{"id":"https://openalex.org/W7225644772","doi":"https://doi.org/10.64898/2026.11.05.26367336","title":"Accelerometer Data Harmonization and Feature Engineering for Gait Analytics","display_name":"Accelerometer Data Harmonization and Feature Engineering for Gait Analytics","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225644772","doi":"https://doi.org/10.64898/2026.11.05.26367336"},"language":"en","primary_location":{"id":"doi:10.64898/2026.11.05.26367336","doi":"https://doi.org/10.64898/2026.11.05.26367336","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.11.05.26367336","pdf_url":null,"source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.64898/2026.11.05.26367336","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092988654","display_name":"Friedrich Philipp Carrle","orcid":"https://orcid.org/0009-0008-4648-8765","observed_orcids":["https://orcid.org/0009-0008-4648-8765"]},"institutions":[{"id":"https://openalex.org/I41121874","display_name":"Heilbronn University","ror":"https://ror.org/04g5gcg95","country_code":"DE","type":"education","lineage":["https://openalex.org/I41121874"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friedrich Philipp Carrle","raw_affiliation_strings":["Heilbronn University;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heilbronn University;","institution_ids":["https://openalex.org/I41121874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080976451","display_name":"Fabian Schmidt","orcid":"https://orcid.org/0000-0001-7731-6685","observed_orcids":["https://orcid.org/0000-0001-7731-6685"]},"institutions":[{"id":"https://openalex.org/I41121874","display_name":"Heilbronn University","ror":"https://ror.org/04g5gcg95","country_code":"DE","type":"education","lineage":["https://openalex.org/I41121874"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Schmidt","raw_affiliation_strings":["Heilbronn University: Hochschule Heilbronn"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heilbronn University: Hochschule Heilbronn","institution_ids":["https://openalex.org/I41121874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073721548","display_name":"Alexandra Reichenbach","orcid":"https://orcid.org/0000-0003-4199-3005","observed_orcids":["https://orcid.org/0000-0003-4199-3005"]},"institutions":[{"id":"https://openalex.org/I41121874","display_name":"Heilbronn University","ror":"https://ror.org/04g5gcg95","country_code":"DE","type":"education","lineage":["https://openalex.org/I41121874"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexandra Reichenbach","raw_affiliation_strings":["Heilbronn University: Hochschule Heilbronn"],"raw_orcid":"https://orcid.org/0000-0003-4199-3005","affiliations":[{"raw_affiliation_string":"Heilbronn University: Hochschule Heilbronn","institution_ids":["https://openalex.org/I41121874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41121874"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9140999913215637,"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":0.9140999913215637,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.027899999171495438,"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.0203000009059906,"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/inertial-measurement-unit","display_name":"inertial measurement unit","score":0.9430000185966492},{"id":"https://openalex.org/keywords/mobile-devices","display_name":"mobile devices","score":0.5929999947547913},{"id":"https://openalex.org/keywords/data-warehouse","display_name":"data warehouse","score":0.6790000200271606},{"id":"https://openalex.org/keywords/star-schema","display_name":"star schema","score":0.8619999885559082},{"id":"https://openalex.org/keywords/sensor-placement","display_name":"sensor placement","score":0.9229999780654907},{"id":"https://openalex.org/keywords/gender-classification","display_name":"gender classification","score":0.7070000171661377},{"id":"https://openalex.org/keywords/data-integration","display_name":"data integration","score":0.6179999709129333},{"id":"https://openalex.org/keywords/cross-study-comparability","display_name":"cross-study comparability","score":0.7649999856948853}],"concepts":[{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.7653999924659729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6636000275611877},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.5823000073432922},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5496000051498413},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.49320000410079956},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4925000071525574},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4697999954223633},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45320001244544983},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.3946000039577484},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.38999998569488525},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.3882000148296356},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C18007350","wikidata":"https://www.wikidata.org/wiki/Q7394815","display_name":"STRIDE","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3449000120162964},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27790001034736633},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25760000944137573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.64898/2026.11.05.26367336","doi":"https://doi.org/10.64898/2026.11.05.26367336","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.11.05.26367336","pdf_url":null,"source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.64898/2026.11.05.26367336","doi":"https://doi.org/10.64898/2026.11.05.26367336","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.11.05.26367336","pdf_url":null,"source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3116998496","https://openalex.org/W6945976878","https://openalex.org/W3166957101","https://openalex.org/W2282396487","https://openalex.org/W2149115530","https://openalex.org/W1978108526","https://openalex.org/W2015046270","https://openalex.org/W7213256949","https://openalex.org/W3036418289","https://openalex.org/W2899671240"],"abstract_inverted_index":{"Gait":[0],"analytics":[1],"is":[2],"utilized":[3],"for":[4,117,128,238,244],"a":[5,81,89,107,212,236],"wide":[6],"range":[7],"of":[8,34,71,83,224],"health-related":[9],"applications,":[10],"ranging":[11,150],"from":[12,151,192],"fitness":[13],"tracking":[14],"to":[15,64,153,155],"medical":[16],"diagnostics,":[17],"and":[18,43,53,59,68,93,100,140,188,209,243,251],"beyond.":[19],"Inertial":[20],"measurement":[21],"units":[22],"that":[23,131,201],"are":[24],"ubiquitously":[25],"available":[26,78],"in":[27,39,169,233],"mobile":[28],"devices":[29],"provide":[30],"an":[31,55,124],"accessible":[32],"means":[33],"gait":[35,73,148,203,241],"analysis":[36,70,242],"but":[37,216],"differences":[38,168],"sensor":[40,101,141,252],"specifications,":[41],"placement,":[42],"recording":[44],"protocols":[45],"limit":[46],"comparability":[47,95,223],"across":[48,98,138],"studies.":[49],"This":[50],"study":[51],"developed":[52],"evaluated":[54],"analysis-centered":[56],"data":[57,91,205],"warehouse":[58],"standardized":[60,217],"quality-assessed":[61],"processing":[62,218],"pipeline":[63],"facilitate":[65],"the":[66,129,225],"integration":[67],"joint":[69],"heterogeneous":[72,202],"accelerometer":[74,204],"data.":[75],"Six":[76],"publicly":[77],"datasets":[79,99,139,194,250],"including":[80],"total":[82],"935":[84],"persons":[85],"were":[86],"integrated":[87,208],"into":[88],"star-schema":[90],"warehouse,":[92],"feature":[94,118],"was":[96,120],"assessed":[97],"locations.":[102,179],"Gender":[103,180],"classification":[104,181],"served":[105],"as":[106,115],"proof-of-concept":[108],"downstream":[109],"analysis.":[110],"Gait-cycle":[111],"extraction,":[112,119],"which":[113],"serves":[114],"foundation":[116,237],"successfully":[121],"achieved":[122],"with":[123,143,249],"accuracy":[125],"above":[126],"99%":[127],"dataset":[130],"provides":[132,235],"ground":[133],"truth":[134],"information.":[135],"Comparability":[136],"varied":[137],"configurations,":[142],"correlation":[144],"coefficients":[145],"between":[146,174],"average":[147],"cycles":[149],"0.5":[152],"close":[154],"1.0.":[156],"Centrally":[157],"positioned":[158],"sensors":[159,175],"generally":[160],"show":[161],"greater":[162],"correspondence":[163],"than":[164],"peripheral":[165],"sensors,":[166],"although":[167],"statistical":[170],"features":[171],"persist":[172],"even":[173],"at":[176],"nominally":[177],"identical":[178],"performance":[182],"remains":[183],"largely":[184],"near":[185],"chance":[186],"level,":[187],"no":[189],"consistent":[190],"benefit":[191],"pooling":[193],"could":[195],"be":[196,207],"established.":[197],"These":[198],"findings":[199],"demonstrate":[200],"can":[206],"processed":[210],"within":[211],"common":[213],"analytical":[214],"framework,":[215],"alone":[219],"does":[220],"not":[221],"ensure":[222],"resulting":[226],"features.":[227],"The":[228],"proposed":[229],"open-source":[230],"framework":[231],"implemented":[232],"Python":[234],"reproducible":[239],"cross-study":[240],"investigating":[245],"residual":[246],"heterogeneity":[247],"associated":[248],"configurations.":[253]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}