Control Signals in Closed-Loop Spinal Cord Stimulation in Patients with Chronic Pain: A Scoping Review

A closed-loop SCS algorithm that incorporates subjective and objective features may hold potential to improve quality of life in patients with chronic pain. Combining these approaches in a temporally resolved manner, for example, integrating patient reports with continuous electrophysiologic information using a state space mathematical model, could allow more optimized and patient-specific SCS programming.

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Publication Details

Journal
Neuromodulation Technology at the Neural Interface
Published
2026-01-01
DOI
https://doi.org/10.1016/j.neurom.2025.11.011
Primary Topic
Pain Management and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Control Signals in Closed-Loop Spinal Cord Stimulation in Patients with Chronic Pain: A Scoping Review

Suguna. Pappu, Brian Y. Hong, Ravishankar K. Iyer, Ying Yang et al.
Neuromodulation Technology at the Neural Interface
Pain Management and Treatment
article

Control Signals in Closed-Loop Spinal Cord Stimulation in Patients with Chronic Pain: A Scoping Review

Suguna. Pappu, Brian Y. Hong, Ravishankar K. Iyer, Ying Yang, Prateek Dullur, Meenakshi Singhal, Mehreen Ali
article en

Abstract

A closed-loop SCS algorithm that incorporates subjective and objective features may hold potential to improve quality of life in patients with chronic pain. Combining these approaches in a temporally resolved manner, for example, integrating patient reports with continuous electrophysiologic information using a state space mathematical model, could allow more optimized and patient-specific SCS programming.

Neuromodulation Technology at the Neural Interface
Carle Foundation Hospital (US), University of Illinois Urbana-Champaign (US), Illinois College (US)
National Science Foundation
Openalex Percentile: Top 91%
Pain Management and Treatment
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Control Signals in Closed-Loop Spinal Cord Stimulation in Patients with Chronic Pain: A Scoping Review — Suguna. Pappu, Brian Y. Hong, et al. · Neuromodulation Technology at the Neural Interface (2026) | TGRS Research Map | TGRS