SILVER-Pain Dataset

Description

This open-access record contains the lower-risk component of the dataset: four-channel physiological signals and associated self-reported pain labels. Physiological signals in the younger cohort were collected using the Empatica E4 wristband. Physiological signals in the older cohort were collected using the Empatica EmbracePlus wristband, a newer device in the Empatica wearable line. The broader SILVER-Pain dataset also includes additional modalities collected during the study, including thermal video, depth video, RGB-derived facial action units (FAUs), and selected screening-questionnaire variables. Because those files may present a non-negligible risk of participant re-identification or sensitive information disclosure, they are not included in this open-access Mendeley record. Instead, they are available separately under a controlled-access process requiring user registration, verifiable identity information, and a signed Data Usage Agreement (DUA), consistent with the controlled-access model described by Scientific Data. The controlled-access materials and request instructions are described here: https://websites.umass.edu/xiandu/data-sharing/silver-pain-restricted/. This record includes both original physiological files and processed, ML-ready derivatives for the open-access component. Baseline utilities for parsing, synchronization, and preprocessing are available at https://github.com/straybird16/SILVER-pain. RGB-derived FAUs in the controlled-access component were obtained from RGB video using the open-source ME-GraphAU library: https://github.com/CVI-SZU/ME-GraphAU. **Access Note** This Mendeley record contains ONLY the open-access portion of the SILVER-Pain dataset. Additional controlled-access files, including thermal video, depth video, RGB-derived FAUs, and screening-questionnaire variables, are available separately through a request process requiring signed agreement to the DUA: https://websites.umass.edu/xiandu/silver-dua.

Steps to reproduce

See README on the linked GitHub repository for details on the collection procedure of the data. For computational pipeline that reproduces the data from original files collected, also see the GitHub READMEs.

Institutions

• University of Massachusetts Amherst

  Massachusetts, Amherst Center

Categories

Funders

• Elaine Marieb Center for Nursing and Engineering Innovation, Center for Personalized Health Monitoring, UMass Amherst
• Mass AI and Technology Center for Connected Care in Aging and Alzheimer's Disease

  Grant ID: NIA P30AG0731075- 03 (Pilot A16)

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