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Control Signals in Closed-Loop Spinal Cord Stimulation in Patients with Chronic Pain: A Scoping Review.
Prateek Dullur1, Meenakshi Singhal1, Brian Hong1
1Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Summary
Closed-loop spinal cord stimulation (SCS) shows promise for chronic pain. Integrating subjective pain reports with objective biomarkers could personalize SCS therapy and enhance patient quality of life.
Area of Science:
- Neuromodulation
- Biomedical Engineering
- Pain Management
Background:
- Spinal cord stimulation (SCS) offers chronic pain relief but faces limitations in programming and personalization.
- Current closed-loop SCS systems adapt stimulation using biomarkers like position and evoked compound action potentials (ECAPs).
- Existing systems often fail to integrate subjective patient pain experiences with objective neural data.
Purpose of the Study:
- To conduct a scoping review of control signals and algorithms in closed-loop SCS devices.
- To identify strategies for enhancing the efficacy of closed-loop SCS.
Main Methods:
- Systematic literature search of PubMed, SCOPUS, and Web of Science databases.
- Inclusion of peer-reviewed English articles on closed-loop SCS for chronic pain with real-time stimulation modulation.
- Screening of 688 unique articles, with 28 meeting criteria (19 unique studies).
Main Results:
- Few studies (3) incorporated subjective patient states (pain, mood, paresthesias).
- Objective features like position and movement were used in seven studies.
- Evoked Compound Action Potentials (ECAPs) were control signals in nine studies.
- No current models fully integrate both subjective and biophysical markers for closed-loop SCS.
Conclusions:
- A closed-loop SCS algorithm combining subjective and objective features could improve patient quality of life.
- Integrating patient reports with continuous electrophysiologic data may enable optimized, patient-specific SCS programming.
- State space mathematical models offer a potential framework for temporally resolved integration of diverse data streams.
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