{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T11:18:32Z","timestamp":1761218312816,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,16]],"date-time":"2020-12-16T00:00:00Z","timestamp":1608076800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work investigates the use of an intelligent and unobstructive sensing technique for maintaining vehicle cabin\u2019s indoor air quality while simultaneously assessing the driver metabolic rate. CO2 accumulation patterns are of great interest because CO2 can have negative cognitive effects at higher concentrations and also since CO2 accumulation rate can potentially be used to determine a person\u2019s metabolic rate. The management of the vehicle\u2019s ventilation system was controlled by periodically alternating the air recirculation mode within the cabin, which was actuated based on the CO2 levels inside the vehicle\u2019s cabin. The CO2 accumulation periods were used to assess the driver\u2019s metabolic rate, using a model that considered the vehicle\u2019s air exchange rate. In the process of the method optimization, it was found that the vehicle\u2019s air exchange rate (\u03bb [h\u22121]) depends on the vehicle speeds, following the relationship: \u03bb = 0.060 \u00d7 (speed) \u2212 0.88 when driving faster than 17 MPH. An accuracy level of 95% was found between the new method to assess the driver\u2019s metabolic rate (1620 \u00b1 140 kcal\/day) and the reference method of indirect calorimetry (1550 \u00b1 150 kcal\/day) for a total of N = 16 metabolic assessments at various vehicle speeds. The new sensing method represents a novel approach for unobstructive assessment of driver metabolic rate while maintaining indoor air quality within the vehicle cabin.<\/jats:p>","DOI":"10.3390\/s20247202","type":"journal-article","created":{"date-parts":[[2020,12,16]],"date-time":"2020-12-16T09:21:15Z","timestamp":1608110475000},"page":"7202","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An Unobstructive Sensing Method for Indoor Air Quality Optimization and Metabolic Assessment within Vehicles"],"prefix":"10.3390","volume":"20","author":[{"given":"Yue","family":"Deng","sequence":"first","affiliation":[{"name":"School of Engineering for Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85281, USA"},{"name":"Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Sprowls","sequence":"additional","affiliation":[{"name":"School of Engineering for Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85281, USA"},{"name":"Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4181-4732","authenticated-orcid":false,"given":"S. Jimena","family":"Mora","sequence":"additional","affiliation":[{"name":"School of Engineering for Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85281, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Doina","family":"Kulick","sequence":"additional","affiliation":[{"name":"Mayo Clinic, Scottsdale, AZ 85054, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nongjian","family":"Tao","sequence":"additional","affiliation":[{"name":"School of Electrical, Energy and Computer Engineering, Arizona State University, Tempe, AZ 85281, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hugo","family":"Destaillats","sequence":"additional","affiliation":[{"name":"Lawrence Berkeley National Laboratory, Indoor Environment Group, Berkeley, CA 94720, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erica","family":"Forzani","sequence":"additional","affiliation":[{"name":"School of Engineering for Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85281, USA"},{"name":"Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,16]]},"reference":[{"key":"ref_1","unstructured":"NHTSA (2020, July 14). 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