Smartphone-Based Mobility Data for Cervical Myelopathy Post-Operative Recovery

Denise Feurer's dataset contains smartphone-derived GPS and accelerometer mobility data from 13 patients recovering from cervical myelopathy surgery at Verona University Hospital. The data includes five mobility variables, patient-reported outcome measures (PROMs), and demographic/surgical information collected between the first and fifth post-operative weeks. It was published on figshare in March 2026 under a CC-BY-4.0 license.

Use Cases

• Compare recovery trajectories based on GPS-derived mobility variables like Home Duration and Steps.
• Analyze correlations between passively acquired accelerometer data and clinical pain/disability scores (VAS, mJOA, ODI).
• Evaluate differences in post-operative mobility between anterior and posterior surgical approaches.
• Model patient recovery using smartphone-derived features like Distance Traveled and Significant Location Count.

Strengths

• Includes data from 13 patients (3 female, 10 male) with cervical myelopathy.
• Contains five specific mobility variables derived from GPS and accelerometer data.
• Links mobility data to multiple established clinical outcome measures (VAS, mJOA, ODI, NDI).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (176.3 KB), indicating a limited scope and sample size.

Provenance

Source

Denise Feurer, likely affiliated with Verona University Hospital.

Collection Method

Passively acquired GPS and accelerometer data from personal smartphones, supplemented by patient-reported outcome measures (PROMs) and demographic/surgical information.

Time Range

Data collected during the first and fifth post-operative weeks.

Freshness

Last updated 2026-03-19 05:19:59; freshness should be verified.

Geography

Patients undergoing surgical decompression at Verona University Hospital.