{"id":"https://openalex.org/W7124900145","doi":"https://doi.org/10.1109/bsn66969.2025.11337750","title":"PPGWeaver: Diffusion-Augmented Models for Real-Time Heart Rate Estimation on Microcontrollers","display_name":"PPGWeaver: Diffusion-Augmented Models for Real-Time Heart Rate Estimation on Microcontrollers","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W7124900145","doi":"https://doi.org/10.1109/bsn66969.2025.11337750"},"language":null,"primary_location":{"id":"doi:10.1109/bsn66969.2025.11337750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn66969.2025.11337750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Body Sensor Networks (BSN)","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/A5007651578","display_name":"Vinayak Narasimhan","orcid":"https://orcid.org/0000-0003-4165-402X"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Vinayak Narasimhan","raw_affiliation_strings":["Samsung System LSI, Samsung Semiconductor,Pasadena,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung System LSI, Samsung Semiconductor,Pasadena,CA,USA","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031727521","display_name":"Raimi Shah","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raimi Shah","raw_affiliation_strings":["Synthefy,Austin,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synthefy,Austin,TX,USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090536067","display_name":"Shubhankar Agarwal","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shubhankar Agarwal","raw_affiliation_strings":["Synthefy,Austin,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synthefy,Austin,TX,USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067900868","display_name":"Sai Shankar Narasimhan","orcid":"https://orcid.org/0000-0001-9714-3865"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sai Shankar Narasimhan","raw_affiliation_strings":["Synthefy,Austin,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synthefy,Austin,TX,USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091263239","display_name":"Shailabh Kumar","orcid":"https://orcid.org/0000-0001-5383-3282"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Shailabh Kumar","raw_affiliation_strings":["Samsung System LSI, Samsung Semiconductor,Pasadena,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung System LSI, Samsung Semiconductor,Pasadena,CA,USA","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002446879","display_name":"Sang Kyu Kim","orcid":"https://orcid.org/0000-0003-4803-1327"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang Kyu Kim","raw_affiliation_strings":["Samsung System LSI, Samsung Electronics,Hwaseong,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung System LSI, Samsung Electronics,Hwaseong,South Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024120306","display_name":"Sandeep Chinchali","orcid":"https://orcid.org/0000-0002-0601-3633"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sandeep Chinchali","raw_affiliation_strings":["Synthefy,Austin,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Synthefy,Austin,TX,USA","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027631236","display_name":"Radwanul Hasan Siddique","orcid":"https://orcid.org/0000-0001-7494-5857"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Radwanul Hasan Siddique","raw_affiliation_strings":["Samsung System LSI, Samsung Semiconductor,Pasadena,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung System LSI, Samsung Semiconductor,Pasadena,CA,USA","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5321835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9340999722480774,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9340999722480774,"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.016200000420212746,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.008100000210106373,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/microcontroller","display_name":"Microcontroller","score":0.630299985408783},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.45329999923706055},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4106000065803528},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.40130001306533813},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.38679999113082886},{"id":"https://openalex.org/keywords/heart-rate-monitor","display_name":"Heart rate monitor","score":0.35839998722076416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34299999475479126},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3264000117778778},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.3199000060558319}],"concepts":[{"id":"https://openalex.org/C173018170","wikidata":"https://www.wikidata.org/wiki/Q165678","display_name":"Microcontroller","level":2,"score":0.630299985408783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5885000228881836},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.45329999923706055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4494999945163727},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4106000065803528},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.40130001306533813},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C2775893642","wikidata":"https://www.wikidata.org/wiki/Q925303","display_name":"Heart rate monitor","level":4,"score":0.35839998722076416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34299999475479126},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C116390426","wikidata":"https://www.wikidata.org/wiki/Q7187885","display_name":"Photoplethysmogram","level":3,"score":0.3075999915599823},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bsn66969.2025.11337750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn66969.2025.11337750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Body Sensor Networks (BSN)","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":8,"referenced_works":["https://openalex.org/W2962182608","https://openalex.org/W2995086119","https://openalex.org/W3154084328","https://openalex.org/W3192530442","https://openalex.org/W3206929260","https://openalex.org/W4309401031","https://openalex.org/W4397028095","https://openalex.org/W4414494323"],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,21,45,67,105,118],"compact,":[3],"deployable":[4],"heart":[5],"rate":[6],"(HR)":[7],"estimation":[8],"system":[9],"using":[10,127],"photoplethysmography":[11],"(PPG)":[12],"and":[13,57,84,130],"inertial":[14],"measurement":[15],"unit":[16],"(IMU)":[17],"data,":[18],"combining":[19],"TimeWeaver,":[20],"conditional":[22],"diffusion":[23],"model":[24,89],"for":[25,122],"metadata-aware":[26],"synthetic":[27],"augmentation,":[28],"with":[29,41],"progressive":[30],"structured":[31],"pruning":[32],"of":[33,50,100],"Temporal":[34],"Convolutional":[35],"Networks":[36],"(TCNs).":[37],"Our":[38,115],"smallest":[39],"model,":[40],"1.56k":[42],"parameters,":[43],"achieves":[44],"mean":[46],"absolute":[47],"error":[48],"(MAE)":[49],"4.92":[51],"BPM":[52],"on":[53,66,80,111],"the":[54,98],"PPG-DaLiA":[55],"dataset":[56],"supports":[58],"real-time":[59],"inference":[60],"(<tex":[61],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[62],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$&lt;{40":[63],"ms}$</tex>":[64],"latency)":[65],"64":[68],"MHz":[69],"ARM":[70],"Cortex-M4F":[71],"microcontroller":[72],"(MCU)":[73],"without":[74],"requiring":[75],"quantization.":[76],"Synthetic":[77],"data":[78,113],"conditioned":[79],"subject":[81],"metadata,":[82],"HR,":[83],"activity":[85],"type":[86],"significantly":[87],"enhances":[88],"generalization,":[90],"enabling":[91],"pruned":[92],"models":[93],"to":[94,109],"match":[95],"or":[96],"exceed":[97],"accuracy":[99],"larger":[101],"baselines,":[102],"achieving":[103],"over":[104],"23%":[106],"improvement":[107],"compared":[108],"training":[110,129],"real":[112],"alone.":[114],"work":[116],"establishes":[117],"new":[119],"Pareto":[120],"frontier":[121],"real-time,":[123],"on-device":[124],"HR":[125],"monitoring":[126],"diffusion-augmented":[128],"sub-2":[131],"k":[132],"parameter":[133],"models.":[134]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-21T00:00:00"}