Pain (Dolor)

The Dolor 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: “Nada”, “Bajo”, “Medio” and “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.

Dolor 数据集包含 256 段西班牙语语音录音，录音对象为 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至以下类别提供数据集：‘无’，‘轻微’，‘中等’和‘剧烈’。录音资料来源多样，以确保其代表性及多样性，包括接受医疗咨询和物理治疗的个人访谈，以及在一次膝关节假体手术宣传活动期间的自愿贡献。录音采用口头量表描述患者在访谈时经历的疼痛强度。录音数据在记录后经过处理以提升其质量，包括选择、剪辑和标准化等阶段。在此过程中，确定了1至5秒的长度为最佳可用长度。通过音量标准化和静音移除，产生了高质量的音频，适用于机器学习模型的训练。