{"id":"https://openalex.org/W2036302853","doi":"https://doi.org/10.1145/2491148.2493888","title":"Efficient health data compression on mobile devices","display_name":"Efficient health data compression on mobile devices","publication_year":2013,"publication_date":"2013-07-29","ids":{"openalex":"https://openalex.org/W2036302853","doi":"https://doi.org/10.1145/2491148.2493888","mag":"2036302853"},"language":"en","primary_location":{"id":"doi:10.1145/2491148.2493888","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2491148.2493888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM MobiHoc workshop on Pervasive wireless healthcare","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/A5101976681","display_name":"Amit Pande","orcid":"https://orcid.org/0000-0001-5379-4746"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amit Pande","raw_affiliation_strings":["University of California, Davis, Davis, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Davis, Davis, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054943180","display_name":"Eilwoo Baik","orcid":null},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eilwoo Baik","raw_affiliation_strings":["University of California, Davis, Davis, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Davis, Davis, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086439160","display_name":"Prasant Mohapatra","orcid":"https://orcid.org/0000-0002-2768-5308"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasant Mohapatra","raw_affiliation_strings":["University of California, Davis, Davis, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Davis, Davis, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101976681"],"corresponding_institution_ids":["https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":1.3898,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83038581,"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":"25","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.982699990272522,"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"}},"topics":[{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.982699990272522,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7612853646278381},{"id":"https://openalex.org/keywords/huffman-coding","display_name":"Huffman coding","score":0.7175164818763733},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.6188139319419861},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5595043897628784},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.5026125907897949},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.4786209464073181},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.4727374315261841},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4505005478858948},{"id":"https://openalex.org/keywords/entropy-encoding","display_name":"Entropy encoding","score":0.44797223806381226},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.42729029059410095},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.3996034264564514},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.282064288854599},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26914697885513306},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.16624760627746582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11179623007774353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7612853646278381},{"id":"https://openalex.org/C46900642","wikidata":"https://www.wikidata.org/wiki/Q2647","display_name":"Huffman coding","level":3,"score":0.7175164818763733},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6188139319419861},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5595043897628784},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.5026125907897949},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.4786209464073181},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.4727374315261841},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4505005478858948},{"id":"https://openalex.org/C1769480","wikidata":"https://www.wikidata.org/wiki/Q1345239","display_name":"Entropy encoding","level":3,"score":0.44797223806381226},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.42729029059410095},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.3996034264564514},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.282064288854599},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26914697885513306},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.16624760627746582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11179623007774353},{"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/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2491148.2493888","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2491148.2493888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM MobiHoc workshop on Pervasive wireless healthcare","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":24,"referenced_works":["https://openalex.org/W1540310433","https://openalex.org/W1596507538","https://openalex.org/W1603895355","https://openalex.org/W1982365250","https://openalex.org/W1985060287","https://openalex.org/W2009135061","https://openalex.org/W2024323540","https://openalex.org/W2029536526","https://openalex.org/W2030459369","https://openalex.org/W2038576877","https://openalex.org/W2052034095","https://openalex.org/W2088462006","https://openalex.org/W2090722357","https://openalex.org/W2104655872","https://openalex.org/W2112114220","https://openalex.org/W2120790961","https://openalex.org/W2123039691","https://openalex.org/W2132926880","https://openalex.org/W2148500771","https://openalex.org/W2153834233","https://openalex.org/W2160710109","https://openalex.org/W2162592883","https://openalex.org/W2488097972","https://openalex.org/W4236206923"],"related_works":["https://openalex.org/W3118996461","https://openalex.org/W4287393224","https://openalex.org/W2541319825","https://openalex.org/W2071387875","https://openalex.org/W1680283075","https://openalex.org/W3080614128","https://openalex.org/W4239869440","https://openalex.org/W2357670775","https://openalex.org/W2380116549","https://openalex.org/W4385932116"],"abstract_inverted_index":{"There":[0],"is":[1,120,136],"an":[2],"increase":[3],"rise":[4],"in":[5,12,70,81,92,158,171,179,199],"the":[6,77,88,125,130,133,152],"usage":[7,31],"of":[8,40,90,129,140],"mobile":[9],"health":[10],"sensors":[11],"wearable":[13],"devices":[14],"and":[15,29,163,177],"smartphones.":[16],"These":[17],"embedded":[18],"systems":[19],"have":[20,149],"tight":[21],"limits":[22],"on":[23],"storage,":[24],"computation":[25],"power,":[26],"network":[27],"connectivity":[28],"battery":[30],"making":[32],"it":[33],"important":[34],"to":[35,43,76,104,122,143,168],"ensure":[36],"efficient":[37],"storage/":[38],"communication":[39],"sensor":[41],"readings":[42],"centralized":[44],"node/":[45],"server.":[46],"Frequency":[47],"Transform":[48],"or":[49,56,73,101,192],"Entropy":[50],"encoding":[51],"schemes":[52],"such":[53,97],"as":[54,98,193],"arithmetic":[55],"Huffman":[57],"coding":[58],"can":[59,188],"be":[60,189],"used":[61,87,121,190],"for":[62,111,154,196],"compression,":[63],"but":[64],"they":[65],"incur":[66],"high":[67],"computational":[68],"cost":[69,109],"some":[71],"scenarios":[72],"are":[74],"oblivious":[75],"higher":[78],"level":[79],"redundancies":[80],"signal.":[82,131],"To":[83],"this":[84],"end,":[85],"we":[86],"property":[89],"periodicity":[91,128],"these":[93],"naturally":[94],"occurring":[95],"signals":[96],"heart":[99],"rate":[100],"gait":[102],"measurements":[103],"design":[105],"a":[106,115,144],"simple":[107],"low":[108],"scheme":[110,153,187],"data":[112,162],"compression.":[113],"First,":[114],"modified":[116],"Chi-square":[117],"periodogram":[118],"metric":[119],"adaptively":[123],"determine":[124],"exact":[126],"time-varying":[127],"Next,":[132],"time-series":[134],"signal":[135],"folded":[137],"into":[138],"Frames":[139],"length":[141],"equal":[142],"pre-determined":[145],"period":[146],"value.":[147],"We":[148],"successfully":[150],"tested":[151],"good":[155],"compression":[156,170],"performance":[157],"ECG,":[159],"motion":[160],"accelerometer":[161],"Parkinson":[164],"patients":[165],"samples,":[166],"leading":[167],"8-14X":[169],"large":[172],"sample":[173,181],"sizes":[174,182],"(6-8K":[175],"samples)":[176],"2-3X":[178],"small":[180],"(200":[183],"samples).":[184],"The":[185],"proposed":[186],"stand-alone":[191],"pre-processing":[194],"step":[195],"existing":[197],"techniques":[198],"literature.":[200]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
