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Development of u-Health Care System for Dementia Patients
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 Title & Authors
Development of u-Health Care System for Dementia Patients
Shin, Dong-Min; Shin, Dong-Il; Shin, Dong-Kyoo;
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For patients who have senile mental disorder such as dementia, quantity of excercise and amount of sunlight are important clue for dose and the treatment. Therefore, monitoring health information of daily life is necessary for patients' safety and healthy life. Portable & wearable sensor device and server configuration monitoring data are needed to provide these services for patients. Watch-type device(smart watch) which patients wear and server system are developed in this paper. Smart watch developed includes GPS, accelerometer and illumination sensor, and can obtain real time health information by measuring the position of patients, quantity of exercise and amount of sunlight. Server system includes the sensor data analysis algorithm and web server that doctor and protector can monitor through sensor data acquired from smart watch. The proposed data analysis algorithm acquires quantity of exercise information and detects step count in patients' motion acquired from acceleration sensor and to verify this, the three cases with fast pace, slow pace, and walking pace show 96% of the experimental result. If developed u-Healthcare System for dementia patients is applied, more high-quality medical service can be provided to patients.
3-axis accelerometer;u-Health Care;Step number detection algorithm;
 Cited by
실내 위치기반 사물인터넷 채팅 서비스 설계 및 구현,이성희;정설영;강순주;이우진;

한국통신학회논문지, 2014. vol.39C. 10, pp.920-929 crossref(new window)
U-Healthcare 기기에서 DRDoS공격 보안위협과 Big Data를 융합한 대응방안 연구,허윤아;이근호;

한국융합학회논문지, 2015. vol.6. 4, pp.243-248 crossref(new window)
건강정보를 이용한 OTP 생성 방식 설계,추연수;강정호;김경훈;박재표;전문석;

디지털융복합연구, 2015. vol.13. 8, pp.315-320 crossref(new window)
Designed OTP Generation Method Using Health Information, Journal of Digital Convergence, 2015, 13, 8, 315  crossref(new windwow)
Ministry of Health & Welfare, Country dementia care comprehensive plan, July 2012.

J. Uhm and S.-H. Park, "Application of the modified real-time medical information standard for U-healthcare systems by using HL7 and modified MFER(TS-MFER)," J. Korea Inform. Commun. Soc. (KICS), vol. 37C, no. 8, pp. 680-689, Aug. 2012. crossref(new window)

M. Choi, J. Lee, and I. Joe, "Design and implementation of the aging-friendly telemedicine system based on CPS for silver town," J. Korea Inform. Commun. Soc. (KICS), vol. 37C, no. 8, pp. 690-696, Aug. 2012. crossref(new window)

G. E. Mead, W. Morley, P. Campbell, C. A. Greig, M. McMurdo, and D. A. Lawlor, "Exercise for depression," Cochrane Database Syst. Rev., vol. 8, no. 3, Article no. CD004366, July 2009.

H. Y. Moon, et al., "Macrophage migration inhibitory factor mediates the antidepressant actions of voluntary exercise," Proc. Nat. Academy Sci. U.S.A., vol. 109, no. 32, pp. 13094-13099, June 2012. crossref(new window)

Company Keruve, Keruve(2010), retrieved Nov., 24, 11, 2013, from

Gang-nam Gu, u-safe Gang-nam(2010), retrieved Nov., 24, 11, 2013, from

KT, I-Search(2009), retrieved Nov., 24, 11, 2013, from

J. Yang, "Toward physical activity diary: motion recognition using simple acceleration features with mobile phones," in Proc. Int. Workshop Interactive Multimedia Consumer Electron. (IMCE '09), pp. 1-10, Beijing, China, Oct. 2009.

L. Bao, and S. S. Intille, "Activity recognition from user-annotated acceleration data," Lecture Notes Comput. Sci., vol. 3001, pp. 1-17, April. 2004.

J. Baek, G. Lee, W. Park, and B.-J. Yun, "Accelerometer signal processing for user activity detection," Lecture Notes Comput. Sci., vol. 3215, pp. 610-617, Sept. 2004.

N. Ravi, N. Dandekar, P. Mysore, and M. L. Littman, "Activity recognition from accelerometer data," in Proc. Innovative Applicat. Artificial Intell. (IAAI), vol. 5, pp. 1541-1546, Pittsburgh, U.S.A., July 2005.

H.-M. Yoo, J.-W. Suh, E.-J. Cha, and H.-D. Bae, "Walking number detection algorithm using a 3-axial accelerometer sensor and activity monitoring," J. Korea Contents Assoc. (KOCON), vol. 8, no. 8, pp. 253-260, Aug. 2008. crossref(new window)

S. H. Shin and C. G. Park, "Adaptive step length estimation algorithm using low-cost MEMS inertial sensors," in Proc. IEEE Sensors Applicat. Symp. (SAS), pp. 1-5, San Diego, U.S.A., Feb. 2007.

Y. H. Noh, S. Y. Ye, and D. U Jeong, "System implementation and algorithm development for classification of the activity states using 3 axial accelerometer," J. Korea Inst. Elect. Electron. Material Eng. (KIEEME), vol. 24, no. 1, pp. 81-88, Jan. 2011. crossref(new window)