메뉴 건너뛰기




Volumn , Issue , 2015, Pages 2353-2358

A survey of physical activity monitoring and assessment using internet of things technology

Author keywords

Internet of things; Physical activity

Indexed keywords

ARTIFICIAL INTELLIGENCE; COST EFFECTIVENESS; DIAGNOSIS; DISEASES; HEALTH; INTERNET; LEARNING ALGORITHMS; LEARNING SYSTEMS; SURVEYS; UBIQUITOUS COMPUTING; WEARABLE TECHNOLOGY;

EID: 84964233723     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIT/IUCC/DASC/PICOM.2015.348     Document Type: Conference Paper
Times cited : (42)

References (53)
  • 1
    • 84964289104 scopus 로고    scopus 로고
    • Accessed 10 June, 2015
    • "WHO" World Health Organisation, 2015. [Online]. Available: http://www.who.int/topics/physical-activity/en/. [Accessed 10 June, 2015].
    • (2015)
    • "WHO" World Health Organisation1
  • 2
    • 79960984111 scopus 로고    scopus 로고
    • Sensor positioning for activity recognition using wearable accelerometers
    • Atallah, Louis, et al. "Sensor positioning for activity recognition using wearable accelerometers." Biomedical Circuits and Systems, IEEE Transactions on 5. 4(2011):320-329.
    • (2011) Biomedical Circuits and Systems, IEEE Transactions on , vol.5 , Issue.4 , pp. 320-329
    • Atallah, L.1
  • 4
    • 84900810686 scopus 로고    scopus 로고
    • An interactive trust model for application market of the internet of things
    • Feb.
    • K. Kang, Z. B. Pang, L. D. Xu, L. Y. Ma and C. Wang, "An interactive trust model for application market of the internet of things", IEEE Trans. Ind. Informat, vol. 10, no. 2, pp. 1516-1526, Feb, 2014.
    • (2014) IEEE Trans. Ind. Informat , vol.10 , Issue.2 , pp. 1516-1526
    • Kang, K.1    Pang, Z.B.2    Xu, L.D.3    Ma, L.Y.4    Wang, C.5
  • 5
    • 84900554215 scopus 로고    scopus 로고
    • Efficient particle filter localisation algorithm in dense passive RFID tags environment
    • Oct.
    • P. Yang and W. Wu, "Efficient particle filter localisation algorithm in dense passive RFID tags environment", IEEE Trans. Ind. Electron, vol. 61, no. 10, pp. 5641-5661, Oct, 2014.
    • (2014) IEEE Trans. Ind. Electron , vol.61 , Issue.10 , pp. 5641-5661
    • Yang, P.1    Wu, W.2
  • 6
    • 84964266447 scopus 로고    scopus 로고
    • Efficient object localisation using sparsely distributed passive RFID tags
    • Dec.
    • P. Yang, W. Wu, M. Moniri and C. C. Chibelushi, "Efficient object localisation using sparsely distributed passive RFID tags", IEEE Trans. Ind. Electron, vol. 10, no. 2, pp. 1443-1451, Dec, 2013.
    • (2013) IEEE Trans. Ind. Electron , vol.10 , Issue.2 , pp. 1443-1451
    • Yang, P.1    Wu, W.2    Moniri, M.3    Chibelushi, C.C.4
  • 7
    • 84961801375 scopus 로고    scopus 로고
    • PRLS-INVES: A general experimental investigation strategy for high accuuracy and precision in passive RFID location systems
    • April
    • P. Yang, "PRLS-INVES: A General Experimental Investigation Strategy for High Accuuracy and Precision in Passive RFID Location Systems", IEEE Internet of Things Journal, vol. 2, no. 2, pp. 159-167, April, 2015.
    • (2015) IEEE Internet of Things Journal , vol.2 , Issue.2 , pp. 159-167
    • Yang, P.1
  • 8
    • 84896979833 scopus 로고    scopus 로고
    • Improving passive radio-frequenc identification localisation precision with moving direction estimation-based feature improvement
    • March
    • P. Yang, "Improving passive radio-frequenc identification localisation precision with moving direction estimation-based feature improvement", IET Wireless Sensor Systems, vol. 4, no. 1, pp. 17-26, March, 2014.
    • (2014) IET Wireless Sensor Systems , vol.4 , Issue.1 , pp. 17-26
    • Yang, P.1
  • 9
    • 84964283464 scopus 로고    scopus 로고
    • Accessed 10 April 2015
    • "Fitbit Flex", Fitbit Ltd, 2015. [Online]. Available: http://www.fitbit.com/uk. [Accessed 10 April 2015].
    • (2015) Fitbit Ltd
    • Fitbit Flex1
  • 10
    • 84964234282 scopus 로고    scopus 로고
    • Accessed 10 April 2015
    • "Nike+ Fuelband", Nike, 2015. [Online]. Available: http://www.nike.com/gb/en-gb/c/nikeplus-fuelband. [Accessed 10 April 2015].
    • (2015) Nike
    • Nike+ Fuelband1
  • 11
    • 84964297832 scopus 로고    scopus 로고
    • Accessed 15 April 2015
    • "Withings", Withings, 2015. [Online]. Available: http://www.withings.com/uk/. [Accessed 15 April 2015].
    • (2015) Withings
    • Withings1
  • 13
    • 0242592241 scopus 로고    scopus 로고
    • Multi-sensor activity context detection for wearable computing
    • Springer Berlin Heidelberg
    • Kern, Nicky, Bernt Schiele, and Albrecht Schmidt. "Multi-sensor activity context detection for wearable computing." Ambient Intelligence. Springer Berlin Heidelberg, 2003. 220-232.
    • (2003) Ambient Intelligence , pp. 220-232
    • Kern, N.1    Schiele, B.2    Schmidt, A.3
  • 14
    • 80054117123 scopus 로고    scopus 로고
    • Activity classification using a single chest mounted tri-axial accelerometer
    • Godfrey, A., et al. "Activity classification using a single chest mounted tri-axial accelerometer." Medical engineering & physics 33. 9(2011):1127-1135.
    • (2011) Medical Engineering & Physics , vol.33 , Issue.9 , pp. 1127-1135
    • Godfrey, A.1
  • 15
    • 30744436064 scopus 로고    scopus 로고
    • Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring
    • Karantonis, Dean M., et al. "Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring." Information Technology in Biomedicine, IEEE Transactions on 10. 1(2006):156-167.
    • (2006) Information Technology in Biomedicine, IEEE Transactions on , vol.10 , Issue.1 , pp. 156-167
    • Karantonis, D.M.1
  • 16
    • 77956366233 scopus 로고    scopus 로고
    • A triaxial accelerometer-based physicalactivity recognition via augmented-signal features and a hierarchical recognizer
    • Khan, Adil Mehmood, et al. "A triaxial accelerometer-based physicalactivity recognition via augmented-signal features and a hierarchical recognizer." Information Technology in Biomedicine, IEEE Transactions on 14. 5(2010):1166-1172.
    • (2010) Information Technology in Biomedicine, IEEE Transactions on , vol.14 , Issue.5 , pp. 1166-1172
    • Khan, A.M.1
  • 17
    • 84918825686 scopus 로고    scopus 로고
    • Recognizing upper limb movements with wrist worn inertial sensors using k-means clustering classification
    • Biswas, Dwaipayan, et al. "Recognizing upper limb movements with wrist worn inertial sensors using k-means clustering classification. " Human movement science 40(2015):59-76.
    • (2015) Human Movement Science , vol.40 , pp. 59-76
    • Biswas, D.1
  • 18
    • 0036063153 scopus 로고    scopus 로고
    • Knee and hip kinetics during normal stair climbing
    • Costigan, Patrick A., Kevin J. Deluzio, and Urs P. Wyss. "Knee and hip kinetics during normal stair climbing." Gait & posture 16. 1(2002):31-37.
    • (2002) Gait & Posture , vol.16 , Issue.1 , pp. 31-37
    • Costigan, P.A.1    Deluzio, K.J.2    Wyss, U.P.3
  • 19
    • 27744466326 scopus 로고    scopus 로고
    • Stair climbing detection during daily physical activity using a miniature gyroscope
    • Coley, Brian, et al. "Stair climbing detection during daily physical activity using a miniature gyroscope." Gait & posture 22. 4(2005):287-294.
    • (2005) Gait & Posture , vol.22 , Issue.4 , pp. 287-294
    • Coley, B.1
  • 20
    • 67049155519 scopus 로고    scopus 로고
    • Fall detection and activity recognition with machine learning
    • Luštrek, Mitja, and Boštjan Kaluža. "Fall detection and activity recognition with machine learning." Informatica 33. 2 (2009).
    • (2009) Informatica , vol.33 , Issue.2
    • Luštrek, M.1    Kaluža, B.2
  • 22
    • 84902837100 scopus 로고    scopus 로고
    • Activity classification based on inertial and barometric pressure sensors at different anatomical locations
    • Moncada-Torres, A., et al. "Activity classification based on inertial and barometric pressure sensors at different anatomical locations." Physiological measurement 35. 7(2014):1245.
    • (2014) Physiological Measurement , vol.35 , Issue.7 , pp. 1245
    • Moncada-Torres, A.1
  • 23
    • 78650044688 scopus 로고    scopus 로고
    • Barometric pressure and triaxial accelerometry-based falls event detection
    • Bianchi, Federico, et al. "Barometric pressure and triaxial accelerometry-based falls event detection. " Neural Systems and Rehabilitation Engineering, IEEE Transactions on 18. 6(2010):619-627.
    • (2010) Neural Systems and Rehabilitation Engineering, IEEE Transactions on , vol.18 , Issue.6 , pp. 619-627
    • Bianchi, F.1
  • 25
    • 84055195118 scopus 로고    scopus 로고
    • Real-time recognition of PA and their intensities using wireless accelerometers and a heart rate monitor
    • IEEE
    • Tapia, Emmanuel Munguia, et al. "Real-time recognition of PA and their intensities using wireless accelerometers and a heart rate monitor." Wearable Computers, 2007 11th IEEE International Symposium on. IEEE, 2007.
    • (2007) Wearable Computers, 2007 11th IEEE International Symposium on
    • Tapia, E.M.1
  • 26
    • 84865789171 scopus 로고    scopus 로고
    • Centinela: A human activity recognition system based on acceleration and vital sign data
    • Lara, Óscar D., et al. "Centinela: A human activity recognition system based on acceleration and vital sign data." Pervasive and mobile computing 8. 5(2012):717-729.
    • (2012) Pervasive and Mobile Computing , vol.8 , Issue.5 , pp. 717-729
    • Lara, O.D.1
  • 28
    • 35448935844 scopus 로고    scopus 로고
    • Towards activity databases: Using sensors and statistical models to summarize people's lives
    • Choudhury, Tanzeem, et al. "Towards Activity Databases: Using Sensors and Statistical Models to Summarize People's Lives." IEEE Data Eng. Bull. 29. 1(2006):49-58.
    • (2006) IEEE Data Eng. Bull , vol.29 , Issue.1 , pp. 49-58
    • Choudhury, T.1
  • 30
    • 84904159626 scopus 로고    scopus 로고
    • Energy-efficient motion related activity recognition on mobile devices for pervasive healthcare
    • Liang, Yunji, et al. "Energy-efficient motion related activity recognition on mobile devices for pervasive healthcare." Mobile Networks and Applications 19. 3(2014):303-317.
    • (2014) Mobile Networks and Applications , vol.19 , Issue.3 , pp. 303-317
    • Liang, Y.1
  • 31
    • 84907494332 scopus 로고    scopus 로고
    • A lightweight hierarchical activity recognition framework using smartphone sensors
    • Han, Manhyung, et al. "A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors." Sensors 14. 9(2014):16181-16195.
    • (2014) Sensors , vol.14 , Issue.9 , pp. 16181-16195
    • Han, M.1
  • 32
    • 84921506826 scopus 로고    scopus 로고
    • A survey of online activity recognition using mobile phones
    • Shoaib, Muhammad, et al. "A survey of online activity recognition using mobile phones." Sensors 15. 1(2015):2059-2085.
    • (2015) Sensors , vol.15 , Issue.1 , pp. 2059-2085
    • Shoaib, M.1
  • 34
    • 23844513274 scopus 로고    scopus 로고
    • A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes
    • Dejnabadi, Hooman, Brigitte M. Jolles, and Kamiar Aminian. "A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes." Biomedical Engineering, IEEE Transactions on 52. 8(2005):1478-1484.
    • (2005) Biomedical Engineering, IEEE Transactions on , vol.52 , Issue.8 , pp. 1478-1484
    • Dejnabadi, H.1    Jolles, B.M.2    Aminian, K.3
  • 36
    • 84880762436 scopus 로고    scopus 로고
    • A hybrid discriminative/generative approach for modeling human activities
    • Lester, Jonathan, et al. "A Hybrid Discriminative/Generative Approach for Modeling Human Activities." IJCAI. Vol. 5. 2005.
    • (2005) IJCAI , vol.5
    • Lester, J.1
  • 37
    • 35048842427 scopus 로고    scopus 로고
    • Activity recognition from userannotated acceleration data
    • Springer Berlin Heidelberg
    • Bao, Ling, and Stephen S. Intille. "Activity recognition from userannotated acceleration data." Pervasive computing. Springer Berlin Heidelberg, 2004. 1-17.
    • (2004) Pervasive Computing , pp. 1-17
    • Bao, L.1    Intille, S.S.2
  • 39
    • 84895062880 scopus 로고    scopus 로고
    • Dynamic sensor data segmentation for realtime knowledge-driven activity recognition
    • Okeyo, George, et al. "Dynamic sensor data segmentation for realtime knowledge-driven activity recognition. " Pervasive and Mobile Computing 10(2014):155-172.
    • (2014) Pervasive and Mobile Computing , vol.10 , pp. 155-172
    • Okeyo, G.1
  • 40
    • 84895057009 scopus 로고    scopus 로고
    • Activity recognition on streaming sensor data
    • Krishnan, Narayanan C., and Diane J. Cook. "Activity recognition on streaming sensor data." Pervasive and mobile computing 10(2014):138-154.
    • (2014) Pervasive and Mobile Computing , vol.10 , pp. 138-154
    • Krishnan, N.C.1    Cook, D.J.2
  • 41
    • 84863126954 scopus 로고    scopus 로고
    • Multisensor data fusion for physical activity assessment
    • Liu, Shaopeng, et al. "Multisensor data fusion for physical activity assessment." Biomedical Engineering, IEEE Transactions on 59. 3(2012):687-696.
    • (2012) Biomedical Engineering, IEEE Transactions on , vol.59 , Issue.3 , pp. 687-696
    • Liu, S.1
  • 45
    • 33744527362 scopus 로고    scopus 로고
    • Classification of gait patterns in the time-frequency domain
    • Nyan, M. N., et al. "Classification of gait patterns in the time-frequency domain. " Journal of biomechanics 39. 14(2006):2647-2656.
    • (2006) Journal of Biomechanics , vol.39 , Issue.14 , pp. 2647-2656
    • Nyan, M.N.1
  • 46
    • 0003123930 scopus 로고    scopus 로고
    • Forecasting with artificial neural networks:: The state of the art
    • Zhang, Guoqiang, B. Eddy Patuwo, and Michael Y. Hu. "Forecasting with artificial neural networks:: The state of the art." International journal of forecasting 14. 1(1998):35-62..
    • (1998) International Journal of Forecasting , vol.14 , Issue.1 , pp. 35-62
    • Zhang, G.1    Eddy Patuwo, B.2    Hu, M.Y.3
  • 47
    • 70350115240 scopus 로고    scopus 로고
    • An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer
    • Staudenmayer, John, et al. "An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer." Journal of Applied Physiology 107. 4(2009):1300-1307.
    • (2009) Journal of Applied Physiology , vol.107 , Issue.4 , pp. 1300-1307
    • Staudenmayer, J.1
  • 48
    • 0000747663 scopus 로고    scopus 로고
    • Maximum entropy markov models for information extraction and segmentation
    • McCallum, Andrew, Dayne Freitag, and Fernando CN Pereira. "Maximum Entropy Markov Models for Information Extraction and Segmentation. " ICML. Vol. 17. 2000.
    • (2000) ICML , vol.17
    • McCallum, A.1    Freitag, D.2    Pereira, F.C.N.3
  • 51
    • 85037974473 scopus 로고    scopus 로고
    • Activity recognition using hierarchical hidden markov models on a smartphone with 3D accelerometer
    • Springer Berlin Heidelberg
    • Lee, Young-Seol, and Sung-Bae Cho. "Activity recognition using hierarchical hidden markov models on a smartphone with 3D accelerometer." Hybrid Artificial Intelligent Systems. Springer Berlin Heidelberg, 2011. 460-467.
    • (2011) Hybrid Artificial Intelligent Systems , pp. 460-467
    • Lee, Y.-S.1    Cho, S.2
  • 53
    • 84870866072 scopus 로고    scopus 로고
    • Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine
    • Springer Berlin Heidelberg
    • Anguita, Davide, et al. "Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine." Ambient assisted living and home care. Springer Berlin Heidelberg, 2012. 216-223.
    • (2012) Ambient Assisted Living and Home Care , pp. 216-223
    • Anguita, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.