Research Focus

The VTC Smart Rehab Lab is developing a low-cost system for Semi-Automated Rehabilitation At Home (SARAH) that leverages high-dimensional data and active participation from clinicians, caregivers, and patients. The system is being tested in Upper Extremity Stroke rehabilitation and Total Knee Arthroplasty rehabilitation.


The lab’s lead investigators have significant interdisciplinary expertise across four research themes that need to be addressed in an integrative manner to produce a robust, scalable, and evidence-based Smart Rehab system:

  • A novel system architecture combining computational intelligence, therapist expertise, and active patient engagement to generate multifaceted data, constrain technical challenges and facilitate continuous improvement for human actors and system components.
  • Low-cost combinations of video-based and innovative wearable sensing solutions (IMUs, smart skins, encoders, pressure sensing insoles) that reliably capture critical components of movement as well as overall activity in the home and are customizable to different rehabilitation contexts.
  • Heterogeneous models of computational movement analysis that leverage therapist expertise to integrate a variety of sensors (wearables, video), a variety of features (kinematics, stick- figures, video-based), and a variety of modeling frameworks (Bayesian structural models, dynamical models, and deep-learning models), to create a new design palette enabling knowledge-driven end- solutions for assessing movement in different applications.
  • Intuitive interfaces and secure communication networks to facilitate communication between the human participants, between the system components and between the humans and the system. We rely on cellular networks for communication thus facilitating use in underserved areas.

Future work:

  • Expansion of the use of the designed system for pediatric stroke rehabilitation and fall prevention in the home;
  • Clinical studies to compare Smart Rehab in the home with standard home-based therapy in order to advance evidence-based therapy customization;
  • Use of data to produce models for guiding increased therapy compliance and develop algorithms for automated adaptation of therapy;
  • Smart Rehab applications that can enhance rehabilitation in the clinic.