{"_buckets": {"deposit": "83c99df2-3da7-4680-9ad5-787f6aa4cd03"}, "_deposit": {"id": "3960", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3960"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3960", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "A Wheeze Detection Method based on a Time Series Regularity of Time- Frequency Distribution", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "This paper proposes a robust method for wheezesound detection. The presented approach is basedon a time series regularity measure called sampleentropy of a time-frequency distribution (GaborSpectrogram). First, the respiratory sound signalsare segmented into their respectiveinspiration/expiration phases for segment-wisedetection of wheeze sounds. Applying GaborSpectrogram to these extracted segments, timefrequencyrepresentation of each segment isobtained. From this representation, regularity ofeach segment is determined using Sample Entropy.A decision rule is then applied to sample entropysequences to determine whether wheeze or normalsound. The accuracy of method is tested on wheezesounds with low and high intensity wheezeinspirations/expirations segments of respiratorysound signals. The experimental results reveal thatthe overall detection accuracy is 86.25% forinspiration and is 82.5% for expiration."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fourth Local Conference on Parallel and Soft Computing", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Thida, Moe"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2009-12-30"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1676"}, "item_title": "A Wheeze Detection Method based on a Time Series Regularity of Time- Frequency Distribution", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003960", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-08-03"}, "publish_date": "2019-08-03", "publish_status": "0", "recid": "3960", "relation": {}, "relation_version_is_last": true, "title": ["A Wheeze Detection Method based on a Time Series Regularity of Time- Frequency Distribution"], "weko_shared_id": -1}