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Rule based classification of neurodegenerative diseases using data driven gait features

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Abstract

Classification of neurodegenerative diseases (NDD) like Parkinson’s disease (PD), Amyotrophic Lateral Sclerosis (ALS), and Huntington’s disease (HD) is of high clinical importance. The gait analysis based classification is attractive due to its simplicity and noninvasiveness. In this paper, we propose a data driven features approach along with autocorrelation and cross correlation between gait time series to create different feature set for a sample representation. Further, a rule based classifier using Decision Tree is trained with those features to classify the neurodegenerative diseases from healthy controls. Mutual Information (MI) analysis revealed the dominance of data driven features over auto and cross correlation based features. The classifier fed with top 500 features could produce the classification accuracy of 88.5%, 92.3%, and 96.2% for HD vs. control, PD vs. Control, and ALS vs. control. Pooling all neurodegenerative samples into one as NDD class and applying current approach produced nearly 87.5% of accuracy for NDD vs. control. Finally, we validated the present approach for a challenging situation of classification of less severe patients and observed respectable accuracies of 80%, 80%, 90%, and 73.33% for HD vs. control, PD vs. Control, and ALS vs. control, and NDD vs. control, respectively. The proposed algorithm shows potential for rule based classification system in data driven features for Neurodegenerative disease classification.

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Notes

  1. Online available at http://www.physionet.org/physiobank/database/gaitndd/

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Acknowledgements

We thank Prof. Vinay Goyal (Professor, Department of Neurology, Neuroscience Centre, AIIMS, New Delhi) for guiding us with his valuable suggestions while preparing the manuscript.

Funding

This study was not funded by any of the agency.

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Authors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology Delhi, New Delhi, India

    Kartikay Gupta & Niladri Chatterjee

  2. Center for Biomedical Engineering and Department of Biomedical Engineering, Indian Institute of Technology Delhi and All India Institute of Medical Sciences (AIIMS), New Delhi, India

    Aayushi Khajuria & Deepak Joshi

  3. School of Business, Quantum University, Roorkee, India

    Pradeep Joshi

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  1. Kartikay Gupta
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  2. Aayushi Khajuria
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  4. Pradeep Joshi
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  5. Deepak Joshi
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Correspondence to Deepak Joshi.

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Gupta, K., Khajuria, A., Chatterjee, N. et al. Rule based classification of neurodegenerative diseases using data driven gait features. Health Technol. 9, 547–560 (2019). https://doi.org/10.1007/s12553-018-0274-y

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