An Energy Efficient Adaptive Sensing Framework For Gait Monitoring Using Smart Insole

• Author(s):

  Prakash P | Kalanithi C | Logesh S | Benitsamraj A

• Keywords:

  Gait Analysis, Energy-Efficient Sensing, Adaptive Sensing, Wearable Devices, Longitudinal Gait Monitoring, Battery Optimization, Presampling, Selective Sensing, Signal Reconstruction, Smart Insole, Plantar Pressure, Flex Force Sensor, Vibration Motor, Dia

• Abstract:

  Gait Analysis Is Crucial For Understanding Human Motion, And Longitudinal Gait Analysis Has Gained Significant Attention In Medical And Healthcare Domains. However, Existing Wearable Gait Devices Face A Major Challenge: Limited Battery Life. Continuous Sensing And Computing In Wearable Gait Devices Lead To Short Battery Life, Making It Difficult To Conduct Studies Over Extended Periods. To Address This Challenge, We Present An Energy-efficient Adaptive Sensing Framework That Uses Presampling For Content Understanding, Selective Sensing, And Sparsity-based Signal Reconstruction. Our Framework Reduces The Number Of Samples While Preserving Information Integrity, Enabling Longitudinal Gait Analysis Over Extended Periods. Experimental Results Demonstrate The Effectiveness Of Our Method, Achieving Significant Data Point Reduction While Maintaining Accuracy, With A Battery Life Extension To 10.47 Hours.

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Other Details

• Paper id:

  IJSARTV11I3102914

• Published in:

  Volume: 11 Issue: 3 March 2025

• Publication Date:

  2025-03-27

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