooij,et al. Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons. , 2008, Age and ageing.
[254] A. Lanata,et al. New Ultrasound-Based Wearable System for Cardiac Monitoring , 2006, 2006 5th IEEE Conference on Sensors.