Human Movement Analysis Group

Objective

The main objective is to understand various aspects of human movement. Specifically, the goals include

  • Study different application areas of human movement such as activities of daily living (rehabilitation, health care etc), sports, e-sports, strength training, and performance arts
  • Design and implement activities based experiments in controlled but realistic environments
  • Development of biosignals and other datasets corresponding to human movements and related activities
  • Identify and study different research questions on human movement based on practical importance and the available datasets
Faculty

Principal Investigator: Dr. Anish Chand Turlapaty

Collaborators:

  • Mainak Thakur
  • Himangsu Sharma
  • Mrinmoy Ghorai
  • Balakrishna Gokaraju(North Carolina A & T State University)
  • Shiv Ram Dubey (IIIT Allahabad)
  • Rakesh Kumar Sanodiya (IIITDM, Jabalpur)
Sponsored Projects

Project Title:

EMGNet: Development of Deep Learning Based Model for Hand Movements Classification using SurfaceEMG Signals

Agency: Science and Engineering Research Board, Department of Science and Technology, Govt. of India

Period: 2 years, Feb 2020 – Feb 2022

Value: 34.06 Lakhs

PI/Co PI: Anish Chand T

Co PI 1: Dr. Shiv Ram Dubey, IIITS

Co PI 2: Dr. Balakrishna Gokaraju, North Carolina A & T State University

Status: Completed

Publications

Journals:

  • D. Kusuru, A. C. Turlapaty and M. Thakur, "An Improved Compound Gaussian Model for Bivariate Surface EMG Signals Related to Strength Training," in IEEE Transactions on Human-Machine Systems, doi: 10.1109/THMS.2024.3486450.
  • N. K. Karnam, A. C. Turlapaty, S. R. Dubey and B. Gokaraju, "EMAHA-DB1: A New Upper Limb sEMG Dataset for Classification of Activities of Daily Living," in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-11, 2023, Art no. 4007411, doi: 10.1109/TIM.2023.3279873.
  • Almalki A, Gokaraju B, Acquaah Y, Turlapaty A. Regression Analysis for COVID-19 Infections and Deaths Based on Food Access and Health Issues. Healthcare. 2022; 10(2):324. https://doi.org/10.3390/healthcare10020324
  • N. Kumar, S. R. Dubey, A. C. Turlapaty and B. Gokaraju, EMGHandNet: A Hybrid CNN and Bi-LSTM Architecture for Hand Activity Classification using Surface EMG Signals, Biocybernetics and Biomedical Engineering,  vol42, no. 1, pp. 325 - 340, 10.1016/j.bbe.2022.02.005.
  • N. Kumar, A. C. Turlapaty,  S. R. Dubey,  and B. Gokaraju "Classification of sEMG Signals of Hand Gestures based on Energy Features," Biomedical Signal Processing and Control, Volume 70, 102948, 2021, https://doi.org/10.1016/j.bspc.2021.102948
  • A. C. Turlapaty, "Variational Bayesian Estimation of Statistical Properties of Composite Gamma Log-Normal Distribution," in IEEE Transactions on Signal Processing, vol. 68, pp. 6481-6492, 2020, doi: 10.1109/TSP.2020.3037397
  • A. C. Turlapaty and B. Gokaraju, "Feature Analysis for Classification of Physical Actions Using Surface EMG Data," in IEEE Sensors Journal, vol. 19, no. 24, pp. 12196-12204, 15 Dec.15, 2019, doi: 10.1109/JSEN.2019.2937979. IEEE-SENSORS

Conferences:

  • Kareemulla, A., A., Sanodyia, R. K., Turlapaty, A. C., Naidu, S. 2024, EMGTTL : Transformers-Based Transfer Learning for Classification of ADL using Raw Surface EMG Signals, 7th IEEE PuneCon 2024, Pune, India.
  • S. Sreenivas, A. Turlapaty, S. Naidu and V. Sagar, "Impact of Activity Pace and Arm Position on Classification of ADLs," 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2024, pp. 1-4, doi: 10.1109/EMBC53108.2024.10782913.
  • Prajapathi, V., Turlapaty, A., Sharma H., Ghorai, M., Relating Muscle Activity and Mouse Sensitivity in FPS Game Players Using Surface EMG Signals, accepted at iBiomed 2024, Batung Bali Resort, Indonesia
  • Naidu, S.; Turlapaty, A. and Sagar, V. (2024). Classification of Fine-ADL Using sEMG Signals Under Different Measurement Conditions. Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS; ISBN 978-989-758-688-0; ISSN 2184-4305, SciTePress, pages 591-598. DOI: 10.5220/0012346000003657
  • A. G. Eswar, Anish C. Turlapaty, Surya Naidu, Fatigue Classification and Onset Estimation Using Surface EMG Signals During Strength Training, Accepted At APSIPA ASC 2023, TICC, TAIPEI, TAIWAN.
  • V. Sagar, A. C. Turlapaty, S. Naidu, Impact of Measurement Conditions on Classification of ADL using Surface EMG signals, IEEE 13th Int'l Symposium on Image and Signal Processing and Analysis (ISPA 2023), Rome, Italy.
  • K. Bhagyasree and Anish C. Turlapaty, A Hierarchical Approach for Decoding Human Reach-and-Grasp Activities based on EEG Signals, IEEE SPCOM 2022, IISc, Bangalore
  • S. K. C. Tallapragada, A. C. Turlapaty, B. Gokaraju and E. Sarku, "Optimal Features for Cross Subject Classification of Imagined Left and Right Fist Movements using EEG Signals," 2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2021, pp. 1-5, doi: 10.1109/AIPR52630.2021.9762123.
  • B. Kanuparthi, A. C. Turlapaty and B. Gokaraju, "An Ensemble Approach for Classification of Reach and Grasp Movements based on EEG Signals," 2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2021, pp. 1-6, doi: 10.1109/AIPR52630.2021.9762070.
  • D. Kusuru, A. C. Turlapaty and M. Thakur, "A Laplacian-Gaussian Mixture Model for Surface EMG Signals from Upper Limbs," 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 681-685, doi: 10.1109/EMBC46164.2021.9630143.
  • Nagaswathi Amancherla, Anish Turlapaty, and Balakrishna Gokaraju. 2019. SVM based Classification Of sEMG Signals using Time Domain Features for the Applications towards Arm Exoskeletons. In Proceedings of the Advances in Robotics 2019 (AIR 2019). Association for Computing Machinery, New York, NY, USA, Article 26, 1–5. https://doi.org/10.1145/3352593.3352620
  • N. Amamcherla, A. Turlapaty and B. Gokaraju, "A Machine Learning System for Classification of EMG Signals to Assist Exoskeleton Performance," 2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2018, pp. 1-4, doi: 10.1109/AIPR.2018.8707426.. AIPR
Patents (if any) : None
Other Prominent Details:

a) Seven publicly available datasets on electromyography signals have been released and are available on Kaggle.

b) Workshop on Advances in statistical data analysis and modeling WASDAM-2022,

  • Convenor - Dr. Anish Chand Turlapaty
  • Co-convenor - Dr. Mainak Thakur

c) PhD Scholars:

  •  Naveen Kumar K: PhD Awarded 11 Jan 2023 Topic: Machine Learning Architectures For Classification Of Human Hand Activities Based On Surface Electromyography Signals
  •  Durgesh: Published 1 Journal paper in IEEE THMS and waiting for review decision for second paper Topic: Compound Gaussian modeling of sEMG signal strength during strength training and its applications

d) Alumni (Honors students)

  • S. Surya Naidu, 2024(IIITS), Current/most recent status: Graduate student at John Hopkins University, Baltimore, Maryland, US Honors topic: Classification of Fine-ADL Using sEMG Signals Under Different Measurement Conditions
  • G. S. Eswar, 2024 (IIITS) Current/most recent status: Employee at Infinity Analytics  Honors Topic:  Fatigue Classification and Onset Estimation Using Surface EMG Signals During Strength Training
  • V. Vidya Sagar, 2024 (IIITS), Current/most recent status: Graduate student at University of Southern California, Los Angeles, California, US Honors topic: Impact of Measurement Conditions on Classification of ADL using Surface EMG signals
  • T.S.K. Charitha, 2021 (IIITS), Current/most recent status: M.Tech from IIT Kanpur, Honors Topic: Cognitive Brain Computer Interface For Motor Imagery
  • C. Naga Siva Krishna, 2020 (IIITS), Current/most recent status: Researcher at Mercedes Benz India Honors Topic: Navigation, Localisation and Mapping of robot