{"id":"https://openalex.org/W4402715781","doi":"https://doi.org/10.1109/mwscas60917.2024.10658849","title":"An AI-Based Approach for Accurate Fall Detection and Prediction Using Wearable Sensors","display_name":"An AI-Based Approach for Accurate Fall Detection and Prediction Using Wearable Sensors","publication_year":2024,"publication_date":"2024-08-11","ids":{"openalex":"https://openalex.org/W4402715781","doi":"https://doi.org/10.1109/mwscas60917.2024.10658849"},"language":"en","primary_location":{"id":"doi:10.1109/mwscas60917.2024.10658849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mwscas60917.2024.10658849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS)","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/A5101985725","display_name":"Muhammad Azeem Sarwar","orcid":null},"institutions":[{"id":"https://openalex.org/I207789805","display_name":"Lahore University of Management Sciences","ror":"https://ror.org/05b5x4a35","country_code":"PK","type":"education","lineage":["https://openalex.org/I207789805"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Azeem Sarwar","raw_affiliation_strings":["LUMS,Electrical Engineering Department,Lahore,Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LUMS,Electrical Engineering Department,Lahore,Pakistan","institution_ids":["https://openalex.org/I207789805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107490585","display_name":"Brandon Chea","orcid":null},"institutions":[{"id":"https://openalex.org/I52669646","display_name":"Western Washington University","ror":"https://ror.org/05wn7r715","country_code":"US","type":"education","lineage":["https://openalex.org/I52669646"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brandon Chea","raw_affiliation_strings":["Western Washington University,Engineering and Design Department,Bellingham,WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Washington University,Engineering and Design Department,Bellingham,WA","institution_ids":["https://openalex.org/I52669646"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114231316","display_name":"Max Widjaja","orcid":null},"institutions":[{"id":"https://openalex.org/I52669646","display_name":"Western Washington University","ror":"https://ror.org/05wn7r715","country_code":"US","type":"education","lineage":["https://openalex.org/I52669646"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Max Widjaja","raw_affiliation_strings":["Western Washington University,Engineering and Design Department,Bellingham,WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Washington University,Engineering and Design Department,Bellingham,WA","institution_ids":["https://openalex.org/I52669646"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017185283","display_name":"Wala Saadeh","orcid":"https://orcid.org/0000-0002-6084-6396"},"institutions":[{"id":"https://openalex.org/I52669646","display_name":"Western Washington University","ror":"https://ror.org/05wn7r715","country_code":"US","type":"education","lineage":["https://openalex.org/I52669646"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wala Saadeh","raw_affiliation_strings":["Western Washington University,Engineering and Design Department,Bellingham,WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Washington University,Engineering and Design Department,Bellingham,WA","institution_ids":["https://openalex.org/I52669646"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5311,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84160333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"118","last_page":"121"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9997000098228455,"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":0.9861000180244446,"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"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.954800009727478,"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/wearable-computer","display_name":"Wearable computer","score":0.7824735641479492},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6532589197158813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5215420722961426},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3343971371650696},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.12575826048851013}],"concepts":[{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.7824735641479492},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6532589197158813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5215420722961426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3343971371650696},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.12575826048851013}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mwscas60917.2024.10658849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mwscas60917.2024.10658849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W123295786","https://openalex.org/W1980340196","https://openalex.org/W2035227519","https://openalex.org/W2088371259","https://openalex.org/W2413337736","https://openalex.org/W2516506354","https://openalex.org/W2543632018","https://openalex.org/W2555209581","https://openalex.org/W2798222646","https://openalex.org/W2913601164","https://openalex.org/W2938949242","https://openalex.org/W3014017840","https://openalex.org/W3016966174","https://openalex.org/W3083408317","https://openalex.org/W4312952558","https://openalex.org/W4320920821","https://openalex.org/W4327518065","https://openalex.org/W4378194824","https://openalex.org/W6725990282","https://openalex.org/W6775698563"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Falls":[0],"are":[1],"a":[2],"paramount":[3],"concern":[4],"in":[5,25,105],"elderly":[6,26],"care":[7,27],"and":[8,13,23,39,81,99,111],"injury":[9],"prevention,":[10],"necessitating":[11],"accurate":[12],"timely":[14],"inter-ventions.":[15],"This":[16,94],"work":[17],"contributes":[18],"to":[19,68,86],"transforming":[20],"fall":[21],"detection":[22,38,98],"prevention":[24],"by":[28],"combining":[29],"Convolutional":[30],"Long":[31],"Short-Term":[32],"Memory":[33],"(ConvLSTM)":[34],"networks":[35],"for":[36,42],"real-time":[37,69,97],"Exponential":[40],"Smoothing":[41],"early":[43,100],"prediction.":[44],"The":[45],"proposed":[46],"solution":[47],"achieves":[48],"an":[49,90],"impressive":[50],"Fl-score":[51],"of":[52,60,92,96],"0.991":[53],"when":[54],"tested":[55],"on":[56],"various":[57],"public":[58],"datasets":[59],"81":[61],"subjects,":[62],"showcasing":[63],"its":[64],"effectiveness.":[65],"In":[66],"addition":[67],"detection,":[70],"the":[71,103],"approach":[72],"introduces":[73],"proactive":[74],"prediction,":[75],"forecasting":[76],"falls":[77],"before":[78],"they":[79],"occur":[80],"significantly":[82],"reducing":[83],"response":[84],"time":[85],"1100\u20131250":[87],"ms":[88],"with":[89],"accuracy":[91],"98.3%.":[93],"integration":[95],"prediction":[101],"addresses":[102],"gap":[104],"traditional":[106],"systems,":[107],"improving":[108],"patient":[109],"safety":[110],"lessening":[112],"healthcare":[113],"burdens.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
