{"id":"https://openalex.org/W4387542706","doi":"https://doi.org/10.1145/3615834.3615836","title":"Classification of freezing of gait using accelerometer data: A systematic performance evaluation approach","display_name":"Classification of freezing of gait using accelerometer data: A systematic performance evaluation approach","publication_year":2023,"publication_date":"2023-09-21","ids":{"openalex":"https://openalex.org/W4387542706","doi":"https://doi.org/10.1145/3615834.3615836"},"language":"en","primary_location":{"id":"doi:10.1145/3615834.3615836","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615834.3615836","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615834.3615836","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3615834.3615836","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011233967","display_name":"Aditi Site","orcid":"https://orcid.org/0000-0001-9802-2061"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Aditi Site","raw_affiliation_strings":["Tampere university, Finland"],"affiliations":[{"raw_affiliation_string":"Tampere university, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035297149","display_name":"Jari Nurmi","orcid":"https://orcid.org/0000-0003-2169-4606"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jari Nurmi","raw_affiliation_strings":["Tampere university, Finland"],"affiliations":[{"raw_affiliation_string":"Tampere university, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063382658","display_name":"Elena Simona Lohan","orcid":"https://orcid.org/0000-0003-1718-6924"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Elena Simona Lohan","raw_affiliation_strings":["Tampere university, Finland"],"affiliations":[{"raw_affiliation_string":"Tampere university, Finland","institution_ids":["https://openalex.org/I166825849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011233967"],"corresponding_institution_ids":["https://openalex.org/I166825849"],"apc_list":null,"apc_paid":null,"fwci":0.1126,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41686802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958999752998352,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.8371767997741699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6347591280937195},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.5895956754684448},{"id":"https://openalex.org/keywords/gait-analysis","display_name":"Gait analysis","score":0.484413206577301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3580073118209839},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.34052973985671997},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06888991594314575}],"concepts":[{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.8371767997741699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6347591280937195},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.5895956754684448},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.484413206577301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3580073118209839},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.34052973985671997},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06888991594314575},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3615834.3615836","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615834.3615836","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615834.3615836","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:trepo.tuni.fi:10024/207532","is_oa":true,"landing_page_url":"https://trepo.tuni.fi/handle/10024/207532","pdf_url":null,"source":{"id":"https://openalex.org/S7407055260","display_name":"Trepo - Institutional Repository of Tampere University","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference"}],"best_oa_location":{"id":"doi:10.1145/3615834.3615836","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615834.3615836","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615834.3615836","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387542706.pdf","grobid_xml":"https://content.openalex.org/works/W4387542706.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W2897498060","https://openalex.org/W2950689162","https://openalex.org/W2993533711","https://openalex.org/W3001492333","https://openalex.org/W3007822349","https://openalex.org/W3013072213","https://openalex.org/W3049059966","https://openalex.org/W3087661417","https://openalex.org/W3093916890","https://openalex.org/W3110996655","https://openalex.org/W3199483519","https://openalex.org/W3206919173","https://openalex.org/W4220986068","https://openalex.org/W4283208220"],"related_works":["https://openalex.org/W2133973503","https://openalex.org/W2471060339","https://openalex.org/W2148547327","https://openalex.org/W1989734657","https://openalex.org/W4226236273","https://openalex.org/W2125892956","https://openalex.org/W1557333606","https://openalex.org/W4226004263","https://openalex.org/W2130975749","https://openalex.org/W2493973380"],"abstract_inverted_index":{"Parkinson\u2019s":[0,78,180],"disease":[1],"is":[2,30],"one":[3,31],"of":[4,17,28,50,68,75,88,122,124,156,176,189,197,203],"the":[5,14,38,44,51,66,73,120,160],"most":[6],"common":[7],"neurodegenerative":[8],"chronic":[9],"diseases":[10],"which":[11,35],"can":[12,36,60,71],"affect":[13],"patient\u2019s":[15],"quality":[16,67],"life":[18,69],"by":[19,128],"creating":[20],"several":[21],"motor":[22,33],"and":[23,57,70,97,106,113,144,162,169,199,201,205,209],"non-motor":[24],"impairments.":[25],"The":[26,48],"freezing":[27,123,175],"gait":[29,125,177],"such":[32,138],"impairment":[34],"cause":[37],"inability":[39],"to":[40,46,159,173,185],"move":[41],"forward":[42],"despite":[43],"intention":[45],"walk.":[47],"identification":[49],"freezing-of-gait":[52],"events":[53,121,178],"using":[54,129],"sensor":[55],"technology":[56],"machine-learning":[58],"algorithms":[59,91,135],"result":[61],"in":[62,65,77,126,147,179],"an":[63,153],"improvement":[64],"decrease":[72],"risk":[74],"fall":[76],"patients.":[79,181],"Our":[80],"study":[81],"focuses":[82],"on":[83,109],"a":[84,94,148],"systematic":[85],"performance":[86],"evaluation":[87],"machine":[89],"learning":[90],"for":[92,118,136,167,207],"developing":[93],"good":[95],"fit":[96,164],"generalized":[98],"model.":[99],"In":[100],"this":[101],"work,":[102],"we":[103],"train":[104],"time-domain":[105],"frequency-domain-transform-based":[107],"features":[108],"fully":[110],"connected":[111],"artificial":[112,168],"deep":[114,170],"neural":[115,171],"network":[116,172],"algorithm":[117],"classifying":[119],"patients":[127],"accelerometer":[130],"data.":[131],"We":[132,151,182],"evaluate":[133],"these":[134],"hyperparameters":[137],"as":[139],"batch":[140,194],"size,":[141],"optimizer":[142],"type,":[143],"window":[145],"sizes":[146,195],"step-wise":[149],"process.":[150],"identify":[152],"optimal":[154],"combination":[155],"parameters":[157],"according":[158],"accuracy":[161,188],"model":[163],"optimality":[165],"metrics,":[166],"classify":[174],"were":[183],"able":[184],"achieve":[186],"classification":[187],"-":[190],"with":[191],"Adam":[192],"optimizer,":[193],"(BS)":[196],"256":[198],"8":[200],"epochs":[202],"60":[204],"40":[206],"ANN":[208],"DNN":[210],"respectively.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
