000 01549nam a2200385 i 4500
005 20250930141809.0
008 170310s2015 my a m 000 0 eng d
039 9 _a201705191126
_bhendon
_c201705191123
_dhendon
_y03-10-2017
_zhamdan
040 _aUKM
_erda
090 _aR857.D47S337 2015 3 tesis
090 _aR857.D47
_bS337 2015 3
100 0 _aSahnius Usman,
_eauthor.
245 4 0 _aNon-invasive discrimnation between diabetic states (HBA1C < 8% and HBA1C > 10%) using photoplethysmography /
_cSahnius Usman.
246 3 4 _aNon-invasive discrimnation between diabetic (HBA1C < 8% and HBA1C > 10%) using photoplethysmography.
264 0 _c2015.
300 _axviii, 152 pages :
_billustrations ;
_c30 cm.
336 _atext
_2rdacontent
337 _aunmediated
_2rdamedia
338 _avolume
_2rdacarrier
502 _aThesis (Ph.D) - Universiti Kebangsaan Malaysia, 2015.
504 _aReferences : pages [100]-114.
610 2 0 _aUniversiti Kebangsaan Malaysia
_xDissertations.
_962865
650 0 _aSignal processing
_xDigital techniques.
650 0 _aBiomedical engineering.
650 0 _aSkin
_xBlood flow
_xMeasurement
_xTechnique.
650 0 _aNeural networks (Computer science).
_960531
650 0 _aDissertations, Academic
_zMalaysia.
_962866
907 _a.b16445090
_b2025-07-18
_c2019-11-12
942 _c3
_n0
_kR857.D47S337 2015 3 tesis
914 _avtls003618916
990 _ahak/ha
991 _aFakulti Kejuruteraan dan Alam Bina
998 _al
_b2017-10-03
_cm
_dx
_feng
_gmy
_y0
_z.b16445090
999 _c617701
_d617701