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Specifically, cyber-physical systems are being increasingly applied in smart-homes to support independent and healthy aging. Due to the growing prevalence of noncommunicable diseases in the senior population, a key application in this domain is the detection of cognitive issues based on sensor data. In this article, we propose a novel cyber-physical system for cognitive assessment in smart-homes. Cognitive evaluation relies on clinical indicators characterizing symptoms of dementia based on the individual\u2019s movement patterns. However, recognizing these patterns in smart-homes is challenging, because movement is constrained by the home layout and obstacles. Since different abnormal patterns are characterized by undulatory-like trajectories, we conjecture that frequency-based locomotion features may more effectively capture these patterns with respect to traditional features in the spatio-temporal domain. Based on this intuition, we introduce novel feature extraction techniques and adopt state-of-the-art machine learning algorithms for short- and long-term cognitive evaluation. Our system includes a user-friendly interface that enables clinicians to inspect the data and predictions. Extensive experiments carried out with a real-world dataset acquired from both cognitively healthy seniors and people with dementia show the superiority of our frequency-based features. Moreover, further experiments with an ensemble method show that prediction accuracy can be enhanced by combining features in the frequency and time domains.<\/jats:p>","DOI":"10.1145\/3470454","type":"journal-article","created":{"date-parts":[[2022,2,4]],"date-time":"2022-02-04T21:44:21Z","timestamp":1644011061000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["FreeSia: A Cyber-physical System for Cognitive Assessment through Frequency-domain Indoor Locomotion Analysis"],"prefix":"10.1145","volume":"6","author":[{"given":"Elham","family":"Khodabandehloo","sequence":"first","affiliation":[{"name":"Department of Geo-spatial Information System, K. N. Toosi University of Technology, Tehran, Iran"}]},{"given":"Abbas","family":"Alimohammadi","sequence":"additional","affiliation":[{"name":"Department of Geo-spatial Information System, K. N. 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