Heart beats in the cloud: distributed analysis of electrophysiological 'Big Data' using cloud computing for epilepsy clinical research
The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorit...
Gespeichert in:
| Veröffentlicht in: | Journal of the American Medical Informatics Association : JAMIA Jg. 21; H. 2; S. 263 |
|---|---|
| Hauptverfasser: | , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
England
01.03.2014
|
| Schlagworte: | |
| ISSN: | 1527-974X, 1527-974X |
| Online-Zugang: | Weitere Angaben |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies.
We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy.
Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology.
Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards.
The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research. |
|---|---|
| AbstractList | The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies.
We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy.
Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology.
Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards.
The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research. The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies.OBJECTIVEThe rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple disease domains, such as epilepsy and sleep medicine. To facilitate secondary use of these data, there is an urgent need to develop novel algorithms and informatics approaches using new cloud computing technologies as well as ontologies for collaborative multicenter studies.We present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy.MATERIALS AND METHODSWe present the Cloudwave platform, which (a) defines parallelized algorithms for computing cardiac measures using the MapReduce parallel programming framework, (b) supports real-time interaction with large volumes of electrophysiological signals, and (c) features signal visualization and querying functionalities using an ontology-driven web-based interface. Cloudwave is currently used in the multicenter National Institute of Neurological Diseases and Stroke (NINDS)-funded Prevention and Risk Identification of SUDEP (sudden unexplained death in epilepsy) Mortality (PRISM) project to identify risk factors for sudden death in epilepsy.Comparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology.RESULTSComparative evaluations of Cloudwave with traditional desktop approaches to compute cardiac measures (eg, QRS complexes, RR intervals, and instantaneous heart rate) on epilepsy patient data show one order of magnitude improvement for single-channel ECG data and 20 times improvement for four-channel ECG data. This enables Cloudwave to support real-time user interaction with signal data, which is semantically annotated with a novel epilepsy and seizure ontology.Data privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards.DISCUSSIONData privacy is a critical issue in using cloud infrastructure, and cloud platforms, such as Amazon Web Services, offer features to support Health Insurance Portability and Accountability Act standards.The Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research.CONCLUSIONThe Cloudwave platform is a new approach to leverage of large-scale electrophysiological data for advancing multicenter clinical research. |
| Author | Lhatoo, Samden D Kaffashi, Farhad Garg, Gaurav Zhang, Guo-Qiang Bozorgi, Alireza Chen, Chien-Hun Sahoo, Satya S Jayapandian, Catherine Chung, Stephanie Loparo, Kenneth |
| Author_xml | – sequence: 1 givenname: Satya S surname: Sahoo fullname: Sahoo, Satya S organization: Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA – sequence: 2 givenname: Catherine surname: Jayapandian fullname: Jayapandian, Catherine – sequence: 3 givenname: Gaurav surname: Garg fullname: Garg, Gaurav – sequence: 4 givenname: Farhad surname: Kaffashi fullname: Kaffashi, Farhad – sequence: 5 givenname: Stephanie surname: Chung fullname: Chung, Stephanie – sequence: 6 givenname: Alireza surname: Bozorgi fullname: Bozorgi, Alireza – sequence: 7 givenname: Chien-Hun surname: Chen fullname: Chen, Chien-Hun – sequence: 8 givenname: Kenneth surname: Loparo fullname: Loparo, Kenneth – sequence: 9 givenname: Samden D surname: Lhatoo fullname: Lhatoo, Samden D – sequence: 10 givenname: Guo-Qiang surname: Zhang fullname: Zhang, Guo-Qiang |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24326538$$D View this record in MEDLINE/PubMed |
| BookMark | eNpNUMtOwzAQtBAIaOELkJBvcAnYjuPE3KA8ilSJC0jcqo2zaV05cYidQ3-A7yZQkDjt7MzsrHYnZL_1LRJyxtkV56m6hsbCpnWJYDxNGBM8U3vkmGciT3Qu3_f_4SMyCWHDGFcizQ7JkZCpUFlaHJPPOUIfaYkQA7UtjWukxvmhuqGVDbG35RCxotCC2wYbqK8pOjSx9916JLzzK2vA0Ys7u6L3EOGCDsG2q10INb7phvjd176n2FmHXdiOom1_xnoM436zPiEHNbiAp791St4eH15n82Tx8vQ8u10kRrIsJqUuQBrQWqOCVOWZ0TVjRSUNN-NtqKpcKVmA5lrUeW4UL2owRqIqhTBaiSm53OV2vf8YMMRlY4NB56BFP4Qll1rzVOhCjtbzX-tQNlgtu9420G-Xf78TX1uYdsM |
| CitedBy_id | crossref_primary_10_1177_1460458216660754 crossref_primary_10_3389_fpubh_2022_838438 crossref_primary_10_1109_TIM_2015_2490858 crossref_primary_10_1111_epi_16633 crossref_primary_10_1016_j_bspc_2019_03_004 crossref_primary_10_1007_s00530_020_00736_8 crossref_primary_10_1016_j_smrv_2021_101529 crossref_primary_10_1136_bmjopen_2015_010579 crossref_primary_10_1097_WCO_0000000000000184 crossref_primary_10_1111_ropr_12077 crossref_primary_10_1088_1361_6579_ab7cb5 crossref_primary_10_4137_BII_S31559 crossref_primary_10_1177_1176934319888904 crossref_primary_10_3390_info11020060 crossref_primary_10_1097_ANA_0000000000000659 crossref_primary_10_3390_e21030274 crossref_primary_10_1016_j_artmed_2017_12_004 crossref_primary_10_1371_journal_pone_0266565 crossref_primary_10_1007_s10844_019_00557_w crossref_primary_10_1177_1460458215572924 crossref_primary_10_1016_j_techfore_2015_12_019 crossref_primary_10_1080_23270012_2016_1141332 crossref_primary_10_1016_j_ijmedinf_2016_11_006 crossref_primary_10_1186_s40537_023_00763_y crossref_primary_10_1016_j_eswa_2018_12_056 crossref_primary_10_3390_electronics14122468 crossref_primary_10_1016_j_cnp_2025_09_003 crossref_primary_10_1016_j_im_2017_04_001 |
| ContentType | Journal Article |
| DBID | CGR CUY CVF ECM EIF NPM 7X8 |
| DOI | 10.1136/amiajnl-2013-002156 |
| DatabaseName | Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
| DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE MEDLINE - Academic |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database |
| DeliveryMethod | no_fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1527-974X |
| ExternalDocumentID | 24326538 |
| Genre | Journal Article Research Support, N.I.H., Extramural |
| GeographicLocations | United States |
| GeographicLocations_xml | – name: United States |
| GrantInformation_xml | – fundername: NCATS NIH HHS grantid: UL1TR000439 – fundername: NINDS NIH HHS grantid: 1-P20-NS076965-01 – fundername: NINDS NIH HHS grantid: P20 NS076965 – fundername: NCATS NIH HHS grantid: UL1 TR000439 |
| GroupedDBID | --- --K .DC .GJ 0R~ 18M 1B1 1TH 29L 2WC 4.4 48X 53G 5GY 5RE 5WD 6PF 7RV 7X7 7~T 88E 88I 8AF 8AO 8FE 8FG 8FI 8FJ 8FW AABZA AACZT AAEDT AAJQQ AALRI AAMVS AAOGV AAPGJ AAPQZ AAPXW AARHZ AAUAY AAUQX AAVAP AAWDT AAWTL AAXUO ABDFA ABEJV ABEUO ABGNP ABIXL ABJNI ABNHQ ABOCM ABPQP ABPTD ABQLI ABQNK ABSMQ ABUWG ABVGC ABWST ABWVN ABXVV ACFRR ACGFO ACGFS ACGOD ACHQT ACRPL ACUFI ACUTJ ACVCV ACYHN ACZBC ADBBV ADGZP ADHKW ADHZD ADIPN ADJOM ADMTO ADMUD ADNBA ADNMO ADQBN ADRTK ADVEK ADYVW AEGPL AEJOX AEKSI AEMDU AEMQT AENEX AENZO AEPUE AETBJ AEWNT AFFQV AFFZL AFIYH AFKRA AFOFC AFXAL AFYAG AGINJ AGKRT AGMDO AGQXC AGSYK AGUTN AHMBA AHMMS AJDVS AJEEA AJNCP ALIPV ALMA_UNASSIGNED_HOLDINGS ALUQC ALXQX APIBT APJGH AQDSO AQKUS AQUVI ARAPS ATGXG AVNTJ AVWKF AXUDD AYCSE AZQEC BAWUL BAYMD BCRHZ BENPR BEYMZ BGLVJ BHONS BKEYQ BPHCQ BTRTY BVRKM BVXVI BZKNY C1A C45 CCPQU CDBKE CGR CS3 CUY CVF DAKXR DIK DILTD DU5 DWQXO E3Z EBD EBS ECM EIF EIHJH EJD EMOBN ENERS EO8 EX3 F5P FDB FECEO FLUFQ FOEOM FOTVD FQBLK FYUFA G-Q GAUVT GJXCC GNUQQ GX1 H13 HAR HCIFZ HMCUK IH2 IHE J21 JXSIZ K6V K7- KBUDW KOP KSI KSN LSO M0T M1P M2P M2Q M41 MBLQV MHKGH NAPCQ NOMLY NOYVH NPM NQ- NU- NVLIB O9- OAUYM OAWHX OBFPC OCZFY ODMLO OJQWA OJZSN OK1 OPAEJ OVD OWPYF P2P P62 PAFKI PCD PEELM PHGZT PQQKQ PROAC PSQYO Q5Y R53 RIG ROL ROX ROZ RPM RPZ RUSNO RWL RXO S0X SSZ SV3 TAE TEORI TJX TMA UKHRP WOQ WOW YAYTL YHZ YKOAZ YXANX ZGI ~S- 77I 7X8 AJBYB |
| ID | FETCH-LOGICAL-c405t-b98a4ca999e6a3675c9f008d4c1c162e6d76648a9192f77c618facc4e6b22c962 |
| IEDL.DBID | 7X8 |
| ISICitedReferencesCount | 50 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000331263600012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1527-974X |
| IngestDate | Sun Sep 28 11:40:53 EDT 2025 Thu Apr 03 07:05:23 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 2 |
| Keywords | Epilepsy and Seizure Ontology SUDEP Cloudwave Electrophsyiological Big Data MapReduce |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c405t-b98a4ca999e6a3675c9f008d4c1c162e6d76648a9192f77c618facc4e6b22c962 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| OpenAccessLink | https://academic.oup.com/jamia/article-pdf/21/2/263/9517748/21-2-263.pdf |
| PMID | 24326538 |
| PQID | 1499132984 |
| PQPubID | 23479 |
| ParticipantIDs | proquest_miscellaneous_1499132984 pubmed_primary_24326538 |
| PublicationCentury | 2000 |
| PublicationDate | 2014-03-01 |
| PublicationDateYYYYMMDD | 2014-03-01 |
| PublicationDate_xml | – month: 03 year: 2014 text: 2014-03-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England |
| PublicationTitle | Journal of the American Medical Informatics Association : JAMIA |
| PublicationTitleAlternate | J Am Med Inform Assoc |
| PublicationYear | 2014 |
| SSID | ssj0016235 |
| Score | 2.3397064 |
| Snippet | The rapidly growing volume of multimodal electrophysiological signal data is playing a critical role in patient care and clinical research across multiple... |
| SourceID | proquest pubmed |
| SourceType | Aggregation Database Index Database |
| StartPage | 263 |
| SubjectTerms | Algorithms Arrhythmias, Cardiac - complications Arrhythmias, Cardiac - diagnosis Biomedical Research Computer Communication Networks - economics Confidentiality Cost-Benefit Analysis Databases, Factual Death, Sudden Electrocardiography Electrophysiologic Techniques, Cardiac Epilepsy - complications Epilepsy - physiopathology Health Insurance Portability and Accountability Act Humans Internet Signal Processing, Computer-Assisted United States |
| Title | Heart beats in the cloud: distributed analysis of electrophysiological 'Big Data' using cloud computing for epilepsy clinical research |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/24326538 https://www.proquest.com/docview/1499132984 |
| Volume | 21 |
| WOSCitedRecordID | wos000331263600012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEF7Uinjx_agvRhB6CrXpdpP1Ir5KD7b0oJJb2OyjVmoSTSv4B_zdziZbPAmCl5AcNoTdycw3O7PfR8jZORcqNIjcNAY7D-Ot8kTgY7JilOlY_jBTnuN-ug8GgzCK-NBtuBWurXLuE0tHrTJp98ibiOS5FUUP6WX-5lnVKFtddRIai6TWRihjW7qC6KeKgKG9U_Kl-oGHuDlyrEOtNmuK17F4SSdoJFbdwAY-9jvGLGNNd_2_X7lB1hzKhKvKLDbJgk63yErf1dG3yVcPDXwKCTriAsYpIAoEOclm6gKUZdK1IlhagXCMJZAZcHo55U7I3GFC43o8glsxFQ2wDfSj6iUgS6kI-4yQGHSOnicvPmF-ChMcw9DzDnns3j3c9DynyOBJBHZTL-GhoFIgqNRMtDHXkNwgiFBUtiTOtmYqYIyGgiNuNEEgWSs0QkqqWeL7kjN_lyylWar3CRhjUzUtEkspZ6iPNzzQSoVJW1GuTZ2czmc4Rou3ZQyR6mxWxD9zXCd71TLFeUXNEfsU4Sj68IM_jD4kq7j6tGooOyI1g_-7PibL8mM6Lt5PSlPC62DY_wbUZdYV |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Heart+beats+in+the+cloud%3A+distributed+analysis+of+electrophysiological+%27Big+Data%27+using+cloud+computing+for+epilepsy+clinical+research&rft.jtitle=Journal+of+the+American+Medical+Informatics+Association+%3A+JAMIA&rft.au=Sahoo%2C+Satya+S&rft.au=Jayapandian%2C+Catherine&rft.au=Garg%2C+Gaurav&rft.au=Kaffashi%2C+Farhad&rft.date=2014-03-01&rft.issn=1527-974X&rft.eissn=1527-974X&rft.volume=21&rft.issue=2&rft.spage=263&rft_id=info:doi/10.1136%2Famiajnl-2013-002156&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1527-974X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1527-974X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1527-974X&client=summon |