Pichora-Fuller, M.K. • Four sleep measures (sleep onset latency (SOL), total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE%)) are extracted from both systems. He, Y.; Li, Y.; Bao, S.-O. 3 May 2017. But there are others, as well. Are You Ready? Issue 9. It featured Web browsing capability on top of most of the features that IBM’s Simon offered. Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine. Tracking lung function on any phone. Consequently, the elderly population in many countries are expected to rise rapidly in the coming years. by Sumit Majumder. Available online: U.S. Department of Health and Human Services Food and Drug Administration. Adv. [, Chen, N.-C.; Wang, K.-C.; Chu, H.-H. Listen-to-nose: A low-cost system to record nasal symptoms in daily life. A Pulse Rate Estimation Algorithm Using PPG and Smartphone Camera. ; Peck, G.L. Therefore, more research and development efforts are needed to improve the systems’ ease-of-use and pervasiveness. One-year mortality among elderly people after hospitalization due to fall-related fractures: comparison with a control group of matched elderly. Available online: AliveCor, Inc. KardiaMobile. [. Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone. ; Ramachandran, K.I. ; Bahyah Kamaruzzaman, S.; Seang Lim, K.; Maw Pin, T.; Ibrahim, F. Smartphone-based solutions for fall detection and prevention: Challenges and open issues. Available online: Coutinho, E.S.F. Nam, Y.; Kong, Y.; Reyes, B.; Reljin, N.; Chon, K.H. Kalache, A.; Gatti, A. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing—UbiComp ’12, Pittsburgh, PA, USA, 5–8 September 2012; p. 351. Smartphone-based fundus camera device (MII Ret Cam) and technique with ability to image peripheral retina. Kim, S.; Crose, M.; Eldridge, W.J. [. The statements, opinions and data contained in the journals are solely Haddock, L.J. Online telemedicine systems are useful due to the possibility of timely and efficient healthcare services. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing—UbiComp ’16, Heidelberg, Germany, 12–16 September 2016. Validity of diagnostic pure-tone audiometry without a sound-treated environment in older adults. ; Sober, A.J. ; Bogdan, A.; Gutkowicz-Krusin, D.; et al. Sager, I. Human activity recognition with smartphone sensors using deep learning neural networks. Min, J.-K.; Doryab, A.; Wiese, J.; Amini, S.; Zimmerman, J.; Hong, J.I. • Classification accuracy: 93.06% (Sleep state), 83.97% (daily sleep quality), 81.48% (overall sleep quality), Best effort sleep (BES) model for sleep duration monitoring. Available online: Maclennan-Smith, F.; Swanepoel, D.W.; Hall, J.W. However, it was never released to the public, arguably because of its weight and poor battery quality [, In 2002, Handspring and RIM released their first smartphones Treo-180 and Blackberry 5810 (5820 for Europe) in the market, respectively [. Börve, A.; Gyllencreutz, J.; Terstappen, K.; Backman, E.; Aldenbratt, A.; Danielsson, M.; Gillstedt, M.; Sandberg, C.; Paoli, J. Smartphone Teledermoscopy Referrals: A Novel Process for Improved Triage of Skin Cancer Patients. ; Semeere, A.; Osman, H.; Peterson, G.; Rajadhyaksha, M.; González, S.; Martin, J.N. 1 and . Canada.ca. 1198–1201. Healthcare Solutions|PureWeb|ResolutionMD. Ronao, C.A. • Number of layers, number of feature maps, pooling and convolutional filter size were adjusted to maximize test-accuracy by ‘softmax’ classifier. Advantages & Disadvantages of Nursing Homes. Gerontol. Childhood Hearing Screening Guidelines. Støve, M.P. Wang, R.; Chen, F.; Chen, Z.; Li, T.; Harari, G.; Tignor, S.; Zhou, X.; Ben-Zeev, D.; Campbell, A.T. StudentLife: Assessing mental health, academic performance and behavioral trends of college students using smartphones. • Highly correlated (correlation coefficient of 0.9957, 0.9860, and 0.9533 for central apnea, obstructive apnea and hypopnea, respectively) with the ground truth. ; Bradley, T.D. Elbaum, M.; Kopf, A.W. • Multilayer perceptron for final recognition. [. Smartphones have become a useful tool in agriculture because their mobility matches the nature of farming, the cost of the device is highly accessible, and their computing power allows a variety of practical applications to be created. ; Meyyappan, M. U-Health Smart Home: Innovative solutions for the management of the elderly and chronic diseases. Prevention of Blindness and Deafness World Health Organization. GOV.UK. ; Bloomgarden, Z.; Lu, K.; Tamler, R. An evaluation of diabetes self-management applications for Android smartphones. Eysenbach, G.; Ruwaard, J.; Bardram, J.; Saeb, S.; Zhang, M.; Karr, C.J. Using the smartphone camera to monitor heart rate and rhythm in heart failure patients. [. Available online: Emergo. In Proceedings of the 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, Spain, 6–13 November 2011; pp. Sleep Apnea in Canada, 2016 and 2017. Sensors. Thap, T.; Chung, H.; Jeong, C.; Hwang, K.-E.; Kim, H.-R.; Yoon, K.-H.; Lee, J.; Chon, K.H. Wearable sensors, just as the name implies, are integrated into wearable objects or directly with the body in order to help monitor health and/or provide clinically relevant data for care. Saeb, S.; Lattie, E.G. [, Larson, E.C. 2019Apr27 Smartphone-sensors for Health Monitoring & Diagnosis.docx. Pearson Correlation coefficient (PC) for most parameters between PPG and ECG: >0.99. Agoulmine, N.; Deen, M.J.; Lee, J.S. 3–14. ; Xu, S.; Kesselheim, A.S. Regulation of Medical Devices in the United States and European Union. In Proceedings of the 5th Augmented Human International Conference, Kobe, Japan, 7–8 March 2014. Eysenbach, G.; Paglialonga, A.; Handzel, O.; Mahomed-Asmail, F.; Moodie, S.; Bright, T.; Pallawela, D. Validated Smartphone-Based Apps for Ear and Hearing Assessments: A Review. Newzoo. Smartphone-Based Dilated Fundus Photography and Near Visual Acuity Testing as Inexpensive Screening Tools to Detect Referral Warranted Diabetic Eye Disease. HR error rate: 4.8% AF detection: 97% specificity, 75% sensitivity. For class IIa devices, manufacturers must also declare the device’s compliance with the corresponding regulatory requirements of the Directive. In the following sections (, Heart rate (HR) or pulse rate is one of the four ‘vital signs’ that is routinely monitored by physicians to diagnose heart-related diseases such as different types of arrhythmias [, However, these portable and wearable systems require additional accessories, which can be avoided by exploiting the embedded sensors such as a camera and microphone in the smartphone for monitoring HR and HRV. Available online: Edjoc, R.; Gal, J. • DNN-based subassembly divides sensor data into various motion states. Available online: World Health Organization. Van Norman, G.A. Accurate and privacy preserving cough sensing using a low-cost microphone. However, Ericsson first coined the term ‘Smart-phone’ for its Ericsson GS 88. a health monitoring system is presented in [12] in which medical staff can access the stored data online through content service application. Deep Convolutional Neural Networks for Human Activity Recognition with Smartphone Sensors. 2011. “National Center for Health Statistics,” Centers for Disease Control and Prevention. Available online: Bernstein, J.G.W. [, Goel, M.; Saba, E.; Stiber, M.; Whitemire, E.; Fromm, J.; Larson, E.C. CE Marking. • Analysis of the raw video signal (green channel) and ICA-decomposed signals of the face in the frequency domain. In Proceedings of the ICTs for Improving Patients Rehabilitation Research Techniques, Venice, Italy, 5–8 May 2013; pp. Smart and mobile sensor systems have taken SHM discipline to a new era in the past two decades. De, D.; Bharti, P.; Das, S.; Chellappan, S. Multi-modal Wearable Sensing for Fine-grained Activity Recognition in Healthcare. A Real-time Fall Detection System Based on the Acceleration Sensor of Smartphone. ; Chang, R.T.; Polkinhorne, A.; Merrell, D.; Foster, D.; Blumenkranz, M.S. Strickland, E. The FDA Takes on Mobile Health Apps. ; Dupuis, K.; Reed, M.; Lemke, U. 26 January 2013. • Wireless sensor data mining (WISDM) dataset from. In 2000, both Samsung and Sharp introduced a camera phone in their respective local markets. High-Resolution Time-Frequency Spectrum-Based Lung Function Test from a Smartphone Microphone. Available online: The European Parliament and the Council of the European Union. ; Ryan, S.; Harper, S.; George, G. Aging populations and management. Motorola Moto X, Motorola, Libertyville, IL and Samsung S 5. 2015; Available online: Premarket Notification 510(k). Ben-Zeev, D.; Scherer, E.A. • University of California Irvine (UCI) Human activity recognition (HAR) dataset. Please note that many of the page functionalities won't work as expected without javascript enabled. Vidal, J. 1, B and C), enabling gentle yet intimate contact with the surface of the skin for application on nearly any region of the body, including challenging areas such as the shin, face, and even the knuckles (Fig. Bloomberg.com. It is an important and relevant topic, as properly explained by the authors, because of the evolution of demography, with a world population living longer. M.J.D. directed the research and did the final revisions. Karargyris, A.; Karargyris, O.; Pantelopoulos, A. DERMA/Care: An Advanced image-Processing Mobile Application for Monitoring Skin Cancer. Myung, D.; Jais, A.; He, L.; Blumenkranz, M.S. Balance analysis and Audio Bio-Feedback (ABF) system. ; Chen, K.H. 28 November 2018. Demidowich, A.P. Note that some commercial solutions based on smartphones/tablets already exist for assessing hearing loss. • Accuracy for sitting, walking, and jogging at different paces: 90.1%–94.1%. Medical Device Stand—Alone Software Including Apps. In this paper, we have presented a state-of-the-art survey on health and activity monitoring systems that exploit the embedded sensors in smartphones for measuring physiological parameters and tracking health conditions. Anguita, D.; Ghio, A.; Oneto, L.; Parra, X.; Reyes-Ortiz, J.L. 5675–5685. Available online: Woyke, E. The Smartphone: Anatomy of an Industry. Biomedical sensors gather information on body from various sources and convert the data into numerical value. Furthermore, the significant progress in display, sensor and battery technologies together have paved the way for modern mobile devices such as smartphones and tablets, enabling seamless internet connectivity, entertainment, and health and fitness monitoring on the go along with conventional voice and text communication. In Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan, 3–7 July 2013; pp. Shoaib, M.; Scholten, H.; Havinga, P. Towards Physical Activity Recognition Using Smartphone Sensors. ; Swanepoel, D.W.; De Jager, L.B. Katie Boehret took a look at a couple of these devices — the HeartMath Inner Balance Sensor and Tinké — in her column here. Ofcom|Statutory Duties and Regulatory Principles. Available online: Majumder, S.; Mondal, T.; Deen, M.J. Wearable Sensors for Remote Health Monitoring. cited and described. Some wearable technology applications are designed for prevention of diseases and maintenance of health, such as weight control and physical activity monitoring. Available online: Making a Success of Brexit. Air Pollution Rising at an ‘Alarming Rate’ in World’s Cities. However, to date, most publications either did not address these critical issues or did so in a cursory manner. Priority Eye Diseases. [. Resources for Parents|Autism & Beyond. [. Centers for Disease Control and Prevention. Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: A feasibility study. PC: ~ 1.0 (HR), PC for Other ECG parameters: 0.72-1 (Droid), 0.8-1 (iPhone). Hassan, M.M. However, none of the camera phones supported web browsing and email communication until Sanyo launched the first smartphone with a built-in camera in 2002. A few months later, in Japan, Sharp released the J-SH04 in Japan with a 256-color display and a built-in 0.11-megapixel CMOS camera. Author Response File: Author Response.docx. ; Lee, T.; Liu, S.; Rosenfeld, M.; Patel, S.N. 22 April 2016. In Proceedings of the International Conference on Advances in Mobile Computing & Multimedia, Vienna, Austria, 2–4 December 2013; pp. Luque, R.; Casilari, E.; Morón, M.-J. In Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy, 25–29 August 2015; pp. Abu-Ghanem, S.; Handzel, O.; Ness, L.; Ben-Artzi-Blima, M.; Fait-Ghelbendorf, K.; Himmelfarb, M. Smartphone-based audiometric test for screening hearing loss in the elderly. 30 August 2017. Ronao, C.A. In addition, diseases related to the cardiovascular system, eye, respiratory system, skin and mental health are widespread globally. In Proceedings of the 13th International Conference on Ubiquitous Computing, Beijing, China, 17–21 September 2011; p. 375. ; smartphone sensors for health monitoring and diagnosis, J: ETDRS Report Number 10 Faezipour, M. ; Youn, S. Chellappan. ( MDSAP ) Transition Plan—Frequently Asked Questions ( FAQ ) disorder using smart phones classification and regression (... However, to date, most of these activities the green channel ) and Registration... 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