A framework for early event detection for wearable systems

ISWC 2015 - Proceedings of the 2015 ACM International Symposium on Wearable Computers

Volumn , Issue , 2015, Pages 109-112

  Dorschky, Eva ^a   Schuldhaus, Dominik ^a   Koerger, Harald ^b   Eskofier, Bjoern M ^a  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b Ait Research   (Germany)

Author keywords

Early event detection; Hybrid HMM; Wearable systems

Indexed keywords

CHEMICAL DETECTION; HIDDEN MARKOV MODELS; MARKOV PROCESSES; SPORTS; UNITS OF MEASUREMENT; WEARABLE COMPUTERS;

EARLY EVENT DETECTION; EPILEPTIC SEIZURES; HYBRID HMM; INERTIAL MEASUREMENT UNIT; LEAD TIME; MONITORING SYSTEM; SPORTS EVENTS; WEARABLE SYSTEMS;

WEARABLE TECHNOLOGY;

EID: 84960453099     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2802083.2808389     Document Type: Conference Paper

References (10)

1. Ellis, C., Masood, S. Z., Tappen, M. F., Laviola Jr, J. J., and Sukthankar, R. Exploring the Trade-off Between Accuracy and Observational Latency in Action Recognition. IJCV 101, 3(2013), 420-436.
2. Gradl, S., Kugler, P., Lohmuller, C., and Eskofier, B. Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices. In Proc. EMBC, IEEE (2012), 2452-2455.
3. Hoai, M., and Torre, F. D. L. Max-Margin Early Event Detectors. IJCV, November 2013, 191-202.
4. Junker, H., Amft, O., Lukowicz, P., and Tröster, G. Gesture spotting with body-worn inertial sensors to detect user activities. Int. J. Pattern Recogn. 41, 6(2008), 2010-2024.
5. Lees, A., and Nolan, L. Three-dimensional kinematic analysis of the instep kick under speed and accuracy conditions. Science and football IV (2002), 16-21.
6. Lester, J., Choudhury, T., Kern, N., Borriello, G., and Hannaford, B. A Hybrid Discriminative/Generative Approach for Modeling Human Activities. In Proc. IJCAI, vol. 5(2005), 766-772.
7. Poh, M.-Z., Loddenkemper, T., Reinsberger, C., Swenson, N. C., Goyal, S., Sabtala, M. C., Madsen, J. R., and Picard, R. W. Convulsive seizure detection using a wrist-worn electrodermal activity and accelerometry biosensor. Epilepsia 53, 5(2012), e93-e97.
8. Ring, M., Jensen, U., Kugler, P., and Eskofier, B. Software-based performance and complexity analysis for the design of embedded classification systems. In Proc. ICPR, IEEE (2012), 2266-2269.
9. Tong, L., Song, Q., Ge, Y., and Liu, M. HMM-based Human Fall Detection and Prediction Method Using Tri-Axial Accelerometer. Sensors J., IEEE 13, 5(2013), 1849-1856.
10. Zanfir, M., Leordeanu, M., and Sminchisescu, C. The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection. In Proc. ICCV, IEEE (2013), 2752-2759.