{"id":"https://openalex.org/W3085381598","doi":"https://doi.org/10.1145/3410530.3414397","title":"VibroScale","display_name":"VibroScale","publication_year":2020,"publication_date":"2020-09-10","ids":{"openalex":"https://openalex.org/W3085381598","doi":"https://doi.org/10.1145/3410530.3414397","mag":"3085381598"},"language":"en","primary_location":{"id":"doi:10.1145/3410530.3414397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3410530.3414397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","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/A5101912178","display_name":"Shibo Zhang","orcid":"https://orcid.org/0000-0003-3054-9590"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shibo Zhang","raw_affiliation_strings":["Northwestern University"],"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053485450","display_name":"Qiuyang Xu","orcid":"https://orcid.org/0000-0001-7132-1707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiuyang Xu","raw_affiliation_strings":["Northwestern University"],"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023938040","display_name":"Sougata Sen","orcid":"https://orcid.org/0000-0002-2466-0025"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sougata Sen","raw_affiliation_strings":["Northwestern University"],"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001385856","display_name":"Nabil Alshurafa","orcid":"https://orcid.org/0000-0001-6681-7564"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nabil Alshurafa","raw_affiliation_strings":["Northwestern University"],"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101912178"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3908,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.61907643,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"176","last_page":"179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9616000056266785,"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":0.9616000056266785,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.9527999758720398,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9516000151634216,"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/measure","display_name":"Measure (data warehouse)","score":0.791445255279541},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6685217022895813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6139546632766724},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5591496825218201},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48170262575149536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4568832516670227},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.4502437114715576},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.4422807991504669},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.4360572397708893},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3960914611816406},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31072932481765747},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.2903324067592621},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19679588079452515},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1935867965221405},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08721593022346497}],"concepts":[{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.791445255279541},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6685217022895813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6139546632766724},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5591496825218201},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48170262575149536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4568832516670227},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.4502437114715576},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.4422807991504669},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.4360572397708893},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3960914611816406},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31072932481765747},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2903324067592621},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19679588079452515},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1935867965221405},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08721593022346497},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3410530.3414397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3410530.3414397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1993100747","https://openalex.org/W2081311480","https://openalex.org/W2091311593","https://openalex.org/W2150639461","https://openalex.org/W2466209343","https://openalex.org/W2538172027","https://openalex.org/W2566338991","https://openalex.org/W2896198943","https://openalex.org/W2919210463","https://openalex.org/W2925634966","https://openalex.org/W3003568014","https://openalex.org/W3036911678","https://openalex.org/W3096917022","https://openalex.org/W3104452718"],"related_works":["https://openalex.org/W2087911819","https://openalex.org/W2136152605","https://openalex.org/W3149853164","https://openalex.org/W2971924187","https://openalex.org/W4366814132","https://openalex.org/W2073947232","https://openalex.org/W2180861079","https://openalex.org/W4387072315","https://openalex.org/W4312295548","https://openalex.org/W2542451093"],"abstract_inverted_index":{"Smartphones,":[0],"with":[1,146],"their":[2],"ubiquity":[3],"and":[4,81,111,118,154,175],"plethora":[5],"of":[6,40,54,62,94,115,127,144,151,160,179,182],"embedded":[7],"sensors":[8],"enable":[9],"on-the-go":[10],"measurement.":[11],"Here,":[12],"we":[13,85,136],"describe":[14,31],"one":[15,142],"novel":[16],"measurement":[17],"potential,":[18],"weight":[19,39,53,126,178],"measurement,":[20],"by":[21],"turning":[22],"an":[23,95,132],"everyday":[24,113],"smartphone":[25,79],"into":[26],"a":[27,64,78,147,155],"weighing":[28,72],"scale.":[29,134],"We":[30,76,101,162],"VibroScale,":[32,87],"our":[33,103],"vibration-based":[34],"approach":[35,168],"to":[36,49,172],"measuring":[37],"the":[38,52,60,90,99,125,177],"objects":[41,55,114],"that":[42,88,138,164],"are":[43],"small":[44,73],"in":[45,56,71,165],"size.":[46],"Being":[47],"able":[48],"objectively":[50],"measure":[51,124,141,176],"free-living":[57],"settings,":[58],"without":[59,129],"burden":[61],"carrying":[63],"scale,":[65],"has":[66],"several":[67],"possible":[68],"uses,":[69],"particularly":[70],"food":[74],"items.":[75],"designed":[77],"app":[80],"regression":[82],"algorithm,":[83],"which":[84],"termed":[86],"estimates":[89],"relative":[91],"induced":[92],"intensity":[93],"object":[96,145],"placed":[97],"on":[98,131],"smartphone.":[100],"tested":[102],"proposed":[104],"method":[105,122],"using":[106],"more":[107],"than":[108],"50":[109],"fruits":[110],"other":[112],"different":[116],"sizes":[117],"weights.":[119],"Our":[120],"smartphone-based":[121],"can":[123,140,169],"fruit":[128],"relying":[130],"actual":[133],"Overall,":[135],"observed":[137],"VibroScale":[139],"type":[143],"mean":[148,156],"absolute":[149,157],"error":[150,159],"12.4":[152],"grams":[153],"percentage":[158],"7.7%.":[161],"believe":[163],"future":[166],"this":[167],"be":[170],"generalized":[171],"estimate":[173],"calories":[174],"various":[180],"types":[181],"objects.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-09-21T00:00:00"}
