{"ID":6267808,"CreatedAt":"2026-07-10T01:11:38.759438437Z","UpdatedAt":"2026-07-12T00:14:05.327919738Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.08007","arxiv_id":"2607.08007","title":"Unit-Independent Low-Rate Wrist GSR Processing for Stress Detection Using Phasic nSCR Features","abstract":"Galvanic skin response (GSR) is widely used for stress detection, but wrist-based GSR remains challenging because its absolute amplitude can differ substantially from laboratory-grade palmar measurements. In this paper, we propose a unit-independent low-rate wrist GSR processing pipeline to extract the number of skin conductance responses per minute (nSCR/min) as a stress-related feature. We collect paired wrist and palmar GSR recordings from 31 participants during sitting baseline, standing baseline, neutral speaking, and the Trier Social Stress Test (TSST), a laboratory social stressor task. The proposed pipeline cleans the raw GSR signal, decomposes it into tonic skin conductance level (SCL) and phasic skin conductance response (SCR), applies robust z-score normalization, and detects phasic SCR peaks to compute nSCR/min. Using random forest on 25Hz We-Be GSR, nSCR/min achieved balanced accuracies of 0.823 and 0.871 for binary classification between TSST and the sitting and standing baselines, respectively. Moreover, the 25Hz We-Be GSR features achieved comparable balanced accuracy to the original 100Hz features across the evaluated tasks. These results suggest the feasibility of low-rate, unit-independent wrist GSR processing for wearable stress detection.","short_abstract":"Galvanic skin response (GSR) is widely used for stress detection, but wrist-based GSR remains challenging because its absolute amplitude can differ substantially from laboratory-grade palmar measurements. In this paper, we propose a unit-independent low-rate wrist GSR processing pipeline to extract the number of skin c...","url_abs":"https://arxiv.org/abs/2607.08007","url_pdf":"https://arxiv.org/pdf/2607.08007v1","authors":"[\"Zequan Liang\",\"Sally Hang\",\"Geneva M. Jost\",\"Ning Miao\",\"Wei Shao\",\"Mahdi Pirayesh Shirazi Nejad\",\"Hossein Sayadi\",\"Ehsan Kourkchi\",\"Setareh Rafatirad\",\"Camelia E. Hostinar\",\"Houman Homayoun\"]","published":"2026-07-09T00:24:04Z","proceeding":"eess.SP","tasks":"[\"eess.SP\",\"cs.LG\"]","methods":"[]","has_code":false}