PDF(Pubmed)
Abstract：
The monitoring of body temperature is a recent addition to the plethora of parameters provided by wellness and fitness wearable devices. Current wearable temperature measurements are made at the skin surface, a measurement that is impacted by the ambient environment of the individual. The use of near-infrared spectroscopy provides the potential for a measurement below the epidermal layer of skin, thereby having the potential advantage of being more reflective of physiological conditions. The feasibility of noninvasive temperature measurements is demonstrated by using an in vitro model designed to mimic the near-infrared spectra of skin. A miniaturizable solid-state laser-diode-based near-infrared spectrometer was used to collect diffuse reflectance spectra for a set of seven tissue phantoms composed of different amounts of water, gelatin, and Intralipid. Temperatures were varied between 20-24 °C while collecting these spectra. Two types of partial least squares (PLS) calibration models were developed to evaluate the analytical utility of this approach. In both cases, the collected spectra were used without pre-processing and the number of latent variables was the only optimized parameter. The first approach involved splitting the whole dataset into separate calibration and prediction subsets for which a single optimized PLS model was developed. For this first case, the coefficient of determination (R2) is 0.95 and the standard error of prediction (SEP) is 0.22 °C for temperature predictions. The second strategy used a leave-one-phantom-out methodology that resulted in seven PLS models, each predicting the temperatures for all spectra in the held-out phantom. For this set of phantom-specific predicted temperatures, R2 and SEP values range from 0.67-0.99 and 0.19-0.65 °C, respectively. The stability and reproducibility of the sample-to-spectrometer interface are identified as major sources of spectral variance within and between phantoms. Overall, results from this in vitro study justify the development of future in vivo measurement technologies for applications as wearables for continuous, real-time monitoring of body temperature for both healthy and ill individuals.
摘要：
体温监测是健康和健身可穿戴设备提供的大量参数的最新补充。当前可穿戴温度测量是在皮肤表面进行的，受个人周围环境影响的测量。近红外光谱的使用为皮肤表皮层以下的测量提供了潜力，从而具有更能反映生理状况的潜在优势。通过使用旨在模拟皮肤近红外光谱的体外模型证明了无创温度测量的可行性。使用可小型化的基于固态激光二极管的近红外光谱仪收集一组由不同量的水组成的七个组织体模的漫反射光谱，明胶,和内脂。温度在20-24°C之间变化,同时收集这些光谱。开发了两种类型的偏最小二乘（PLS）校准模型来评估这种方法的分析实用性。在这两种情况下，收集的光谱没有预处理，潜在变量的数量是唯一的优化参数。第一种方法涉及将整个数据集分成单独的校准和预测子集,针对这些子集开发了单个优化的PLS模型。对于第一种情况，温度预测的决定系数（R2）为0.95，预测标准误差（SEP）为0.22°C。第二种策略使用了留一模方法，产生了七个PLS模型，每个人都预测保持体模中所有光谱的温度。对于这组特定于体模的预测温度，R2和SEP值范围为0.67-0.99和0.19-0.65°C，分别。样品到光谱仪接口的稳定性和再现性被认为是体模内部和之间光谱变化的主要来源。总的来说,这项体外研究的结果证明了未来体内测量技术的发展，可用于可穿戴设备的应用，实时监测健康和患病个体的体温。
