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SPECIAL SESSION ON RECENT ADVANCES IN COMPUTATIONAL INTELLIGENCE & TECHNOLOGYS (SS_10_RACIT)

Development of Generic Human Motion Simulation Categorization using Inception based CNN

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Proceedings of Third International Conference on Computing, Communications, and Cyber-Security

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 421))

Abstract

Generic human motion is the steps taken by the person for everyday movement. In this paper, the generic framework has been proposed for gait activity recognition using the inception-based convolutional neural network (CNN) model. The gait pattern is a compound of seven sub-phases. However, sequential execution of these seven sub-phases of left and right legs is called gait cycle. Gait features are used to perform the biometric, biomechanics, and human psychology analysis of human beings. Human walking is very challenging to measure due to high variability. It depends on age, gender, walking terrain, walking speed, mental condition, health condition, etc. The analysis of human gait helps identify human activities, diagnose many gait-related diseases like Parkinson’s and freezing of gait. Due to variability of gait, biometric is difficult to spool. This paper covers to analyzing the existing available wireless sensor data mining (WISDM) dataset and our gait dataset of human activity (GDOHA) dataset and evaluating the performance. Moreover, we compare performance metrics on datasets applying machine learning and deep learning algorithms. The result achieved 99.03% accuracy using the inception-based CNN model. The proposed computational model helps to early detection of gait abnormality and provides the proper mechanism for recovery from abnormal gait.

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Funding

This work is supported by SERB, DST of government of India under Early Career Award with DST NO: ECR/2018/000203 ECR dated June 04, 2019.

Author information

Authors and Affiliations

  1. Amity University Gwalior, Gwalior, India

    Ram Kumar Yadav & Subhrendu Guha Neogi

  2. MANIT Bhopal, Bhopal, India

    Vijay Bhaskar Semwal

Authors
  1. Ram Kumar Yadav
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  2. Subhrendu Guha Neogi
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  3. Vijay Bhaskar Semwal
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Corresponding author

Correspondence to Ram Kumar Yadav .

Editor information

Editors and Affiliations

  1. Department of Computer Science, KIET Group of Institutions, Ghaziabad, Delhi, India

    Pradeep Kumar Singh

  2. Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland

    Sławomir T. Wierzchoń

  3. Department of Computer Science and Engineering, Nirma University, Ahmedabad, India

    Sudeep Tanwar

  4. Federal University of PiauĂ­, Teresina, Brazil

    Joel J. P. C. Rodrigues

  5. Faculty of Mathematics and Informatics, Warsaw University of Technology, Warsaw, Poland

    Maria Ganzha

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Yadav, R.K., Neogi, S.G., Semwal, V.B. (2023). SPECIAL SESSION ON RECENT ADVANCES IN COMPUTATIONAL INTELLIGENCE & TECHNOLOGYS (SS_10_RACIT). In: Singh, P.K., Wierzchoń, S.T., Tanwar, S., Rodrigues, J.J.P.C., Ganzha, M. (eds) Proceedings of Third International Conference on Computing, Communications, and Cyber-Security. Lecture Notes in Networks and Systems, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-19-1142-2_47

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  • DOI: https://doi.org/10.1007/978-981-19-1142-2_47

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1141-5

  • Online ISBN: 978-981-19-1142-2

  • eBook Packages: EngineeringEngineering (R0)

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