data_CL_SCS: Computational Models of Spinal Cord Stimulation Signals

A computational modeling dataset by Zhen Wu, last updated May 7, 2026. It contains multi-compartment cable models of sensory fibers and finite element models of the human spinal cord under various postures. The 14.8 GB dataset compares the regulatory performance of two closed-loop algorithms during spinal cord stimulation therapy.

Use Cases

• Simulating evoked compound action potential (ECAP) signals based on posture changes.
• Comparing closed-loop algorithm performance for spinal cord stimulation therapy.
• Analyzing ECAP–current curves derived from computational models.
• Validating finite element models of the human spinal cord.

Strengths

• Dataset size is 14.8 GB, indicating substantial model output.
• License is CC-BY-4.0, permitting open sharing and adaptation.
• Last updated date is explicitly provided (2026-05-07).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Zhen Wu via figshare

Collection Method

Constructed using computational modeling of sensory fibers and spinal cord.

Freshness

Last updated 2026-05-07 09:31:06.