{"corpus_id":10779782,"paper_sha":"b2429e6afee440d940a69197e7bbb602b0d3986a","doi":"10.3390/s140202595","arxiv_id":null,"pmid":24514883,"pmcid":"3958278","mag_id":2045200098,"dblp_id":"journals/sensors/LazaroGV14","acl_id":null,"title":"Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars","year":2014,"publication_date":"2014-02-01","venue":"Italian National Conference on Sensors","journal":{"name":"Sensors (Basel, Switzerland)","pages":"2595 - 2618","volume":"14"},"journal_issn":null,"journal_title":null,"publication_types":["JournalArticle"],"pubmed_pub_types":["Journal Article","Research Support, Non-U.S. Gov't"],"s2_fields_of_study":["Medicine","Computer Science","Engineering"],"reference_count":66,"citation_count":129,"influential_citation_count":5,"is_open_access":true,"arxiv_categories":null,"arxiv_license":null,"arxiv_journal_ref":null,"mesh_headings":null,"chemicals":null,"comments_corrections":null,"source_flags":5,"s2_open_access_pdf_url":"https://www.mdpi.com/1424-8220/14/2/2595/pdf?version=1403345117","s2_open_access_landing_url":"https://www.semanticscholar.org/paper/b2429e6afee440d940a69197e7bbb602b0d3986a","s2_open_access_license":"CCBY","s2_open_access_status":"GOLD","pmc_open_access_pdf_url":null,"pmc_open_access_landing_url":null,"pmc_open_access_license":null,"pmc_open_access_status":null,"unpaywall_open_access_pdf_url":null,"unpaywall_open_access_landing_url":null,"unpaywall_open_access_license":null,"unpaywall_open_access_status":null,"abstract":"This paper focuses on the feasibility of tracking the chest wall movement of a human subject during respiration from the waveforms recorded using an impulse-radio (IR) ultra-wideband radar. The paper describes the signal processing to estimate sleep apnea detection and breathing rate. Some techniques to solve several problems in these types of measurements, such as the clutter suppression, body movement and body orientation detection are described. Clutter suppression is achieved using a moving averaging filter to dynamically estimate it. The artifacts caused by body movements are removed using a threshold method before analyzing the breathing signal. The motion is detected using the time delay that maximizes the received signal after a clutter removing algorithm is applied. The periods in which the standard deviations of the time delay exceed a threshold are considered macro-movements and they are neglected. The sleep apnea intervals are detected when the breathing signal is below a threshold. The breathing rate is determined from the robust spectrum estimation based on Lomb periodogram algorithm. On the other hand the breathing signal amplitude depends on the body orientation respect to the antennas, and this could be a problem. In this case, in order to maximize the signal-to-noise ratio, multiple sensors are proposed to ensure that the backscattered signal can be detected by at least one sensor, regardless of the direction the human subject is facing. The feasibility of the system is compared with signals recorded by a microphone.","claims":[{"public_id":"cl_116ffeccc32dabec6ce1e54825be87a8","status":"active","text":"Artifacts caused by body movements are removed with a threshold method before breathing-signal analysis, and periods with time-delay standard deviations above a threshold are treated as macro-movements and ignored.","confidence":0.95,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_116ffeccc32dabec6ce1e54825be87a8"},{"public_id":"cl_afcb92504d994cdc833d4af0d98114ed","status":"active","text":"Clutter suppression is achieved with a moving averaging filter that dynamically estimates clutter.","confidence":0.96,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_afcb92504d994cdc833d4af0d98114ed"},{"public_id":"cl_311d4c490ab94762f7aa4c8cbcf8f9e8","status":"active","text":"Feasibility of the system is compared with signals recorded by a microphone.","confidence":0.89,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_311d4c490ab94762f7aa4c8cbcf8f9e8"},{"public_id":"cl_066e99076cc58c91d226cacbf8d329d4","status":"active","text":"Multiple sensors are proposed to maximize signal-to-noise ratio by ensuring that the backscattered signal is detected regardless of the subject's orientation toward the antennas.","confidence":0.93,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_066e99076cc58c91d226cacbf8d329d4"},{"public_id":"cl_68dd652dc89abba17c45d0a21503865d","status":"active","text":"Sleep apnea intervals are detected when the breathing signal falls below a threshold, and breathing rate is estimated using Lomb periodogram-based robust spectrum estimation.","confidence":0.97,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_68dd652dc89abba17c45d0a21503865d"}],"concepts":[{"public_id":"co_11d6b6841af436a2119dc8f391c5ef21","status":"active","name":"Lomb periodogram algorithm","description":"A spectral estimation approach used to estimate periodicity from unevenly sampled or noisy data.","types":["algorithm","spectral estimation method"],"aliases":["Lomb periodogram"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_11d6b6841af436a2119dc8f391c5ef21"},{"public_id":"co_26ea0ffe30844e05479313c861e84f6d","status":"active","name":"microphone","description":"An audio sensor used here as a reference for comparing respiration-related measurements.","types":["reference sensor","sensor"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_26ea0ffe30844e05479313c861e84f6d"},{"public_id":"co_37bfabff4098d38347ed93c6cb831536","status":"active","name":"body movements","description":"Gross subject motion that introduces artifacts into respiratory sensing measurements.","types":["motion artifact source"],"aliases":["body movement"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_37bfabff4098d38347ed93c6cb831536"},{"public_id":"co_3fba6335de7526ee984099bd397c71d1","status":"active","name":"macro-movements","description":"Large body motions identified from elevated variability in the estimated time delay.","types":["motion event"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_3fba6335de7526ee984099bd397c71d1"},{"public_id":"co_3fc3cc57d0672a0b6fb540fbbbaa00e9","status":"active","name":"multiple sensors","description":"An arrangement of more than one sensing element used to increase the chance of detecting the reflected signal.","types":["sensor configuration"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_3fc3cc57d0672a0b6fb540fbbbaa00e9"},{"public_id":"co_5949526d232ce2ac4581bd411d8d8fbc","status":"active","name":"sleep apnea intervals","description":"Time intervals during which breathing is suppressed below a defined threshold.","types":["event","clinical phenomenon"],"aliases":["sleep apnea detection"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_5949526d232ce2ac4581bd411d8d8fbc"},{"public_id":"co_633e7dbb839843460ab5f9d99020aa6a","status":"active","name":"clutter suppression","description":"Signal processing intended to reduce unwanted stationary or slowly varying components in radar measurements.","types":["signal processing method"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_633e7dbb839843460ab5f9d99020aa6a"},{"public_id":"co_7d156978734bff2e262f19e1a503ab25","status":"active","name":"backscattered signal","description":"The radar return signal reflected from the subject toward the sensors.","types":["signal"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_7d156978734bff2e262f19e1a503ab25"},{"public_id":"co_93fbb24a16003cbdfe765d572a84c794","status":"active","name":"signal-to-noise ratio","description":"The ratio of desired signal power to background noise power.","types":["measurement"],"aliases":["SNR"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_93fbb24a16003cbdfe765d572a84c794"},{"public_id":"co_b21d7ee30a430df951430b95dfb81449","status":"active","name":"impulse-radio ultra-wideband radar","description":"A radar modality that uses very short impulse radio signals over an ultra-wide frequency band to sense reflected signals from the human body.","types":["sensor","measurement technique"],"aliases":["IR UWB radar","UWB radar"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_b21d7ee30a430df951430b95dfb81449"},{"public_id":"co_db190acab99557c0fc74b06e4e4e9bad","status":"active","name":"respiration","description":"The breathing process whose motion and waveform are being tracked.","types":["physiological process"],"aliases":["breathing"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_db190acab99557c0fc74b06e4e4e9bad"},{"public_id":"co_de2d09a7d238223f1de434e0bc3b2000","status":"active","name":"breathing signal","description":"The radar-derived signal used to represent respiratory activity.","types":["signal"],"aliases":["breathing signal amplitude"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_de2d09a7d238223f1de434e0bc3b2000"},{"public_id":"co_eb98176e572f6c355bdce7bc080f7cb0","status":"active","name":"system feasibility","description":"The practical viability of the proposed respiratory sensing setup in comparison with reference measurements.","types":["evaluation outcome"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_eb98176e572f6c355bdce7bc080f7cb0"},{"public_id":"co_edcfbecb71b12855b12615780d7787e6","status":"active","name":"moving averaging filter","description":"A filter that smooths a signal by averaging values over a sliding window.","types":["filter"],"aliases":["moving average filter"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_edcfbecb71b12855b12615780d7787e6"},{"public_id":"co_ef5d1b072f3dbbff461679227f817c53","status":"active","name":"chest wall movement","description":"Motion of the chest surface associated with respiration.","types":["physiological motion","signal source"],"aliases":["chest wall movement of a human subject"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_ef5d1b072f3dbbff461679227f817c53"},{"public_id":"co_f3baddce3e6b288b4050a1e0e07375de","status":"active","name":"threshold method","description":"A decision rule that classifies signal values or events using preset threshold levels.","types":["signal processing method"],"aliases":[],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/concepts/co_f3baddce3e6b288b4050a1e0e07375de"}],"external_ids":{"DOI":"10.3390/s140202595","ArXiv":null,"PubMed":24514883,"PubMedCentral":"3958278","MAG":2045200098,"DBLP":"journals/sensors/LazaroGV14","ACL":null},"open_access":{"is_open_access":true,"pdf_url":"https://www.mdpi.com/1424-8220/14/2/2595/pdf?version=1403345117","landing_url":"https://www.semanticscholar.org/paper/b2429e6afee440d940a69197e7bbb602b0d3986a","source":"semantic_scholar","pdf_url_source":"semantic_scholar_open_access_pdf","license":"CCBY","status":"GOLD","reason":null},"reference_availability":{"status":"available","references_indexed":true,"full_text_available":false,"full_text_source":null,"count_basis":"semantic_scholar_metadata","extraction_status":"not_applicable","reason":null},"source":{"provider":"episteme2","base_corpus":"semantic_scholar_dump","freshness_mode":"unknown","basis":["semantic_scholar_metadata","postgres_metadata"],"limits":["paper metadata is based on indexed upstream scholarly datasets","claims and concepts are available only for extracted papers","absence of claims or concepts means no extracted graph data is available in this response"],"status":"available","degraded":false,"degraded_reasons":[],"diagnostics":{"status":"available","degraded":false,"degraded_reasons":[],"metadata_status":"available","graph_status":"available","abstract_status":"available"},"source_flags":5},"paper_id":631435,"paper_uid":"1d1151a2-6107-46c5-ad04-a5be075ad729","canonical_identity":{"paper_id":631435,"paper_uid":"1d1151a2-6107-46c5-ad04-a5be075ad729","identity_status":"available","lookup_basis":"semantic_scholar_external_id","compatibility_path":"corpus_id"},"url":"https://sah.borca.ai/papers/10779782"}