{"doi":"10.1177/1071181320641003","title":"Use Of Linear-Polarization Doppler Radar System to Detect Falls: Results From a Simulated Living Environment","abstract":"Substantial recent growth in the number and proportion of older adults (aged 65 and over) is an important U.S. demographic change, with a projection that one of every four Americansabout 95 million peoplewill be an older adult by 2060 (US Census Bureau 2020).This demographic change has and will have significant impacts on American society.Accompanied by Affordable Care Act (ACA) coverage expansions, older adults (OAs) are expected to create growing demands on and needs for healthcare and medical care services in coming decades.While fall prevention is being investigated extensively, falls will remain highly prevalent for the foreseeable future.Fall detection can be enabled with diverse sensor technologies, alone or in combination, such as wearable sensors (e.g., accelerometers, gyroscopes, emergency buttons) and ambient sensors (e.g., video cameras, microphones).Use of radar technologies has gained interest with applications for indoor fall and/or activity monitoring, likely because radar signals are insensitive to lighting conditions and may pose limited privacy concerns.Earlier work explored using radar signals (especially micro-Doppler signatures) in several applications, such as human activity (e.g., gait, fall) classification (e.g., Kim and Ling 2009;Jokanovic et al. 2016;Liu et al. 2011), and demonstrated the potential as an approach for in-home ambient (or non-wearable) monitoring.Earlier work has also demonstrated clear potential in using micro-Doppler signatures to detect and monitor physical activities.Fall simulations in such earlier work were, however, quite simple (e.g., considering one or two simple fall types, a fall in a preset direction), and involved small sample sizes.Here, a total of 20 gender-balanced participants were recruited from the local community and university; each completed seven different fall types in a mock room environment, and also four different types of activities of daily living (ADLs) at self-selected normal, slower, and faster speeds.Note that all falls were performed onto a large foam mat to minimize the risk of injury, and that no specific instructions were given about how to perform each type of falls and ADLs.Informed consent was obtained, and all procedures were approved by the Virginia Tech IRB.Fall and ADL simulations performed by participants were captured using the Ancorteck SDR-KIT 2400AD2 (Fairfax, VA, USA) linear polarization radar system, two of which were configured orthogonally in the mock room environment.The respective center frequency, chirp bandwidth, and chirp period were 2.43 GHz, 750 MHz, and 1 ms for System 1; and 2.44 GHz, 500 MHz, and 1 ms for System 2. In addition, all fall and ADL simulations were","journal":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","year":2020,"id":117151,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9564,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":547289,"name":"Maury A. Nussbaum","orcid":null,"position":1,"is_corresponding":false},{"id":314146,"name":"Fleming Lure","orcid":"0000-0001-5655-6831","position":2,"is_corresponding":false},{"id":546688,"name":"Sunwook Kim","orcid":"0000-0003-3624-1781","position":0,"is_corresponding":true}],"reference_count":2,"raw_metadata":null,"created_at":"2026-07-18T23:13:51.309289Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}