A framework for daily activity monitoring and fall detection based on surface electromyography and accelerometer signals

IEEE Journal of Biomedical and Health Informatics

Volumn 17, Issue 1, 2013, Pages 38-45

  Cheng, Juan ^a   Chen, Xiang ^a   Shen, Minfen ^b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b SHANTOU UNIVERSITY   (China)

Author keywords

Activity awareness; Entropy; Fall detection; Surface electromyography (SEMG)

Indexed keywords

ACCELEROMETERS; ENTROPY;

ACCELEROMETER SIGNALS; ACTIVITY AWARENESS; DAILY ACTIVITY MONITORING; DYNAMIC TRANSITIONS; FALL DETECTION; RECOGNITION ACCURACY; SURFACE ELECTROMYOGRAPHY; TRANSITION ACTIVITY;

HIDDEN MARKOV MODELS;

ACCELEROMETRY; ADULT; AMBULATORY MONITORING; BODY POSTURE; DAILY LIFE ACTIVITY; ELECTROMYOGRAPHY; FALLING; FEMALE; HUMAN; MALE; MEDICAL INFORMATICS; PHYSIOLOGY; PROBABILITY; PROCEDURES;

ACCELEROMETRY; ACCIDENTAL FALLS; ACTIVITIES OF DAILY LIVING; ADULT; ELECTROMYOGRAPHY; FEMALE; HUMANS; MALE; MARKOV CHAINS; MEDICAL INFORMATICS APPLICATIONS; MONITORING, AMBULATORY; POSTURE;

EID: 84899604248     PISSN: 21682194     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2012.2226905     Document Type: Article

References (51)

1. B. Schilit, N. Adams, and R. Want, "Context-aware computing application," Mobile Comput. Syst. Appl., vol. 8, pp. 85-90, Dec. 1994.
2. A. K. Dey, "Understanding and using context," Pers. Ubiquitous Comput., vol. 5, pp. 4-7, 2001.
3. R. Tesoriero, J. A. Gallud, M. D. Lozano, and V. M. R. Penichet, "CAUCE: Model-driven development of context-aware applications for ubiquitous computing environments," J. Universal Comput. Sci., vol. 16, pp. 2111-2138, 2010.
4. J. Yin, Q. Yang, and J. J. Pan, "Sensor-based abnormal human-activity detection," IEEE Trans. Knowl. Data Eng., vol. 20, no. 8, pp. 1082-1090, Aug. 2008.
5. O. Thomas, P. Sunehag, G. Dror, S. Yun, S. Kim, M. Robards, A. Smola, D. Green, and P. Saunders, "Wearable sensor activity analysis using semi-Markov models with a grammar," Pervasive Mob. Comput., vol. 6, pp. 342-350, 2010.
6. S. H. Roy, M. S. Cheng, S. S. Chang, J. Moore, G. De Luca, S. H. Nawab, and C. J. De Luca, "A combined sEMG and accelerometer system for monitoring functional activity in stroke," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 17, no. 6, pp. 585-594, Dec. 2009.
7. F. Hijaz, N. Afzal, T. Ahmad, and O. Hasan, "Survey of fall detection and daily activity monitoring techniques," in Proc. 2nd Int. Conf. Inf. Emerg. Technol., Jun. 14-16, 2010, pp. 1-6.
8. C. N. Huang, C. Y. Chiang, G. C. Chen, S. J. Hsu, W. C. Chu, and C. T. Chan, "Fall detection system for healthcare quality improvement in residential care facilities," J. Med. Biol. Eng., vol. 30, pp. 247-252, 2010.
9. M. E. Pollack, "Intelligent technology for an aging population: The use of AI to assist elders with cognitive impairment," AI Mag., vol. 26, no. 2, pp. 9-24, 2005.
10. T. Stiefmeier, G. Ogris, H. Junker, P. Lukowicz, and G. Troster, "Combining motion sensors and ultrasonic hands tracking for continuous activity recognition in a maintenance scenario," in Proc. 10th IEEE Int. Symp. Wearable Comput., 2006, pp. 97-104.
11. P. Turaga, R. Chellappa, V. S. Subrahmanian, and O. Udrea, "Machine recognition of human activities: a survey," IEEE Trans. Circuits Syst. Video Technol., vol. 18, no. 11, pp. 1473-1488, Nov. 2008.
12. C. Zhu and W. H. Sheng, "Wearable sensor-based hand gesture and daily activity recognition for robot-assisted living," IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 41, no. 3, pp. 569-573, May 2011.
13. G. Wu and S. W. Xue, "Portable preimpact fall detector with inertial sensors," IEEE Trans. Neural Syst. Rehabil. Eng., vol. 16, no. 2, pp. 178-183, Apr. 2008. (Pubitemid 351519530)
14. H. Ghasemzadeh, R. Jafari, and B. Prabhakaran, "A body sensor network with electromyogram and inertial sensors: Multimodal interpretation of muscular activities," IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 2, pp. 198-206, Mar. 2010.
15. N. Vaswani, A. K. Roy-Chowdhury, and R. Chellappa, "Shape activity: A continuous-state HMM for moving/deforming shapes with application to abnormal activity detection," IEEE Trans. Image Process., vol. 14, no. 10, pp. 1603-1616, Oct. 2005. (Pubitemid 41623090)
16. R. Poppe, "A survey on vision-based human action recognition," Image Vision Comput., vol. 28, pp. 976-990, Jun. 2010.
17. M. Popescu, Y. Li, M. Skubic, and M. Rantz, "An acoustic fall detector system that uses sound height information to reduce the false alarm rate," in Proc. 30th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2008, vol. 1-8, pp. 4628-4631.
18. J. A. Ward, P. Lukowicz, G. Troster, and T. E. Starner, "Activity recognition of assembly tasks using body-worn microphones and accelerometers," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 10, pp. 1553-1567, Oct. 2006.
19. L. Bao and S. S. Intille, "Activity recognition from user-annotated acceleration data," in Proc. Pervasive Comput., 2004, vol. 3001, pp. 1-17.
20. Q. Li, J. A. Stankovic, M. A. Hanson, A. T. Barth, J. Lach, and G. Zhou, "Accurate, fast fall detection using gyroscopes and accelerometer-derived posture information," in Proc. 6th Int. Workshop Wearable Implantable Body Sens. Netw., 2009, pp. 138-143.
21. U. Maurer, A. Smailagic, D. P. Siewiorek, and M. Deisher, "Activity recognition and monitoring using multiple sensors on different body positions," in Proc. Int. Workshop Wearable Implantable Body Sens. Netw., 2006, pp. 113-116.
22. D. M. Karantonis, M. R. Narayanan, M. Mathie, N. H. Lovell, and B. G. Celler, "Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring," IEEE Trans. Inf. Technol. Biomed., vol. 10, no. 1, pp. 156-167, Jan. 2006. (Pubitemid 43092328)
23. J. H. Park, H. J. Kim, and S. J. Kang, "Validation of the AMP331 monitor for assessing energy expenditure of free-living physical activity," Res. Quarterly Exercise Sport, vol. 77, Mar. 2006.
24. M. J. Mathie, A. C. F. Coster, N. H. Lovell, B. G. Celler, S. R. Lord, and A. Tiedemann, "A pilot study of long-term monitoring of human movements in the home using accelerometry," J. Telemed. Telecare, vol. 10, pp. 144-151, 2004. (Pubitemid 38901253)
25. S. Abbate, M. Avvenuti, P. Corsini, J. Light, and A. Vecchio, "Monitoring of human movements for fall detection and activities recognition in elderly care using wireless sensor network: A survey," Wireless Sens. Netw.: Appl.-Centric Design, pp. 1-22, Dec. 2010.
26. J. T. Perry, S. Kellog, S. M. Vaidya, J. H. Youn, H. Ali, and H. Sharif, "Survey and evaluation of real-time fall detection approaches," in Proc. 6th Int. Symp. High Capacity Opt. Netw. Enabling Technol., 2009, pp. 158-164.
27. A. K. Bourke, J. V. O'Brien, and G. M. Lyons, "Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm," Gait Posture, vol. 26, pp. 194-199, Jul. 2007.
28. N. Noury, A. Fleury, P. Rurneau, A. K. Bourke, G. Laighin, V. Rialle, and J. E. Lundy, "Fall detection - principles and methods," in Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2007, vol. 1-16, pp. 1663-1666.
29. T. Zhang, J. Wang, L. Xu, and P. Liu, "Fall detection by wearable sensor and one-class SVM algorithm," Intell. Comput. Signal Process. Pattern Recognit., vol. 345, pp. 858-863, 2006. (Pubitemid 44421654)
30. G. Y. Shi, Y. X. Zou, Y. F. Jin, X. L. Cui, and W. J. Li, "Towards HMM based human motion recognition using MEMS inertial sensors," in Proc. IEEE Int. Conf. Rob. Biomimetics, 2009, vol. 1-4, pp. 1762-1766.
31. C.-C. Yang and Y.-L. Hsu, "Algorithm design for real-time physical activity identification with accelerometry measurement," in Proc. 33rd Annu. Conf. IEEE Ind. Electron. Soc., 2007, vol. 1-3, pp. 2996-3000.
32. E. M. Tapia and S. S. Intille, "Real-time recognition of physical activities and their intensities using wireless accelerometers and a heart rate monitor," in Proc. 11th IEEE Int. Symp. Wearable Comput., 2007, pp. 37-40.
33. L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol. 77, no. 2, pp. 257-286, Feb. 1989.
34. J. Kim, J. Wagner, M. Rehm, and E. Andre, "Bi-channel sensor fusion for automatic sign language recognition," in Proc. 8th IEEE Int. Conf. Autom. Face Gesture Recognit., 2008, vol. 1-2, pp. 647-652.
35. P. Konrad, The ABC of EMG, Version 1.0, Apr. 2005.
36. X. Zhang, X. Chen, Y. Li, V. Lantz, K. Wang, and J. Yang, "A framework for hand gesture recognition based on accelerometer and EMG sensors," IEEE Trans. Syst., Man, Cybern. Part A, Syst. Humans, vol. 41, no. 6, pp. 1064-1076, Nov. 2011.
37. R. Z. Chen, W. Chen, X. A. Chen, X. Zhang, and Y. W. Chen, "Sensing strides using EMG signal for pedestrian navigation," GPS Solutions, vol. 15, pp. 161-170, Apr. 2011.
38. X. Zhang, X. Chen, and Z. Y. Zhao, "Research on gesture definition and electrode placement in pattern recognition of hand gesture action SEMG," presented at the 1st Int. Conf. Med. Biometrics, Hong Kong, Jan. 04-05, 2007.
39. Y. Huang, K. Englehart, B. Hudgins, and A. D. C. Chan, "A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses," IEEE Trans. Biomed. Eng., vol. 52, no. 11, pp. 1801-1811, Nov. 2005. (Pubitemid 41578800)
40. J. F. Bercher and C. Vignat, "Estimating the entropy of a signal with applications," IEEE Trans. Signal Process., vol. 48, no. 6, pp. 1687-1694, Jun. 2000.
41. M. Kaufman, U. Zurcher, and P. S. Sung, "Entropy of electromyography time series," Phys. A: Statist. Mech. Appl., vol. 386, pp. 698-707, Dec. 15, 2007.
42. A. Chakrabarti, K. Do Ba, and S. Muthukrishnan, "Estimating entropy and entropy norm on data streams," in Proc. Symp. Theoretical Aspects Comput. Sci., 2006, vol. 3884, pp. 196-205.
43. X. Zhang, X. Chen, W. Wang, J. Yang, V. Lantz, and K. Wang, "Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors," in Proc. 13th Int. Conf. Intell. User Interfaces, 2009, pp. 401-406.
44. S. Zhong and J. Ghosh, "HMMs and coupled HMMs for multi-channel EEG classification," in Proc. Int. Joint Conf. Neural Netw., 2002, vol. 1-3, pp. 1154-1159. (Pubitemid 34647790)
45. H. Manabe and Z. Zhang, "Multi-stream HMM for EMG-based speech recognition," in Proc. 26th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2004, vol. 2, pp. 4389-4392.
46. W. H. Wang, X. A. Chen, K. Q. Wang, X. Zhang, and J. H. Yang, "Dynamic gesture recognition based on multiple sensors fusion technology," in 31st Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2009, vol. 1-20, pp. 7014-7017.
47. P. Jantaraprim, P. Phukpattaranont, C. Limsakul, and B. Wongkittisuksa, "Evaluation of fall detection for the elderly on a variety of subject groups," in Proc. 3rd Int. Convention Rehabil. Eng. Assistive Technol., 2009.
48. M. R. Narayanan, S. R. Lord, M. M. Budge, B. G. Celler, and N. H. Lovell, "Falls management: Detection and prevention, using a waistmounted triaxial accelerometer," in Proc. 29th Int. Conf. IEEE Eng. Med. Biol. Soc., 2007, vol. 1-16, pp. 4037-4040.
49. T. Zhang, J. Wang, P. Liu, and J. Hou, "Fall detection by embedding an accelerometer in cellphone and using KFD algorithm," Int. J. Comput. Sci. Network Secur., vol. 6, no. 10, Oct. 2006.
50. J.-Y. Yang, Y.-P. Chen, G.-Y. Lee, S.-N. Liou, and J.-S. Wang, "Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction," in Entertainment Computing, vol. 4740, Berlin, Germany: Springer, 2007, pp. 395-400.
51. S. Mitra and T. Acharya, "Gesture recognition: A survey," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 37, no. 3, pp. 314-324, May 2007.