A Preliminary Investigation into Infrared Sensors in Wearables for Upper Extremity Motion Sensing

Studies demonstrate that monitoring and recording movement of rehabilitation exercises can improve the degree of recovery of the patient. Technologies exist to track user movements but they are often large, expensive, or require multiple units to be mounted on the user in different locations. Each of these can be barriers to patient adoption of rehabilitation technologies inside the home. We propose a single unit which incorporates an inertial measurement unit (IMU) and infrared sensors to determine orientation of the arm for various movements. The infrared sensors compensate for IMU drift errors, providing a sensor fusion solution. A novel optical wearable was created for detection of arm movement exercises in three-dimensional space that are consistent with stroke survivor exercises for spasticity rehabilitation. A study of five participants yielded high average accuracies of 98% across participants, without requiring any normalization of results to varying body sizes of participants. These findings indicate a strong inter-patient similarity in arm movement patterns. This inter-patient similarity implies the possibility of a transfer learning application, where various patient data can be used to collectively improve the accuracy of the predictive machine learning model. This could allow development of a medical device that is easily donned by the user for rehabilitation in the comfort of their own home, allowing more effective telerehabilitation.

@article{Menon2018,
  title     = {A Preliminary Investigation into Infrared Sensors in Wearables for Upper Extremity Motion Sensing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {1},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Carlo Menon and Jordan Lui and Kevin Andrews and Andrea Ferrone},
  doi       = {10.14569/SpecialIssue.2018.090114},
  url       = {https://doi.org/10.14569/SpecialIssue.2018.090114}
}