Currà Antonio, Gasbarrone Riccardo, Trompetto Carlo, Fattapposta Francesco, Pierelli Francesco, Missori Paolo, Bonifazi Giuseppe, Serranti Silvia
Academic Neurology Unit, A. Fiorini Hospital, Terracina (LT), Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Polo Pontino, Via Firenze snc, 04019 Terracina, LT, Italia.
Research Center for Biophotonics, Sapienza University of Rome, Polo Pontino, Corso della Repubblica 79, 04100 Latina, Italia.
Data Brief. 2020 Nov 2;33:106480. doi: 10.1016/j.dib.2020.106480. eCollection 2020 Dec.
Advancement of technology and device miniaturization have made near infrared spectroscopy (NIRS) techniques cost-effective, small-sized, simple, and ready to use. We applied NIRS to analyze healthy human muscles in vivo, and we found that this technique produces reliable and reproducible spectral "fingerprints" of individual muscles, that can be successfully discriminated by chemometric predictive models. The dataset presented in this descriptor contains the reflectance spectra acquired in vivo from the ventral and dorsal aspects of the arm using an ASD FieldSpec® 4 Standard-Res field portable spectroradiometer (350-2500 nm), the values of the anthropometric variables measured in each subject, and the codes to assist access to the spectral data. The dataset can be used as a reference set of spectral signatures of "biceps" and "triceps" and for the development of automated methods of muscle detection.
技术进步和设备小型化使近红外光谱(NIRS)技术具有成本效益、体积小、操作简单且随时可用的特点。我们应用NIRS对健康人体肌肉进行体内分析,发现该技术能产生个体肌肉可靠且可重复的光谱“指纹”,这些光谱“指纹”可通过化学计量学预测模型成功区分。本描述符中呈现的数据集包含使用ASD FieldSpec® 4标准分辨率野外便携式光谱辐射仪(350 - 2500 nm)在体内从手臂腹侧和背侧采集的反射光谱、每个受试者测量的人体测量变量值以及用于辅助访问光谱数据的代码。该数据集可作为“肱二头肌”和“肱三头肌”光谱特征的参考集,用于开发肌肉检测的自动化方法。