A Context-Aware mHealth System for Online Physiological Monitoring in Remote Healthcare
Keywords:
decision support systems, telemonitoring, Context-Aware applicationAbstract
Physiological or biological stress is an organism’s response to a stressor such as an environmental condition or a stimulus. The identification of physiological stress while performing the activities of daily living is an important field of health research in preventive medicine. Activities initiate a dynamic physiological response that can be used as an indicator of the overall health status. This is especially relevant to high risk groups; the assessment of the physical state of patients with cardiovascular diseases in daily activities is still very difficult. This paper presents a context-aware telemonitoring platform, IPM-mHealth, that receives vital parameters from multiple sensors for online, real-time analysis. IPM-mHealth provides the technical basis for effectively evaluating patients’ physiological conditions, whether inpatient or at home, through the relevance between physical function and daily activities. The two core modules in the platform include: 1) online activity recognition algorithms based on 3-axis acceleration sensors and 2) a knowledge-based, conditional-reasoning decision module which uses context information to improve the accuracy of determining the occurrence of a potentially dangerous abnormal heart rate. Finally, we present relevant experiments to collect cardiac information and upper-body acceleration data from the human subjects. The test results show that this platform has enormous potential for use in long-term health observation, and can help us define an optimal patient activity profile through the automatic activity analysis.
References
Jovanov, E., Milosevic, M., Milenkovic, A.(2013); A mobile system for assessment of physiological response to posture transitions, Proc. of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, art. no. 6611220, 7205-7208.
Berndt, R.-D., Takenga, M.C., Kuehn, S., Preik, P., Stoll, N., Thurow, K., Kumar, M., Weippert, M., Rieger, A., Stoll, R.(2011); A scalable and secure telematics platform for the hosting of telemedical applications. Case study of a stress and fitness monitoring, IEEE 13th International Conference on e-Health Networking, Applications and Services, HEALTHCOM, art. no. 6026726, 118-121.
Dey, A.K., Abowd, G.D., Salber, D.(2001); A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications, Human-Computer Interaction, 16 (2-4): 97-166.
Vajirkar, P., Singh, S., Lee, Y.(2003); Context-aware data mining framework for wireless medical application, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2736, 381-391.
Ito, T.(2013); An approach of body movement-based interaction towards remote collaboration, 20th ISPE International Conference on Concurrent Engineering, CE - Proceedings, 163-172.
Hossain, M.A., Alamri, A., Parra, J.(2013); Context-aware elderly entertainment support system in assisted living environment, Electronic Proc. of the IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2013, art. no. 6618365.
Van Cauwenberg, J., Van Holle, V., De Bourdeaudhuij, I., Clarys, P., Nasar, J., Salmon, J., Maes, L., Goubert, L., Van de Weghe, N., Deforche, B.(2014); Physical environmental factors that invite older adults to walk for transportation, Journal of Environmental Psychology, 38: 94-103. http://dx.doi.org/10.1016/j.jenvp.2013.12.012
Ogawa, Mitsuhiro, Tamura, Toshiyo, Togawa, Tatsuo.(1998); Fully automated biosignal acquisition in daily routine through 1 month, Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, 4: 1947-1950.
Manios, Y., Moschonis, G., Papandreou, C., Politidou, E., Naoumi, A., Peppas, D., Mavrogianni, C., Lionis, C., Chrousos, G.P. (2015); Revised Healthy Lifestyle-Diet Index and associations with obesity and iron deficiency in schoolchildren: The Healthy Growth Study, Journal of Human Nutrition and Dietetics, Suppl 2:50-8. doi: 10.1111/jhn.12183. Epub 2013 Dec 5. http://dx.doi.org/10.1111/jhn.12183
Jakkula, V.(2007); Predictive data mining to learn health vitals of a resident in a smart home, Proceedings - IEEE International Conference on Data Mining, ICDM, art. no. 4476662, 163-168. http://dx.doi.org/10.1109/icdmw.2007.57
Gjevjon, E.R., Eika, K.H., Romoren, T.I., Landmark, B.F.(2014); Measuring interpersonal continuity in high-frequency home healthcare services, Journal of Advanced Nursing, 70(3): 553-563. http://dx.doi.org/10.1111/jan.12214
Costin, Hariton, Rotariu, Cristian, et al. (2008); Complex Telemonitoring of Patients and Elderly People for Telemedical and Homecare Services, Proc. of the 1st WSEAS Int. Conf. on Biomedical Electronics and Biomedical Informatics, Rhodes, GREECE, AUG 20-22, 2008, Edited by: Long, CA; Anninos, P; Pham, T; et al., Book Series: Recent Advances in Biology and Biomedicine, 183-187.
Berkow, M., Monsere, C.M., Koonce, P., Bertini, R.L., Wolfe, M. (2009); Prototype for data fusion using stationary and mobile data, Transportation Research Record, 102-112.
Ermes, M., Parkka, J., Mantyjarvi, J., Korhonen, I.(2008); Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions, IEEE Transactions on Information Technology in Biomedicine, 12 (1): 20-26. http://dx.doi.org/10.1109/TITB.2007.899496
Heinz, EA., Kunze, KS., Gruber, M., Bannach, D., Lukowicz, P. (2006); Using Wearable Sensors for Real-Time Recognition Tasks in Games of Martial Arts-An Initial Experiment, Computational Intelligence and Games, IEEE , 98-102.
Han, S.N., Lee, G.M., Crespi, N. (2014); Semantic context-aware service composition for building automation system, IEEE Transactions on Industrial Informatics, art. no. 6478809, 10 (1): 252-261.
Zhang, S., McClean, S., Scotney, B., Galway, L., Nugent, C. (2014); A framework for context-aware online physiological monitoring, Proceedings - IEEE Symposium on Computer-Based Medical Systems, art. no. 5999038.
Abe, B.T., Olugbara, O.O., Marwala, T. (2014); Classification of hyperspectral images using machine learning methods, Lecture Notes in Electrical Engineering, 247 LNEE, 555-569.
Zhang, W., Thurow, K., Stoll, R.(2013); A SOA and knowledge-based telemonitoring framework: Design, modeling, and deployment, International Journal of Online Engineering, 9 (6): 48-57.
Sannino, G., De Pietro, G. (2011); A smart context-aware mobile monitoring system for heart patients, IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011, art. no. 6112448, 655-659.
She, J., Nakamura, H., Makino, K., Ohyama, Y., Hashimoto, H., Wu, M. (2013); Experimental selection and verification of maximum-heart-rate formulas for use with karvonen formula, ICINCO - Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics, 2: 536-541.
Hidalgo Limited, Equivital EQ-01 Vital Signs Monitor Health Care Practioner Guide. Dokumentation, Hidalgo Ltd., 2006.
M. Kumar, M. Weippert, R. Vilbrandt, S. Kreuzfeld, and R. Stoll, (2007); Fuzzy evaluation of heart rate signals for mental stress assessment, IEEE Transactions on Fuzzy Systems, 15: 791-808. http://dx.doi.org/10.1109/TFUZZ.2006.889825
K Aminian, B Najjafi, (2002); Body movement monitoring system and method, US.Patient EP 119513910.
Fuentes, D., Gonzalez-Abril, L., Angulo, C., Ortega, J. A. (2012); Online motion recognition using an accelerometer in a mobile device, Expert systems with applications, 39(3): 2461- 2465. http://dx.doi.org/10.1016/j.eswa.2011.08.098
Godfrey, A., Bourke, AK., Olaighin, GM. (2011); Activity classification using a single chest mounted triaxial accelerometer, Medical Engineering and Physics, 33(9): 1127-1135. http://dx.doi.org/10.1016/j.medengphy.2011.05.002
Fleury, A., Noury, N., Vacher, M. (2009); A wavelet-based pattern recognition algorithm to classify postural transitions in humans, 17th European Signal Processing Conference, 2047 - 2051.
Published
Issue
Section
License
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.
