{"id":"https://openalex.org/W2886300352","doi":"https://doi.org/10.1109/icc.2018.8422107","title":"Indoor Human Activity Recognition Based on Ambient Radar with Signal Processing and Machine Learning","display_name":"Indoor Human Activity Recognition Based on Ambient Radar with Signal Processing and Machine Learning","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2886300352","doi":"https://doi.org/10.1109/icc.2018.8422107","mag":"2886300352"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2018.8422107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051716922","display_name":"Shangyue Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I198089087","display_name":"Ball State University","ror":"https://ror.org/00k6tx165","country_code":"US","type":"education","lineage":["https://openalex.org/I198089087"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shangyue Zhu","raw_affiliation_strings":["Department of Computer Science, Ball State University, Muncie, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Ball State University, Muncie, IN","institution_ids":["https://openalex.org/I198089087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101786021","display_name":"Junhong Xu","orcid":"https://orcid.org/0000-0001-7127-5093"},"institutions":[{"id":"https://openalex.org/I198089087","display_name":"Ball State University","ror":"https://ror.org/00k6tx165","country_code":"US","type":"education","lineage":["https://openalex.org/I198089087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junhong Xu","raw_affiliation_strings":["Department of Computer Science, Ball State University, Muncie, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Ball State University, Muncie, IN","institution_ids":["https://openalex.org/I198089087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035545617","display_name":"Hanqing Guo","orcid":"https://orcid.org/0000-0003-3779-4679"},"institutions":[{"id":"https://openalex.org/I198089087","display_name":"Ball State University","ror":"https://ror.org/00k6tx165","country_code":"US","type":"education","lineage":["https://openalex.org/I198089087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanqing Guo","raw_affiliation_strings":["Department of Computer Science, Ball State University, Muncie, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Ball State University, Muncie, IN","institution_ids":["https://openalex.org/I198089087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101924195","display_name":"Qiwei Liu","orcid":"https://orcid.org/0009-0005-5344-3985"},"institutions":[{"id":"https://openalex.org/I198089087","display_name":"Ball State University","ror":"https://ror.org/00k6tx165","country_code":"US","type":"education","lineage":["https://openalex.org/I198089087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiwei Liu","raw_affiliation_strings":["Department of Computer Science, Ball State University, Muncie, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Ball State University, Muncie, IN","institution_ids":["https://openalex.org/I198089087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100743605","display_name":"Shaoen Wu","orcid":"https://orcid.org/0000-0002-4768-6930"},"institutions":[{"id":"https://openalex.org/I198089087","display_name":"Ball State University","ror":"https://ror.org/00k6tx165","country_code":"US","type":"education","lineage":["https://openalex.org/I198089087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaoen Wu","raw_affiliation_strings":["Department of Computer Science, Ball State University, Muncie, IN"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Ball State University, Muncie, IN","institution_ids":["https://openalex.org/I198089087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100419573","display_name":"Honggang Wang","orcid":"https://orcid.org/0000-0001-9475-2630"},"institutions":[{"id":"https://openalex.org/I100633361","display_name":"University of Massachusetts Dartmouth","ror":"https://ror.org/00fzmm222","country_code":"US","type":"education","lineage":["https://openalex.org/I100633361"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Honggang Wang","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, MA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, MA","institution_ids":["https://openalex.org/I100633361"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5051716922"],"corresponding_institution_ids":["https://openalex.org/I198089087"],"apc_list":null,"apc_paid":null,"fwci":3.0948,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.93285066,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7315986156463623},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.65562504529953},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6301620602607727},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5626639723777771},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5486963987350464},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5167731046676636},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4931130111217499},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4751814901828766},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.46475425362586975},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4419862926006317},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42781898379325867},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.420057475566864},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4131265878677368},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09624254703521729}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7315986156463623},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.65562504529953},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6301620602607727},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5626639723777771},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5486963987350464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5167731046676636},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4931130111217499},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4751814901828766},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.46475425362586975},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4419862926006317},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42781898379325867},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.420057475566864},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4131265878677368},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09624254703521729}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2018.8422107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2018.8422107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1590683836","https://openalex.org/W1656031401","https://openalex.org/W1995461206","https://openalex.org/W1999712889","https://openalex.org/W2017351764","https://openalex.org/W2023021494","https://openalex.org/W2025723605","https://openalex.org/W2055590061","https://openalex.org/W2069373269","https://openalex.org/W2084553975","https://openalex.org/W2102524092","https://openalex.org/W2103151433","https://openalex.org/W2116064496","https://openalex.org/W2116225745","https://openalex.org/W2159613676","https://openalex.org/W2294654473","https://openalex.org/W2313154375","https://openalex.org/W2437887222","https://openalex.org/W2469690627","https://openalex.org/W2587503868","https://openalex.org/W2962755669","https://openalex.org/W4235485727","https://openalex.org/W6677321020","https://openalex.org/W6733775978"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Indoor":[0],"human":[1,21,80],"activity":[2],"recognition":[3],"has":[4,181],"been":[5,182],"extensively":[6,183],"investigated.":[7],"However,":[8],"most":[9],"of":[10,79,87,133],"the":[11,43,68,76,115,150,157],"solutions":[12],"require":[13],"sensors":[14],"e.g.":[15],"9-axis":[16],"IMU":[17],"be":[18],"equipped":[19],"on":[20],"body":[22],"or":[23],"use":[24],"image":[25],"processing":[26],"that":[27,45],"presents":[28],"privacy":[29],"issues.":[30],"This":[31,52,82,124,179],"work":[32],"proposes":[33],"an":[34],"ambient":[35],"radar":[36,58],"sensor":[37],"based":[38],"a":[39,55,85,92,100,110,131,165,169,186],"solution":[40,53,83,125,180],"to":[41,59,74,96,104,113,129,144,155,173],"recognize":[42,176],"activities":[44,135,158],"humans":[46],"normally":[47],"perform":[48],"in":[49,185],"indoor":[50],"environments.":[51],"uses":[54,164],"7.8":[56],"GHz":[57],"emit":[60],"16":[61],"pulse":[62],"signals":[63,70],"every":[64],"second":[65],"and":[66,109,149,168,191],"samples":[67],"reflected":[69],"at":[71],"128":[72],"KHz":[73],"capture":[75],"fine":[77],"dynamics":[78],"activities.":[81],"designs":[84],"set":[86],"data":[88,93,117,148],"preprocessing":[89],"algorithms,":[90],"including":[91],"refining":[94],"algorithm":[95,103,112],"filter":[97,141],"outlier":[98],"data,":[99],"contrastive":[101],"divergence":[102],"remove":[105,145],"background":[106],"static":[107],"reflection,":[108],"transformation":[111],"convert":[114],"signal":[116],"into":[118,136,159],"feature-":[119],"rich":[120],"spatial":[121],"location":[122],"changes.":[123],"also":[126],"develops":[127],"schemes":[128],"separate":[130],"collection":[132],"various":[134],"individuals.":[137],"A":[138],"lowpass":[139],"frequency":[140],"is":[142,153],"designed":[143],"unwanted":[146],"noisy":[147],"motion":[151],"intensity":[152],"used":[154],"classify":[156],"two":[160],"high-level":[161],"groups.":[162],"It":[163],"slope-based":[166],"approach":[167],"k-":[170],"means":[171],"clustering":[172],"further":[174],"finely":[175],"each":[177],"activity.":[178],"evaluated":[184],"spacious":[187],"research":[188],"lab":[189],"room":[190],"shows":[192],"outstanding":[193],"accuracy.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
