Christopher Pulliam, PhD

Assistant Professor
Department of Biomedical Engineering
Case School of Engineering, School of Medicine

Research Information

Research Interests

Many studies have demonstrated that rehabilitation and other therapeutic interventions are beneficial across several neurological conditions. Choosing the most effective intervention for an individual patient, however, is challenging and tools are needed assess if the patient is responding adequately to the ongoing intervention or if an adjustment to the intervention strategy is needed. Over the past decade, wearable and implantable technologies have matured enough to provide effective tools for monitoring patients during their daily lives, providing the potential for an objective assessment to inform patient care.

Our long-term goal is to develop clinical decision support tools that aid neurorehabilitation specialists in identifying and titrating interventions in a way that better accounts for the unique characteristics of each individual. Towards that goal, we are 1) developing novel approaches for monitoring motor recovery and physiological function in the real-world; and 2) evaluating models for predicting optimal interventions and rehab outcomes.


  • Xiao Y, Panken EJ, Jackson JC, Pulliam CL., inventors. Medtronic, assignee. "Signal-based automated deep brain stimulation programming." United States 11,318,296. 2022.
  • Heldman DA, Pulliam CL, Giuffrida JP, Mera TO., inventors. Great Lakes NeuroTechnologies, assignee. "Artificial intelligence systems for quantifying movement disorder symptoms and adjusting treatment based on symptom quantification." United States 10,974,049. 2021.
  • Pulliam CL, Heldman DA, Brokaw EB, Mera TO, Mari ZK, Burack MA. Continuous Assessment of Levodopa Response in Parkinson's Disease Using Wearable Motion Sensors. IEEE Trans Biomed Eng. 2018 Jan;65(1):159-164. PubMed Central PMCID: PMC5755593.

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