公开(公告)号：US20220359078A1

公开(公告)日：2022-11-10

申请号：US17684992

申请日：2022-03-02

Applicant: Tata Consultancy Services Limited

Inventor： Shivam SINGHAL ,  Nasimuddin Ahmed ,  Varsha Sharma ,  Sakyajit Bhattacharya ,  Aniruddha Sinha ,  Avik Ghose

IPC: G16H50/20 ,  A61B5/11 ,  A61B5/00

Abstract: This disclosure relates generally to patient invariant model for freezing of gait detection based on empirical wavelet decomposition. The method receives a motion data from an accelerometer sensor coupled to an ankle of a subject. The motion data is further processed to denoise a plurality of data windows using a peak detection technique to classify into a real motion data window or a noisy data window. Further, a plurality of denoised data windows are generated by processing spectrums associated with each real motion data window and a plurality of empirical modes using an empirical wavelet decomposition technique (EWT). Then, a resultant acceleration is computed, and a plurality of features are extracted from the denoised data window which enables detection of freezing of gait based on a pretrained classifier model into a (i) a positive class, or (ii) a negative class.