Abstract
This paper is intended to present a smart posture recognition and correction system. In specific, Sitting in wrong posture for persistent period of time results in many health problems such as back pain, soreness, poor circulation, cervical pains and also decrease in eyesight in the long run. The proposed model makes use of real time skeletal points extraction. This system is based on computer vision and machine learning algorithms.
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References
Cheng H, Luo H, Zhao F (2011) A fall detection algorithm based on pattern recognition and human posture analysis, Proceedings of ICCTA
Stoble JB, Seeraj M (2015) Multi-posture human detection based on hybrid HOG-BO feature, 2015 Fifth international conference on advances in computing and communication, pp 37–40
Miljkoviü N, Bijeliü G, Garcia GA, Mirjana B (2011) Popoviü.: Independent component analysis of EMG for posture detection: sensitivity to variation of posture properties. 19th Telecommunications forum TELFOR 2011, pp 47–50
Lee HJ, Hwang SH, Lee SM, Lim YG, Park KS (2013) Estimation of body postures on bed using unconstrained ECG measurements. IEEE J Biomed Health Inform 17(6):985–993 (2013)
Matsumoto M, Takano K (2016) A posture detection system using consumer wearable sensors. 10th international conference on complex, intelligent, and software intensive systems
Wahabi S, Pouryayevali S, Hatzinakos D (2015) Posture-invariant ECG recognition with posture detection, ICASSP 2015, pp 1812–1816
Tan TD, Tinh NV (2014) Reliable fall detection system using an 3-DOF accelerometer and cascade posture recognitions, APSIPA
Ni W, Gao Y, Lucev Z, Pun SH, Cifrek M, Vai MI, Du M (2016) Human posture detection based on human body communication with muti-carriers modulation, MIPRO 2016, Opatija, Croatia, pp 273–276
Yi WJ, Saniie J (2014) Design flow of a wearable system for body posture assessment and fall detection with android smartphone, 2014 IEEE international technology management conference
Terrillon JC, Pilpré A, Niwa Y, Yamamoto K, DRUIDE: A real-time system for robust multiple face detection, tracking and hand posture recognition in color video sequences. 17th international conference on pattern recognition (ICPR’04)
Chopra S, Kumar M, Sood S (2016) Wearable posture detection and alert system. 5th international conference on system modeling & advancement in research trends, pp 130–134
Bei S, Xing Z, Taocheng L, Qin L (2017) Sitting posture detection using adaptively fused 3D features. 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp 1073–1077
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Raju, J.B.V.P., Reddy, Y.C., G, P.R. (2020). Smart Posture Detection and Correction System Using Skeletal Points Extraction. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-24322-7_23
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DOI: https://doi.org/10.1007/978-3-030-24322-7_23
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Online ISBN: 978-3-030-24322-7
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