Hair follicle stem cells naturally participate in cutaneous wound healing and are accessible. There are great interests in applying them to wound treatments. Vibrational spectroscopy is a label-free and non-invasive technique. Establishing spectral fingerprint of a cell type can enable label-free live cell sorting. The aim of this work is to identify hair follicle stem cells using vibrational spectroscopy. The work focuses on the hair follicle mesenchymal stem cells (MSCs) and epithelial progenitor cells (epiPCs). Firstly demonstrated, was the feasibility of using Fourier transform infrared (FTIR) spectroscopy and chemometric analysis, to discern tissue types within the hair follicle, based solely on spectral variation. Next, single dermal papilla (DP) cell spectra were analysed in relation to stem cell properties. The differences found in the C-H stretching bands ascribed to fatty acids and proteins were of particular interests. Human hair follicle MSCs express nestin, but lack definitive markers and a defined niche, making it difficult to isolate pure MSCs for FTIR signature establishment. epiPC FTIR features were thus used as guidance, towards identifying the hair follicle MSCs. The comparison between FTIR spectra of single hair follicle epiPCs and mature outer root sheath (ORS) cells rendered increased total lipid concentration and decreased protein concentration to be spectral features for discerning human hair follicle epiPCs against ORS cells. FTIR imaging at an approximate single cell spatial resolution was applied to hair bulbs. The use of unsupervised hierarchical clustering analysis (UHCA) to the FTIR maps successfully isolated spectra in the hair follicle mesenchyme, with similar characteristics to the epiPCs. They were found in both mesenchymal compartments and their locations were similar to the nestin immunostaining pattern. It was thus evident that FTIR spectroscopy imaging had located MSCs in the human hair follicle. Lastly, by combining Raman mapping and UHCA, Raman signature of hair follicle cells were extracted, which will enable future live stem cell analysis. This thesis shows unprecedented examples of hair follicle stem cell characterisation using vibrational spectroscopy. It paves way towards a label-free, non-invasive hair follicle stem cell sorting modality.