Enhancing personal comfort: A machine learning approach using physiological and environmental signals measurements

•Physiological and environmental parameters were collected on 24 volunteers.•Physiological features - thermal sensation (TS) correlation was investigated.•Machine learning algorithms were fed with an optimal features subset to classify TS.•RF classifier provided the best accuracy (90%) for both hot and cold TS.