Chronic Pain Audio Dataset

The Chronic Pain Audio Dataset comprises 256 audio recordings in Spanish from patients aged between 24 and 84 years who suffer from musculoskeletal pain. The purpose of this study is to contribute a dataset for the classification of pain levels into the following categories: None (Nada), Low (Bajo), Medium (Medio) and Strong (Fuerte).
The audio recordings were collected from diverse sources to ensure representativeness and diversity. They include interviews with individuals attending medical consultations and physiotherapy treatments, as well as voluntary contributions recorded during a knee prosthesis surgery campaign.
The recordings employ a verbal scale to describe the intensity of pain experienced by patients at the time of the interview. After being recorded, the audio data underwent processing to enhance its quality, involving stages of selection, trimming, and normalisation. During these procedures, it was determined that an optimal length for usability is between 1 and 5 seconds. Volume normalisation and the removal of silences were applied to produce high-quality audio, suitable for use in training machine learning models.

慢性疼痛音频数据集收录了256段西班牙语录音，这些录音来自24至84岁之间患有肌肉骨骼疼痛的患者。本研究的目的是为将疼痛程度分类为以下类别提供数据集：无（Nada）、轻度（Bajo）、中度（Medio）和重度（Fuerte）。录音资料来源于多元化的渠道，以确保其代表性和多样性。这些资料包括与接受医疗咨询和物理治疗的个体进行的访谈，以及在一次膝关节假体手术活动期间自愿提供的录音。录音采用了口头量表来描述患者在访谈时体验到的疼痛强度。录音完成后，音频数据经过处理以提升其质量，包括筛选、剪辑和标准化等阶段。在这些过程中，确定了1至5秒的长度为最佳使用长度。通过音量标准化和静音去除等手段，生产出高质量的音频，适用于训练机器学习模型。